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{"poster":"ScipioElder","date":"2015-01-09T19:13:01.039+0000","title":"Got Pulsefire Ezreal in the mystery gift, but not the icon.","subforum":"[ARCHIVED] Help & Support","up_votes":2,"down_votes":1,"body":"I got Pulsefire Ezreal in the mystery gift from Riot. The icon doesn't show up, even when I log back in. Do we get the icon if we're gifted Pulsefire Ezreal?","replies":[{"poster":"Hollymonster","date":"2015-01-09T19:22:08.911+0000","up_votes":4,"down_votes":0,"body":"Yes, you should. :(\n\nIt's on your account now.","replies":[]},{"poster":"The Gollywog","date":"2017-05-17T11:14:06.518+0000","up_votes":1,"down_votes":0,"body":"I did not receive it as well. :(\nI submitted a ticket, hopefully it will be fixed. :)","replies":[]},{"poster":"quazie","date":"2015-10-15T19:25:20.456+0000","up_votes":1,"down_votes":0,"body":"got the pulsefire ezreal tx riot:) but not the icon can i still get it?","replies":[]},{"poster":"Eambo","date":"2015-01-11T05:16:38.053+0000","up_votes":1,"down_votes":0,"body":"Hi guys,\n\nPlease submit a ticket to Riot at http://support.leagueoflegends.com and they'll be able to add this to your account as Hollymonster did above :-)","replies":[]},{"poster":"aJILLity","date":"2015-01-09T20:49:56.514+0000","up_votes":1,"down_votes":0,"body":"hey Lukirus,\n\nIf Hollymonster doesn't notice this, write in a support ticket!","replies":[]},{"poster":"Irus","date":"2015-01-09T19:57:02.577+0000","up_votes":1,"down_votes":0,"body":"This happened to me too, I don't have an icon :(","replies":[]},{"poster":"Oblivion Drakon","date":"2015-01-11T05:15:59.238+0000","up_votes":0,"down_votes":0,"body":"This also happened to me :( and I don't have the icon :(","replies":[]}]} |
{"tag": "2", "title": ["pippen", "call", "quit"], "text": ["scotti", "pippen", "one", "member", "legendari", "chicago", "bull", "team", "scoop", "six", "nba", "titl", "1990", "announc", "retir", "today"]} |
{"poster":"Yàmii","date":"2019-03-31T15:10:02.122+0000","title":"cerco player","subforum":"Reclutamento","up_votes":0,"down_votes":0,"body":"salve a tutti cerco player con cui giocare visto che ho appena cominciato a giocare","replies":[]} |
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Common approaches use the few labeled pixels in all training images to train a segmentation model, and then propagate labels within each image based on visual or feature similarity. Instead, we treat segmentation as a semi-supervised pixel-wise metric learning problem, where pixels in different segments are mapped to distinctive features. Naturally, our unlabeled pixels participate not only in data-driven grouping within each image, but also in discriminative feature learning within and across images. Our results on Pascal VOC and DensePose datasets demonstrate our substantial accuracy gain on various forms of weak supervision including image-level tags, bounding boxes, labeled points, and scribbles.", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "ke|universal_weakly_supervised_segmentation_by_pixeltosegment_contrastive_learning", "one-sentence_summary": "We propose a unified pixel-to-segment contrastive learning loss formulation for weakly supervised semantic segmentation with various types of annotations. 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Accordingly, I propose to accept this paper at ICLR 2021."}, "signatures": ["ICLR.cc/2021/Conference/Program_Chairs"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference/Program_Chairs"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning", "authorids": ["~Tsung-Wei_Ke2", "~Jyh-Jing_Hwang1", "~Stella_Yu2"], "authors": ["Tsung-Wei Ke", "Jyh-Jing Hwang", "Stella Yu"], "keywords": ["weakly supervised representation learning", "representation learning for computer vision", "metric learning", "semantic segmentation"], "abstract": "Weakly supervised segmentation is challenging as sparsely labeled pixels do not provide sufficient supervision: A semantic segment may contain multiple distinctive regions whereas adjacent segments may appear similar. 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After deciding the label of each segment in the training set, we use them for the nearest neighbor search to predict the label of query segments during inference. We\u2019ll include detailed description in the final version.\n\nQ2: Does the inference take a long time?\n* We refer to Table 4 in the SegSort paper for the ablation study on runtime. The computation bottleneck is the iterative K-Means algorithm rather than nearest neighbor search as the latter can be well parallelized on GPUs. Also, one can replace the nearest neighbor search by training a linear classifier. In terms of the runtime of iterative K-Means for 576 segments, one can consider each iteration is equivalent to a convolutional layer with 576 dimension on top of the last embedding layer, whose resolution is very small. 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Our results on Pascal VOC and DensePose datasets demonstrate our substantial accuracy gain on various forms of weak supervision including image-level tags, bounding boxes, labeled points, and scribbles.", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "ke|universal_weakly_supervised_segmentation_by_pixeltosegment_contrastive_learning", "one-sentence_summary": "We propose a unified pixel-to-segment contrastive learning loss formulation for weakly supervised semantic segmentation with various types of annotations. ", "pdf": "/pdf/c8c53f398e0c806b3eb6ece878b69731dbd16bd5.pdf", "venueid": "ICLR.cc/2021/Conference", "venue": "ICLR 2021 Poster", "_bibtex": "@inproceedings{\nke2021universal,\ntitle={Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning},\nauthor={Tsung-Wei Ke and Jyh-Jing Hwang and Stella Yu},\nbooktitle={International Conference on Learning Representations},\nyear={2021},\nurl={https://openreview.net/forum?id=N33d7wjgzde}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters). Add formatting using Markdown and formulas using LaTeX. For more information see https://openreview.net/faq", "required": true, "markdown": true}}, "forum": "N33d7wjgzde", "readers": {"description": "Who your comment will be visible to. If replying to a specific person make sure to add the group they are a member of so that they are able to see your response", "values-dropdown": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper203/Area_Chairs"], "default": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper203/Area_Chairs"]}, "writers": {"values-copied": ["ICLR.cc/2021/Conference", "{signatures}"]}, "signatures": {"values-regex": "ICLR.cc/2021/Conference/Paper203/AnonReviewer[0-9]+|ICLR.cc/2021/Conference/Paper203/Authors|ICLR.cc/2021/Conference/Paper203/Area_Chair[0-9]+|ICLR.cc/2021/Conference/Program_Chairs", "description": "How your identity will be displayed."}}, "expdate": 1610649480000, "final": [], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper203/Area_Chairs", "ICLR.cc/2021/Conference/Program_Chairs", "OpenReview.net/Support"], "noninvitees": [], "tcdate": 1601923873522, "tmdate": 1610649509835, "super": "ICLR.cc/2021/Conference/-/Comment", "signatures": ["ICLR.cc/2021/Conference"], "writers": ["ICLR.cc/2021/Conference"], "id": "ICLR.cc/2021/Conference/Paper203/-/Official_Comment"}}}, {"id": "yLb_-AKsAm", "original": null, "number": 5, "cdate": 1606222048121, "ddate": null, "tcdate": 1606222048121, "tmdate": 1606222394768, "tddate": null, "forum": "N33d7wjgzde", "replyto": "T9QuyHfckA6", "invitation": "ICLR.cc/2021/Conference/Paper203/-/Official_Comment", "content": {"title": "Thanks for recognizing that our pixel-to-segment contrastive loss formulation is intriguing and our exploration of relationships within- and across-images is insightful", "comment": "Thanks for recognizing that our pixel-to-segment contrastive loss formulation is intriguing and our exploration of relationships within- and across-images is insightful. Now we address the concerns you raised.\n\nQ1: Lack of theoretical novelty?\n* We are the first one to consider within- and across-image relationships in a contrastive learning formulation in order to provide a unifying solution for various forms of weakly supervised segmentation problems, even though the basic form of the loss was first introduced in SegSort. More importantly, we showcase how to augment the supervision spatially and semantically by simply mining visual relationships from the data and integrating them in a single, easily optimizable, contrastive learning loss for pixel-wise feature embedding. While none of these relationships are always correct, they deliver substantial performance gains with the final representation and reach new SOTAs. The success of our novel modeling approach opens up a new direction on exploring more visual relationships for computer vision tasks in general. \n\nQ2: Assess the accumulated errors from pseudo labels?\n* This is a nice suggested analysis! We generate pseudo labels using the feature affinity propagation and measure the accuracy using ground truth masks. We find that such pseudo labels only account for 45.83% accuracy, which is quite inaccurate. Therefore, using only the feature affinity relationship would deteriorate the training quality. To conclude, different relationships compensate each other and together enable the model to learn better representations.\n"}, "signatures": ["ICLR.cc/2021/Conference/Paper203/Authors"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper203/Authors"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning", "authorids": ["~Tsung-Wei_Ke2", "~Jyh-Jing_Hwang1", "~Stella_Yu2"], "authors": ["Tsung-Wei Ke", "Jyh-Jing Hwang", "Stella Yu"], "keywords": ["weakly supervised representation learning", "representation learning for computer vision", "metric learning", "semantic segmentation"], "abstract": "Weakly supervised segmentation is challenging as sparsely labeled pixels do not provide sufficient supervision: A semantic segment may contain multiple distinctive regions whereas adjacent segments may appear similar. Common approaches use the few labeled pixels in all training images to train a segmentation model, and then propagate labels within each image based on visual or feature similarity. Instead, we treat segmentation as a semi-supervised pixel-wise metric learning problem, where pixels in different segments are mapped to distinctive features. Naturally, our unlabeled pixels participate not only in data-driven grouping within each image, but also in discriminative feature learning within and across images. Our results on Pascal VOC and DensePose datasets demonstrate our substantial accuracy gain on various forms of weak supervision including image-level tags, bounding boxes, labeled points, and scribbles.", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "ke|universal_weakly_supervised_segmentation_by_pixeltosegment_contrastive_learning", "one-sentence_summary": "We propose a unified pixel-to-segment contrastive learning loss formulation for weakly supervised semantic segmentation with various types of annotations. ", "pdf": "/pdf/c8c53f398e0c806b3eb6ece878b69731dbd16bd5.pdf", "venueid": "ICLR.cc/2021/Conference", "venue": "ICLR 2021 Poster", "_bibtex": "@inproceedings{\nke2021universal,\ntitle={Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning},\nauthor={Tsung-Wei Ke and Jyh-Jing Hwang and Stella Yu},\nbooktitle={International Conference on Learning Representations},\nyear={2021},\nurl={https://openreview.net/forum?id=N33d7wjgzde}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters). Add formatting using Markdown and formulas using LaTeX. For more information see https://openreview.net/faq", "required": true, "markdown": true}}, "forum": "N33d7wjgzde", "readers": {"description": "Who your comment will be visible to. If replying to a specific person make sure to add the group they are a member of so that they are able to see your response", "values-dropdown": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper203/Area_Chairs"], "default": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper203/Area_Chairs"]}, "writers": {"values-copied": ["ICLR.cc/2021/Conference", "{signatures}"]}, "signatures": {"values-regex": "ICLR.cc/2021/Conference/Paper203/AnonReviewer[0-9]+|ICLR.cc/2021/Conference/Paper203/Authors|ICLR.cc/2021/Conference/Paper203/Area_Chair[0-9]+|ICLR.cc/2021/Conference/Program_Chairs", "description": "How your identity will be displayed."}}, "expdate": 1610649480000, "final": [], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper203/Area_Chairs", "ICLR.cc/2021/Conference/Program_Chairs", "OpenReview.net/Support"], "noninvitees": [], "tcdate": 1601923873522, "tmdate": 1610649509835, "super": "ICLR.cc/2021/Conference/-/Comment", "signatures": ["ICLR.cc/2021/Conference"], "writers": ["ICLR.cc/2021/Conference"], "id": "ICLR.cc/2021/Conference/Paper203/-/Official_Comment"}}}, {"id": "Kyo5nCrxWJF", "original": null, "number": 3, "cdate": 1606221658715, "ddate": null, "tcdate": 1606221658715, "tmdate": 1606222362743, "tddate": null, "forum": "N33d7wjgzde", "replyto": "ZTbEayq8pm-", "invitation": "ICLR.cc/2021/Conference/Paper203/-/Official_Comment", "content": {"title": "Thank you for acknowledging that our proposed framework unifies various annotations for weakly supervised semantic segmentation and achieves SOTA results", "comment": "Thank you for acknowledging that our proposed framework unifies various annotations for weakly supervised semantic segmentation and achieves SOTA results.\n\nQ: Not new compared to Guided Attention Inference Network (GAIN)?\n\n* Thanks for bringing this work to our attention! We will also mention this comparison in the main paper. To compare our method with GAIN, we would like to first point out that GAIN only deals with image tags, bounding boxes, or full segmentation masks. The idea of GAIN is to utilize these annotations to refine class-specific attentional maps. On the other hand, our framework is more general, with which we tackle all types of weak annotations, including scribbles, points, images tags, and bounding boxes. \n\n* It is worth noting that each of the annotations carries different assumptions: 1) Image tags provide only semantic information but no locations; 2) Bounding boxes precisely indicate background regions, but only roughly outline the size and location of objects, without knowing the pixels on the objects; 3) Scribbles and points show the object foreground, but the boundary between background and foreground remains unknown. \n\n* In particular, it is unclear how GAIN can be extended to scribbles or points, which provide more precisely localized cues than other forms of weak annotations. In contrast, our method unifies all these types of weak annotations (each with its own characterization and assumptions) in a single contrastive learning framework and achieves SOTA performance across the board.\n"}, "signatures": ["ICLR.cc/2021/Conference/Paper203/Authors"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper203/Authors"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning", "authorids": ["~Tsung-Wei_Ke2", "~Jyh-Jing_Hwang1", "~Stella_Yu2"], "authors": ["Tsung-Wei Ke", "Jyh-Jing Hwang", "Stella Yu"], "keywords": ["weakly supervised representation learning", "representation learning for computer vision", "metric learning", "semantic segmentation"], "abstract": "Weakly supervised segmentation is challenging as sparsely labeled pixels do not provide sufficient supervision: A semantic segment may contain multiple distinctive regions whereas adjacent segments may appear similar. Common approaches use the few labeled pixels in all training images to train a segmentation model, and then propagate labels within each image based on visual or feature similarity. Instead, we treat segmentation as a semi-supervised pixel-wise metric learning problem, where pixels in different segments are mapped to distinctive features. Naturally, our unlabeled pixels participate not only in data-driven grouping within each image, but also in discriminative feature learning within and across images. Our results on Pascal VOC and DensePose datasets demonstrate our substantial accuracy gain on various forms of weak supervision including image-level tags, bounding boxes, labeled points, and scribbles.", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "ke|universal_weakly_supervised_segmentation_by_pixeltosegment_contrastive_learning", "one-sentence_summary": "We propose a unified pixel-to-segment contrastive learning loss formulation for weakly supervised semantic segmentation with various types of annotations. ", "pdf": "/pdf/c8c53f398e0c806b3eb6ece878b69731dbd16bd5.pdf", "venueid": "ICLR.cc/2021/Conference", "venue": "ICLR 2021 Poster", "_bibtex": "@inproceedings{\nke2021universal,\ntitle={Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning},\nauthor={Tsung-Wei Ke and Jyh-Jing Hwang and Stella Yu},\nbooktitle={International Conference on Learning Representations},\nyear={2021},\nurl={https://openreview.net/forum?id=N33d7wjgzde}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters). Add formatting using Markdown and formulas using LaTeX. For more information see https://openreview.net/faq", "required": true, "markdown": true}}, "forum": "N33d7wjgzde", "readers": {"description": "Who your comment will be visible to. If replying to a specific person make sure to add the group they are a member of so that they are able to see your response", "values-dropdown": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper203/Area_Chairs"], "default": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper203/Area_Chairs"]}, "writers": {"values-copied": ["ICLR.cc/2021/Conference", "{signatures}"]}, "signatures": {"values-regex": "ICLR.cc/2021/Conference/Paper203/AnonReviewer[0-9]+|ICLR.cc/2021/Conference/Paper203/Authors|ICLR.cc/2021/Conference/Paper203/Area_Chair[0-9]+|ICLR.cc/2021/Conference/Program_Chairs", "description": "How your identity will be displayed."}}, "expdate": 1610649480000, "final": [], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper203/Area_Chairs", "ICLR.cc/2021/Conference/Program_Chairs", "OpenReview.net/Support"], "noninvitees": [], "tcdate": 1601923873522, "tmdate": 1610649509835, "super": "ICLR.cc/2021/Conference/-/Comment", "signatures": ["ICLR.cc/2021/Conference"], "writers": ["ICLR.cc/2021/Conference"], "id": "ICLR.cc/2021/Conference/Paper203/-/Official_Comment"}}}, {"id": "Ph_E6Q9cnTN", "original": null, "number": 4, "cdate": 1606221868184, "ddate": null, "tcdate": 1606221868184, "tmdate": 1606222351159, "tddate": null, "forum": "N33d7wjgzde", "replyto": "tTFY4-YUaPv", "invitation": "ICLR.cc/2021/Conference/Paper203/-/Official_Comment", "content": {"title": "We appreciate your recognition that our work is interesting and our results are validated qualitatively and quantitatively", "comment": "We appreciate your recognition that our work is interesting and our results are validated qualitatively and quantitatively. Here we list your questions and answer them accordingly.\n\nQ1: Big performance gain for the \"labeled points\" annotation type?\n\n* The \"labeled points\" annotation provides much sparser localization information than scribbles yet more precise foreground localization cues than bounding boxes. Existing works are highly specialized for either scribbles by propagating and enhancing the mask boundaries or bounding boxes by injecting priors using CAM; neither can generalize well to the more extreme \"labeled points\" annotations. Our method unifies all these types of weak supervision with equal ease and is thus able to provide most performance gain for this challenging annotation type.\n\n\nQ2: Compare with Sun et al. 2020 and Fan et al. 2020?\n\n* Thanks for referring to these two works! We will introduce them in the related work as well. [Sun et al 2020] considers within-image relationships and explores the idea of co-segmentation, whereas [Fan et al 2020] estimates the foreground and background for each category, with which the network learns to generate more precise CAMs. Our method approaches weakly supervised semantic segmentation as a semi-supervised metric learning problem, with the goal of propagating semantic labels to unlabeled pixels in a unifying and flexible contrastive learning framework. A unique, novel, and most advantageous aspect of our method is that we contrast both labeled and unlabeled pixels within and across images with equal ease, bringing a substantial performance gain that has not been met by any other approach.\n\nQ3: The metric in Table 2?\n* The metric in Table 2 is based on mIoU, the most commonly adopted semantic segmentation metric.\n\nQ4: How to decide lambda values in Table 1?\n* The lambda values are decided by experimental validation, as a generic hyperparameter selection problem. Table 5 in the Appendix details our ablation studies on the effects of loss-weighting parameters.\n\nQ5: Descriptions can be crisper?\n* Yes! We\u2019ll keep polishing the writing of our paper.\n"}, "signatures": ["ICLR.cc/2021/Conference/Paper203/Authors"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper203/Authors"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning", "authorids": ["~Tsung-Wei_Ke2", "~Jyh-Jing_Hwang1", "~Stella_Yu2"], "authors": ["Tsung-Wei Ke", "Jyh-Jing Hwang", "Stella Yu"], "keywords": ["weakly supervised representation learning", "representation learning for computer vision", "metric learning", "semantic segmentation"], "abstract": "Weakly supervised segmentation is challenging as sparsely labeled pixels do not provide sufficient supervision: A semantic segment may contain multiple distinctive regions whereas adjacent segments may appear similar. Common approaches use the few labeled pixels in all training images to train a segmentation model, and then propagate labels within each image based on visual or feature similarity. Instead, we treat segmentation as a semi-supervised pixel-wise metric learning problem, where pixels in different segments are mapped to distinctive features. Naturally, our unlabeled pixels participate not only in data-driven grouping within each image, but also in discriminative feature learning within and across images. Our results on Pascal VOC and DensePose datasets demonstrate our substantial accuracy gain on various forms of weak supervision including image-level tags, bounding boxes, labeled points, and scribbles.", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "ke|universal_weakly_supervised_segmentation_by_pixeltosegment_contrastive_learning", "one-sentence_summary": "We propose a unified pixel-to-segment contrastive learning loss formulation for weakly supervised semantic segmentation with various types of annotations. ", "pdf": "/pdf/c8c53f398e0c806b3eb6ece878b69731dbd16bd5.pdf", "venueid": "ICLR.cc/2021/Conference", "venue": "ICLR 2021 Poster", "_bibtex": "@inproceedings{\nke2021universal,\ntitle={Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning},\nauthor={Tsung-Wei Ke and Jyh-Jing Hwang and Stella Yu},\nbooktitle={International Conference on Learning Representations},\nyear={2021},\nurl={https://openreview.net/forum?id=N33d7wjgzde}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters). Add formatting using Markdown and formulas using LaTeX. For more information see https://openreview.net/faq", "required": true, "markdown": true}}, "forum": "N33d7wjgzde", "readers": {"description": "Who your comment will be visible to. If replying to a specific person make sure to add the group they are a member of so that they are able to see your response", "values-dropdown": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper203/Area_Chairs"], "default": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper203/Area_Chairs"]}, "writers": {"values-copied": ["ICLR.cc/2021/Conference", "{signatures}"]}, "signatures": {"values-regex": "ICLR.cc/2021/Conference/Paper203/AnonReviewer[0-9]+|ICLR.cc/2021/Conference/Paper203/Authors|ICLR.cc/2021/Conference/Paper203/Area_Chair[0-9]+|ICLR.cc/2021/Conference/Program_Chairs", "description": "How your identity will be displayed."}}, "expdate": 1610649480000, "final": [], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper203/Area_Chairs", "ICLR.cc/2021/Conference/Program_Chairs", "OpenReview.net/Support"], "noninvitees": [], "tcdate": 1601923873522, "tmdate": 1610649509835, "super": "ICLR.cc/2021/Conference/-/Comment", "signatures": ["ICLR.cc/2021/Conference"], "writers": ["ICLR.cc/2021/Conference"], "id": "ICLR.cc/2021/Conference/Paper203/-/Official_Comment"}}}, {"id": "P6lol6-XSus", "original": null, "number": 6, "cdate": 1606222296838, "ddate": null, "tcdate": 1606222296838, "tmdate": 1606222296838, "tddate": null, "forum": "N33d7wjgzde", "replyto": "-CIOT0L8ObO", "invitation": "ICLR.cc/2021/Conference/Paper203/-/Official_Comment", "content": {"title": "Thanks for acknowledging that our work is interesting, effective, and validated by different benchmarks", "comment": "Thanks for acknowledging that our work is interesting, effective, and validated by different benchmarks. Here we respond to your insightful comments.\n\nQ1: Technical contribution is limited?\n* We are the first one to consider within- and across-image relationships in a contrastive learning formulation in order to provide a unifying solution for various forms of weakly supervised segmentation problems, even though the basic form of the loss was first introduced in SegSort. More importantly, we showcase how to augment the supervision spatially and semantically by simply mining visual relationships from the data and integrating them in a single, easily optimizable, contrastive learning loss for pixel-wise feature embedding. While none of these relationships are always correct, they deliver substantial performance gains with the final representation and reach new SOTAs. The success of our novel modeling approach opens up a new direction on exploring more visual relationships for computer vision tasks in general. \n\nQ2: Effectiveness of the proposed relationships, such as semantic co-occurrence?\n* Yes! How to capture scene context using semantic co-occurrence relationships can be dependent on the nature of the dataset, and introducing weights by computed categorical co-occurrences is a great suggestion! For example, if a dataset contains both indoor and outdoor scenes, people appearing with cats and people with vehicles represent two types of scenes and can be modeled separately.\n\n* Furthermore, we\u2019d like to point out that the formulation of our loss function (exp(-d)) also implicitly handles this situation. So long as in the feature space, there is at least one segment very close to the query pixel, the (pulling) effect of other far away segments would be neglected. In other words, the learned embedding allows multiple subclusters for one category. Therefore, if the batch contains enough images to cover at least one other similar scene, this semantic co-occurrence relationship can still be effective. To conclude, a larger batch size or a memory bank to store cross-batch exemplars could help mitigate this issue for a larger and more complex dataset.\n\n\nQ3: Feature affinity is less effective?\n* We propose 4 kinds of relationships, and not a single one is perfect. Even the low-level image similarity cue based on detected edges could be undesirable when examined by itself on an individual image. For example, in Figure 4a, the brown cat is mistakenly attracted to the brown sofa it spread upon, as their colors and textures are highly similar. What is amazing is that the pixel-wise feature embedding that statistically optimizes such 4 kinds (or sometimes 3 kinds) of noisy pixel-to-segment contrastive relationships could deliver SOTA performance on a variety of weakly supervised semantic segmentation problems with equal ease.\n\n* How generally applicable and how relatively important these 4 relationships (such as feature affinity) are to a specific dataset and annotation type can be decided by their relative weights in a pure data-driven fashion, through hyperparameter selection on the validation set (as done in our experiments). \n\n* Our contribution is to augment supervision by discovering and incorporating various visual relationships into a contrastive learning formulation. There exist other types of visual relationships that can be explored and utilized pending on the visual task.\n\nQ4: Simultaneously leverage different weak labels?\n* Thanks for the great suggestion! We conduct the suggested experiments accordingly and plan to include this in the main paper. We construct two training sets on PASCAL VOC, one with 100% image tags and the other with 50% image tags and 50% bounding boxes. We train our models and summarize their performance in the table below. It shows that training with mixed image tags and bounding boxes can improve the performance by almost 2% mIoU. \n\n| | 100% image tags | 50% image tags + 50% bounding boxes |\n| ------------- |:-------------: |:-------------: |\n| mIoU | 68.6% | 70.3% | \n"}, "signatures": ["ICLR.cc/2021/Conference/Paper203/Authors"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper203/Authors"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning", "authorids": ["~Tsung-Wei_Ke2", "~Jyh-Jing_Hwang1", "~Stella_Yu2"], "authors": ["Tsung-Wei Ke", "Jyh-Jing Hwang", "Stella Yu"], "keywords": ["weakly supervised representation learning", "representation learning for computer vision", "metric learning", "semantic segmentation"], "abstract": "Weakly supervised segmentation is challenging as sparsely labeled pixels do not provide sufficient supervision: A semantic segment may contain multiple distinctive regions whereas adjacent segments may appear similar. Common approaches use the few labeled pixels in all training images to train a segmentation model, and then propagate labels within each image based on visual or feature similarity. Instead, we treat segmentation as a semi-supervised pixel-wise metric learning problem, where pixels in different segments are mapped to distinctive features. Naturally, our unlabeled pixels participate not only in data-driven grouping within each image, but also in discriminative feature learning within and across images. Our results on Pascal VOC and DensePose datasets demonstrate our substantial accuracy gain on various forms of weak supervision including image-level tags, bounding boxes, labeled points, and scribbles.", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "ke|universal_weakly_supervised_segmentation_by_pixeltosegment_contrastive_learning", "one-sentence_summary": "We propose a unified pixel-to-segment contrastive learning loss formulation for weakly supervised semantic segmentation with various types of annotations. ", "pdf": "/pdf/c8c53f398e0c806b3eb6ece878b69731dbd16bd5.pdf", "venueid": "ICLR.cc/2021/Conference", "venue": "ICLR 2021 Poster", "_bibtex": "@inproceedings{\nke2021universal,\ntitle={Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning},\nauthor={Tsung-Wei Ke and Jyh-Jing Hwang and Stella Yu},\nbooktitle={International Conference on Learning Representations},\nyear={2021},\nurl={https://openreview.net/forum?id=N33d7wjgzde}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters). Add formatting using Markdown and formulas using LaTeX. For more information see https://openreview.net/faq", "required": true, "markdown": true}}, "forum": "N33d7wjgzde", "readers": {"description": "Who your comment will be visible to. If replying to a specific person make sure to add the group they are a member of so that they are able to see your response", "values-dropdown": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper203/Area_Chairs"], "default": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper203/Area_Chairs"]}, "writers": {"values-copied": ["ICLR.cc/2021/Conference", "{signatures}"]}, "signatures": {"values-regex": "ICLR.cc/2021/Conference/Paper203/AnonReviewer[0-9]+|ICLR.cc/2021/Conference/Paper203/Authors|ICLR.cc/2021/Conference/Paper203/Area_Chair[0-9]+|ICLR.cc/2021/Conference/Program_Chairs", "description": "How your identity will be displayed."}}, "expdate": 1610649480000, "final": [], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper203/Area_Chairs", "ICLR.cc/2021/Conference/Program_Chairs", "OpenReview.net/Support"], "noninvitees": [], "tcdate": 1601923873522, "tmdate": 1610649509835, "super": "ICLR.cc/2021/Conference/-/Comment", "signatures": ["ICLR.cc/2021/Conference"], "writers": ["ICLR.cc/2021/Conference"], "id": "ICLR.cc/2021/Conference/Paper203/-/Official_Comment"}}}, {"id": "5lRDQEvNjMe", "original": null, "number": 2, "cdate": 1606221506911, "ddate": null, "tcdate": 1606221506911, "tmdate": 1606221506911, "tddate": null, "forum": "N33d7wjgzde", "replyto": "QcnkjfLgdEQ", "invitation": "ICLR.cc/2021/Conference/Paper203/-/Official_Comment", "content": {"title": "Thank you for recognizing our efforts in unifying various annotation types in a metric learning framework and our SOTA performance across all annotations", "comment": "Thank you for recognizing our efforts in unifying various annotation types in a metric learning framework and our SOTA performance across all annotations. Here we list your questions and provide our answers.\n\nQ1: How to apply semantic co-occurrence using image classification models?\n\n* For semantic co-occurrence, we consider whether an image contains a specific object class. For a segment in a training image, all the segments in any other images that contain the same category are positive examples, or otherwise negative. We can thus mine the semantic co-occurrence relationship from either pixel labels, bounding boxes or image tags. The image classification model is not required for the relationship.\n\nQ2: Release code?\n\n* Yes, we are also committed to open source research and will release our code upon publication.\n\nQ3: Metric learning vs contrastive learning?\n\n* While we agree that metric learning is a more general term, our method emphasizes on contrasting segments based on different relationships. Our objective is to contrast a pixel against segments other than its own. Therefore, we name the title of our paper in terms of pixel-to-segment contrastive learning to highlight such a perspective.\n\nQ4: Clarification on the relations between semantic annotations, semantic co-occurrences, and feature affinities?\n\n* Semantic annotations, feature affinities, and semantic co-occurrences characterize semantic relationships at an increasingly higher level: 1) Our supervision is first based on sparsely labeled pixels (scribbles / points / CAM); 2) We then augment our supervision by propagating labels to unlabelled pixels in the feature space, via the feature affinity relationship; 3) We finally consider more global regularization at the scene level, in terms of semantic co-occurrence relationships. These relationships together provide pseudo supervision from low- to high- semantic levels, and from local to more global spatial coverage.\n"}, "signatures": ["ICLR.cc/2021/Conference/Paper203/Authors"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper203/Authors"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning", "authorids": ["~Tsung-Wei_Ke2", "~Jyh-Jing_Hwang1", "~Stella_Yu2"], "authors": ["Tsung-Wei Ke", "Jyh-Jing Hwang", "Stella Yu"], "keywords": ["weakly supervised representation learning", "representation learning for computer vision", "metric learning", "semantic segmentation"], "abstract": "Weakly supervised segmentation is challenging as sparsely labeled pixels do not provide sufficient supervision: A semantic segment may contain multiple distinctive regions whereas adjacent segments may appear similar. Common approaches use the few labeled pixels in all training images to train a segmentation model, and then propagate labels within each image based on visual or feature similarity. Instead, we treat segmentation as a semi-supervised pixel-wise metric learning problem, where pixels in different segments are mapped to distinctive features. Naturally, our unlabeled pixels participate not only in data-driven grouping within each image, but also in discriminative feature learning within and across images. Our results on Pascal VOC and DensePose datasets demonstrate our substantial accuracy gain on various forms of weak supervision including image-level tags, bounding boxes, labeled points, and scribbles.", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "ke|universal_weakly_supervised_segmentation_by_pixeltosegment_contrastive_learning", "one-sentence_summary": "We propose a unified pixel-to-segment contrastive learning loss formulation for weakly supervised semantic segmentation with various types of annotations. ", "pdf": "/pdf/c8c53f398e0c806b3eb6ece878b69731dbd16bd5.pdf", "venueid": "ICLR.cc/2021/Conference", "venue": "ICLR 2021 Poster", "_bibtex": "@inproceedings{\nke2021universal,\ntitle={Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning},\nauthor={Tsung-Wei Ke and Jyh-Jing Hwang and Stella Yu},\nbooktitle={International Conference on Learning Representations},\nyear={2021},\nurl={https://openreview.net/forum?id=N33d7wjgzde}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters). Add formatting using Markdown and formulas using LaTeX. For more information see https://openreview.net/faq", "required": true, "markdown": true}}, "forum": "N33d7wjgzde", "readers": {"description": "Who your comment will be visible to. If replying to a specific person make sure to add the group they are a member of so that they are able to see your response", "values-dropdown": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper203/Area_Chairs"], "default": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper203/Area_Chairs"]}, "writers": {"values-copied": ["ICLR.cc/2021/Conference", "{signatures}"]}, "signatures": {"values-regex": "ICLR.cc/2021/Conference/Paper203/AnonReviewer[0-9]+|ICLR.cc/2021/Conference/Paper203/Authors|ICLR.cc/2021/Conference/Paper203/Area_Chair[0-9]+|ICLR.cc/2021/Conference/Program_Chairs", "description": "How your identity will be displayed."}}, "expdate": 1610649480000, "final": [], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper203/Area_Chairs", "ICLR.cc/2021/Conference/Program_Chairs", "OpenReview.net/Support"], "noninvitees": [], "tcdate": 1601923873522, "tmdate": 1610649509835, "super": "ICLR.cc/2021/Conference/-/Comment", "signatures": ["ICLR.cc/2021/Conference"], "writers": ["ICLR.cc/2021/Conference"], "id": "ICLR.cc/2021/Conference/Paper203/-/Official_Comment"}}}, {"id": "lTbuDjjOjim", "original": null, "number": 1, "cdate": 1605244875635, "ddate": null, "tcdate": 1605244875635, "tmdate": 1605244875635, "tddate": null, "forum": "N33d7wjgzde", "replyto": "N33d7wjgzde", "invitation": "ICLR.cc/2021/Conference/Paper203/-/Public_Comment", "content": {"title": "The inference phase requires pixel-level annotations of the training set and takes a long time?", "comment": "In Appendix A.4, the authors said, \"We produce oversegmentations and calculate the prototypes in the training set. For Pascal VOC and DensePose dataset, We partition each image into 144 and 576 clusters, respectively. We set k = 20 for nearest neighbor retrievals, and then, we infer the semantic label of each queried segment with majority label of retrievals.\" \n\nI have two questions about this inference operation. First, \"label of retrievals\" means that the pixel-level annotations of the training set are required? Second, this inference operation takes a long time? For DensePose, each image will be partitioned into 576 clusters, and retrieval must be performed 576 times for each image. Over-segmentation and retrieval are both time-consuming operations."}, "signatures": ["~Wanxuan_Lu1"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference", "~Wanxuan_Lu1"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning", "authorids": ["~Tsung-Wei_Ke2", "~Jyh-Jing_Hwang1", "~Stella_Yu2"], "authors": ["Tsung-Wei Ke", "Jyh-Jing Hwang", "Stella Yu"], "keywords": ["weakly supervised representation learning", "representation learning for computer vision", "metric learning", "semantic segmentation"], "abstract": "Weakly supervised segmentation is challenging as sparsely labeled pixels do not provide sufficient supervision: A semantic segment may contain multiple distinctive regions whereas adjacent segments may appear similar. Common approaches use the few labeled pixels in all training images to train a segmentation model, and then propagate labels within each image based on visual or feature similarity. Instead, we treat segmentation as a semi-supervised pixel-wise metric learning problem, where pixels in different segments are mapped to distinctive features. Naturally, our unlabeled pixels participate not only in data-driven grouping within each image, but also in discriminative feature learning within and across images. Our results on Pascal VOC and DensePose datasets demonstrate our substantial accuracy gain on various forms of weak supervision including image-level tags, bounding boxes, labeled points, and scribbles.", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "ke|universal_weakly_supervised_segmentation_by_pixeltosegment_contrastive_learning", "one-sentence_summary": "We propose a unified pixel-to-segment contrastive learning loss formulation for weakly supervised semantic segmentation with various types of annotations. ", "pdf": "/pdf/c8c53f398e0c806b3eb6ece878b69731dbd16bd5.pdf", "venueid": "ICLR.cc/2021/Conference", "venue": "ICLR 2021 Poster", "_bibtex": "@inproceedings{\nke2021universal,\ntitle={Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning},\nauthor={Tsung-Wei Ke and Jyh-Jing Hwang and Stella Yu},\nbooktitle={International Conference on Learning Representations},\nyear={2021},\nurl={https://openreview.net/forum?id=N33d7wjgzde}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters). Add formatting using Markdown and formulas using LaTeX. For more information see https://openreview.net/faq", "required": true, "markdown": true}}, "forum": "N33d7wjgzde", "readers": {"description": "User groups that will be able to read this comment.", "values": ["everyone"]}, "writers": {"values-copied": ["ICLR.cc/2021/Conference", "{signatures}"]}, "signatures": {"values-regex": "~.*", "description": "How your identity will be displayed."}}, "expdate": 1605630600000, "final": [], "readers": ["everyone"], "nonreaders": [], "invitees": ["everyone"], "noninvitees": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper203/Authors", "ICLR.cc/2021/Conference/Paper203/Reviewers", "ICLR.cc/2021/Conference/Paper203/Area_Chairs", "ICLR.cc/2021/Conference/Program_Chairs"], "tcdate": 1605024984684, "tmdate": 1610649509835, "super": "ICLR.cc/2021/Conference/-/Comment", "signatures": ["ICLR.cc/2021/Conference"], "writers": ["ICLR.cc/2021/Conference"], "id": "ICLR.cc/2021/Conference/Paper203/-/Public_Comment"}}}, {"id": "-CIOT0L8ObO", "original": null, "number": 1, "cdate": 1603829946788, "ddate": null, "tcdate": 1603829946788, "tmdate": 1605034004056, "tddate": null, "forum": "N33d7wjgzde", "replyto": "N33d7wjgzde", "invitation": "ICLR.cc/2021/Conference/Paper203/-/Official_Review", "content": {"title": "Paper review from AnonReviewer3", "review": "Summary:\n\nThe paper proposes a unified framework for weakly-supervised semantic segmentation that can take various types of weak labels as the input, e.g., points, scribbles, boxes, image tags. The authors formulate it as a contrastive learning framework by considering pixel-to-segment relationships, i.e., for each pixel, finding positive and negative segments to perform contrastive learning objectives. Specifically, the paper introduces four types of relationships between pixels and segments, i.e., image similarity within the image, semantic relationship, semantic co-occurrence, and feature affinity across images. In experiments, results with various weak labels show SOTA performance on the PASCAL and DensePose datasets.\n\nPros:\n\nThe paper is well written and is easy to follow. The proposed unified framework using the idea of pixel-to-segment contrastive learning is interesting for the weakly-supervised semantic segmentation task. \n\nThe proposed four types of pixel-to-segment relationships seem mostly reasonable and effective for different types of weak label inputs.\n\nExtensive experiments are conducted to demonstrate the effectiveness of the proposed framework and show strong performance on the PASCAL and DensePose datasets.\n\nCons:\n\nAlthough using pixel-to-segment contrastive learning is interesting for weakly-supervised semantic segmentation, the technical contribution is a bit limited as it mostly derives from the recent work in Hwang et al., 2019.\n\nIt is not clear to fully understand the effectiveness of the introduced four types of relationships. For example, for semantic co-occurrence, it is doubtful to form positive pairs simply based on the co-occurrence, as the features in two images could be very different even they share at least one same label. This situation could be more significant if performing on more challenging datasets that contain diverse scenes and more categories, e.g., COCO, ADE20K. The authors should make comments on this or provide more analysis for reasoning this design choice, e.g., one easy thing to consider could be weighting this relationship based on the co-occurrence rate.\n\nIt appears that feature affinity is less effective or not used in some settings. Although the authors explain the reason in the appendix (due to noisy label propagation), it may not be a principal way to integrate this feature affinity into any dataset. Moreover, Table 1 shows different configurations for different label types, and it could also vary across different datasets. Although there are ablation studies provided in Table 5 and 6 of the appendix, it is difficult to draw conclusions on how to choose the proper weights. In this way, it makes the practical usage harder to scale up to more challenging datasets.\n\nAnother concern is the motivation and usefulness of the unified framework. In the literature, there exist specific frameworks optimized for different types of weak labels. Previous frameworks could not use all the weak labels at the same time, which is on the contrary the advantage of the proposed method. Therefore, it is of great interest to see whether the method can simultaneously leverage different weak labels and achieve better performance, e.g., using image tags + boxes against only boxes.\n\nOverall, the paper presents an interesting and effective framework. I would like to hear the feedback from the authors about the above-raised points and may update the rating (my current rating is more like a borderline).\n", "rating": "6: Marginally above acceptance threshold", "confidence": "5: The reviewer is absolutely certain that the evaluation is correct and very familiar with the relevant literature"}, "signatures": ["ICLR.cc/2021/Conference/Paper203/AnonReviewer3"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper203/AnonReviewer3"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning", "authorids": ["~Tsung-Wei_Ke2", "~Jyh-Jing_Hwang1", "~Stella_Yu2"], "authors": ["Tsung-Wei Ke", "Jyh-Jing Hwang", "Stella Yu"], "keywords": ["weakly supervised representation learning", "representation learning for computer vision", "metric learning", "semantic segmentation"], "abstract": "Weakly supervised segmentation is challenging as sparsely labeled pixels do not provide sufficient supervision: A semantic segment may contain multiple distinctive regions whereas adjacent segments may appear similar. Common approaches use the few labeled pixels in all training images to train a segmentation model, and then propagate labels within each image based on visual or feature similarity. Instead, we treat segmentation as a semi-supervised pixel-wise metric learning problem, where pixels in different segments are mapped to distinctive features. Naturally, our unlabeled pixels participate not only in data-driven grouping within each image, but also in discriminative feature learning within and across images. Our results on Pascal VOC and DensePose datasets demonstrate our substantial accuracy gain on various forms of weak supervision including image-level tags, bounding boxes, labeled points, and scribbles.", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "ke|universal_weakly_supervised_segmentation_by_pixeltosegment_contrastive_learning", "one-sentence_summary": "We propose a unified pixel-to-segment contrastive learning loss formulation for weakly supervised semantic segmentation with various types of annotations. ", "pdf": "/pdf/c8c53f398e0c806b3eb6ece878b69731dbd16bd5.pdf", "venueid": "ICLR.cc/2021/Conference", "venue": "ICLR 2021 Poster", "_bibtex": "@inproceedings{\nke2021universal,\ntitle={Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning},\nauthor={Tsung-Wei Ke and Jyh-Jing Hwang and Stella Yu},\nbooktitle={International Conference on Learning Representations},\nyear={2021},\nurl={https://openreview.net/forum?id=N33d7wjgzde}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"order": 1, "value-regex": ".{0,500}", "description": "Brief summary of your review.", "required": true}, "review": {"order": 2, "value-regex": "[\\S\\s]{1,200000}", "description": "Please provide an evaluation of the quality, clarity, originality and significance of this work, including a list of its pros and cons (max 200000 characters). Add formatting using Markdown and formulas using LaTeX. For more information see https://openreview.net/faq . ***Please remember to file the Code-of-Ethics report. Once you submitted the review, a link to the report will be visible in the bottom right corner of your review.***", "required": true, "markdown": true}, "rating": {"order": 3, "value-dropdown": ["10: Top 5% of accepted papers, seminal paper", "9: Top 15% of accepted papers, strong accept", "8: Top 50% of accepted papers, clear accept", "7: Good paper, accept", "6: Marginally above acceptance threshold", "5: Marginally below acceptance threshold", "4: Ok but not good enough - rejection", "3: Clear rejection", "2: Strong rejection", "1: Trivial or wrong"], "required": true}, "confidence": {"order": 4, "value-radio": ["5: The reviewer is absolutely certain that the evaluation is correct and very familiar with the relevant literature", "4: The reviewer is confident but not absolutely certain that the evaluation is correct", "3: The reviewer is fairly confident that the evaluation is correct", "2: The reviewer is willing to defend the evaluation, but it is quite likely that the reviewer did not understand central parts of the paper", "1: The reviewer's evaluation is an educated guess"], "required": true}}, "forum": "N33d7wjgzde", "replyto": "N33d7wjgzde", "readers": {"description": "Select all user groups that should be able to read this comment.", "values": ["everyone"]}, "nonreaders": {"values": []}, "writers": {"values-copied": ["ICLR.cc/2021/Conference", "{signatures}"], "description": "How your identity will be displayed."}, "signatures": {"values-regex": "ICLR.cc/2021/Conference/Paper203/AnonReviewer[0-9]+", "description": "How your identity will be displayed."}}, "expdate": 1607428800000, "duedate": 1606752000000, "multiReply": false, "readers": ["everyone"], "tcdate": 1602538148168, "tmdate": 1606915772889, "super": "ICLR.cc/2021/Conference/-/Official_Review", "signatures": ["OpenReview.net"], "writers": ["ICLR.cc/2021/Conference"], "invitees": ["ICLR.cc/2021/Conference/Paper203/Reviewers", "OpenReview.net/Support"], "id": "ICLR.cc/2021/Conference/Paper203/-/Official_Review"}}}, {"id": "tTFY4-YUaPv", "original": null, "number": 3, "cdate": 1603921139396, "ddate": null, "tcdate": 1603921139396, "tmdate": 1605024740768, "tddate": null, "forum": "N33d7wjgzde", "replyto": "N33d7wjgzde", "invitation": "ICLR.cc/2021/Conference/Paper203/-/Official_Review", "content": {"title": "WSSS approach which leverages a single pixel-to-segment contrastive learning", "review": "Summary:\nThis paper talks about a novel weakly-supervised semantic segmentation (WSSS) approach which leverages a single pixel-to-segment contrastive learning formulation. The key idea is to map each pixel into a point in the feature space so that the pixels in the same semantic categories are embedded closely. It is interesting to note that they have also incorporated the analysis of unlabeled pixels across the images to harvest their patterns/clusters for better discrimination.\n\nPros:\n- Motivation was well described.\n- It is interesting to see that four different types of pixel-to-segment (where same segmentation entities were sometimes regarded as different categories) relationships were leveraged in a combined manner to eventually pull up the performance.\n- Experiments are reasonably carried out both qualitatively and quantitatively.\n\nCons/Questions:\n- Would there be a reasonable explanation of why a big performance gain was acquired for the \"labeled points\" case while the jump was relatively small on other weak supervision cases (image tags, bounding boxes, scribbles)?\n- A paper by Sun et al. (Mining Cross-Image Semantics for Weakly Supervised Semantic Segmentation, ECCV 2020) also claims that their approach is novel in that they make use of the intra-image information which is somewhat similar to the proposed approach. A paper by Fan et al. (Learning Integral Objects With Intra-Class Discriminator for Weakly-Supervised Semantic Segmentation, CVPR 2020) seems highly relevant to the proposed approach, especially with the CAM-driven WSSS approaches. \nSince these recent papers have not been included in the reference of the submitted manuscript, it would be interesting to elaborate on how the proposed approach is unique/strong when compared.\n- For Table 2, what is the accuracy measure for the numbers shown?\n- It is hard to tell how the lambda values were chosen. (Table 1)\n- Some descriptions/explanations are rather redundant and verbose which makes it hard to read.\n\nTypo:\nIn Section 1, \"have have\" --> \"have\"", "rating": "7: Good paper, accept", "confidence": "3: The reviewer is fairly confident that the evaluation is correct"}, "signatures": ["ICLR.cc/2021/Conference/Paper203/AnonReviewer1"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper203/AnonReviewer1"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning", "authorids": ["~Tsung-Wei_Ke2", "~Jyh-Jing_Hwang1", "~Stella_Yu2"], "authors": ["Tsung-Wei Ke", "Jyh-Jing Hwang", "Stella Yu"], "keywords": ["weakly supervised representation learning", "representation learning for computer vision", "metric learning", "semantic segmentation"], "abstract": "Weakly supervised segmentation is challenging as sparsely labeled pixels do not provide sufficient supervision: A semantic segment may contain multiple distinctive regions whereas adjacent segments may appear similar. Common approaches use the few labeled pixels in all training images to train a segmentation model, and then propagate labels within each image based on visual or feature similarity. Instead, we treat segmentation as a semi-supervised pixel-wise metric learning problem, where pixels in different segments are mapped to distinctive features. Naturally, our unlabeled pixels participate not only in data-driven grouping within each image, but also in discriminative feature learning within and across images. Our results on Pascal VOC and DensePose datasets demonstrate our substantial accuracy gain on various forms of weak supervision including image-level tags, bounding boxes, labeled points, and scribbles.", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "ke|universal_weakly_supervised_segmentation_by_pixeltosegment_contrastive_learning", "one-sentence_summary": "We propose a unified pixel-to-segment contrastive learning loss formulation for weakly supervised semantic segmentation with various types of annotations. ", "pdf": "/pdf/c8c53f398e0c806b3eb6ece878b69731dbd16bd5.pdf", "venueid": "ICLR.cc/2021/Conference", "venue": "ICLR 2021 Poster", "_bibtex": "@inproceedings{\nke2021universal,\ntitle={Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning},\nauthor={Tsung-Wei Ke and Jyh-Jing Hwang and Stella Yu},\nbooktitle={International Conference on Learning Representations},\nyear={2021},\nurl={https://openreview.net/forum?id=N33d7wjgzde}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"order": 1, "value-regex": ".{0,500}", "description": "Brief summary of your review.", "required": true}, "review": {"order": 2, "value-regex": "[\\S\\s]{1,200000}", "description": "Please provide an evaluation of the quality, clarity, originality and significance of this work, including a list of its pros and cons (max 200000 characters). Add formatting using Markdown and formulas using LaTeX. For more information see https://openreview.net/faq . ***Please remember to file the Code-of-Ethics report. Once you submitted the review, a link to the report will be visible in the bottom right corner of your review.***", "required": true, "markdown": true}, "rating": {"order": 3, "value-dropdown": ["10: Top 5% of accepted papers, seminal paper", "9: Top 15% of accepted papers, strong accept", "8: Top 50% of accepted papers, clear accept", "7: Good paper, accept", "6: Marginally above acceptance threshold", "5: Marginally below acceptance threshold", "4: Ok but not good enough - rejection", "3: Clear rejection", "2: Strong rejection", "1: Trivial or wrong"], "required": true}, "confidence": {"order": 4, "value-radio": ["5: The reviewer is absolutely certain that the evaluation is correct and very familiar with the relevant literature", "4: The reviewer is confident but not absolutely certain that the evaluation is correct", "3: The reviewer is fairly confident that the evaluation is correct", "2: The reviewer is willing to defend the evaluation, but it is quite likely that the reviewer did not understand central parts of the paper", "1: The reviewer's evaluation is an educated guess"], "required": true}}, "forum": "N33d7wjgzde", "replyto": "N33d7wjgzde", "readers": {"description": "Select all user groups that should be able to read this comment.", "values": ["everyone"]}, "nonreaders": {"values": []}, "writers": {"values-copied": ["ICLR.cc/2021/Conference", "{signatures}"], "description": "How your identity will be displayed."}, "signatures": {"values-regex": "ICLR.cc/2021/Conference/Paper203/AnonReviewer[0-9]+", "description": "How your identity will be displayed."}}, "expdate": 1607428800000, "duedate": 1606752000000, "multiReply": false, "readers": ["everyone"], "tcdate": 1602538148168, "tmdate": 1606915772889, "super": "ICLR.cc/2021/Conference/-/Official_Review", "signatures": ["OpenReview.net"], "writers": ["ICLR.cc/2021/Conference"], "invitees": ["ICLR.cc/2021/Conference/Paper203/Reviewers", "OpenReview.net/Support"], "id": "ICLR.cc/2021/Conference/Paper203/-/Official_Review"}}}, {"id": "ZTbEayq8pm-", "original": null, "number": 4, "cdate": 1603951332297, "ddate": null, "tcdate": 1603951332297, "tmdate": 1605024740710, "tddate": null, "forum": "N33d7wjgzde", "replyto": "N33d7wjgzde", "invitation": "ICLR.cc/2021/Conference/Paper203/-/Official_Review", "content": {"title": "great performance but a bit incremental", "review": "The submission proposes a unified framework for weakly supervised semantic segmentation which is compatible with different types of annotations including image tag, bounding box, points and scribbles. With different kinds of labels, the method derives positive and negative segments for each labels and via metric learning the network learns to predict class label for each pixel. While the proposed method obtained STOA or close to SOTA performance on VOC2012 and densepose dataset, the reviewer feels that the novelty of the proposed method is not significant enough. A unified framework for semantic segmentation is appealing but it isn't new. E.g. Guided Attention Inference Network, TPAMI 2019 proposed a way to use gradient-based attention weakly supervised semantic segmentation framework which is compatible with image tags, bounding boxes and pixel-level annotations. In their work, different kinds of annotations are converted into supervision on class-specific attention maps and no parameters need to be tuned based on the ratio/types of annotations are used in the training, whereas the proposed method here needs different parameter choices for different lables/dataset. In the reviewer's eyes the submission follows a similar direction, although the framework design and objectives are different. The reviewer hope the authors can clarify their contribution and add discussions comparing to other similar approaches. ", "rating": "5: Marginally below acceptance threshold", "confidence": "4: The reviewer is confident but not absolutely certain that the evaluation is correct"}, "signatures": ["ICLR.cc/2021/Conference/Paper203/AnonReviewer2"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper203/AnonReviewer2"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning", "authorids": ["~Tsung-Wei_Ke2", "~Jyh-Jing_Hwang1", "~Stella_Yu2"], "authors": ["Tsung-Wei Ke", "Jyh-Jing Hwang", "Stella Yu"], "keywords": ["weakly supervised representation learning", "representation learning for computer vision", "metric learning", "semantic segmentation"], "abstract": "Weakly supervised segmentation is challenging as sparsely labeled pixels do not provide sufficient supervision: A semantic segment may contain multiple distinctive regions whereas adjacent segments may appear similar. Common approaches use the few labeled pixels in all training images to train a segmentation model, and then propagate labels within each image based on visual or feature similarity. Instead, we treat segmentation as a semi-supervised pixel-wise metric learning problem, where pixels in different segments are mapped to distinctive features. Naturally, our unlabeled pixels participate not only in data-driven grouping within each image, but also in discriminative feature learning within and across images. Our results on Pascal VOC and DensePose datasets demonstrate our substantial accuracy gain on various forms of weak supervision including image-level tags, bounding boxes, labeled points, and scribbles.", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "ke|universal_weakly_supervised_segmentation_by_pixeltosegment_contrastive_learning", "one-sentence_summary": "We propose a unified pixel-to-segment contrastive learning loss formulation for weakly supervised semantic segmentation with various types of annotations. ", "pdf": "/pdf/c8c53f398e0c806b3eb6ece878b69731dbd16bd5.pdf", "venueid": "ICLR.cc/2021/Conference", "venue": "ICLR 2021 Poster", "_bibtex": "@inproceedings{\nke2021universal,\ntitle={Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning},\nauthor={Tsung-Wei Ke and Jyh-Jing Hwang and Stella Yu},\nbooktitle={International Conference on Learning Representations},\nyear={2021},\nurl={https://openreview.net/forum?id=N33d7wjgzde}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"order": 1, "value-regex": ".{0,500}", "description": "Brief summary of your review.", "required": true}, "review": {"order": 2, "value-regex": "[\\S\\s]{1,200000}", "description": "Please provide an evaluation of the quality, clarity, originality and significance of this work, including a list of its pros and cons (max 200000 characters). Add formatting using Markdown and formulas using LaTeX. For more information see https://openreview.net/faq . ***Please remember to file the Code-of-Ethics report. Once you submitted the review, a link to the report will be visible in the bottom right corner of your review.***", "required": true, "markdown": true}, "rating": {"order": 3, "value-dropdown": ["10: Top 5% of accepted papers, seminal paper", "9: Top 15% of accepted papers, strong accept", "8: Top 50% of accepted papers, clear accept", "7: Good paper, accept", "6: Marginally above acceptance threshold", "5: Marginally below acceptance threshold", "4: Ok but not good enough - rejection", "3: Clear rejection", "2: Strong rejection", "1: Trivial or wrong"], "required": true}, "confidence": {"order": 4, "value-radio": ["5: The reviewer is absolutely certain that the evaluation is correct and very familiar with the relevant literature", "4: The reviewer is confident but not absolutely certain that the evaluation is correct", "3: The reviewer is fairly confident that the evaluation is correct", "2: The reviewer is willing to defend the evaluation, but it is quite likely that the reviewer did not understand central parts of the paper", "1: The reviewer's evaluation is an educated guess"], "required": true}}, "forum": "N33d7wjgzde", "replyto": "N33d7wjgzde", "readers": {"description": "Select all user groups that should be able to read this comment.", "values": ["everyone"]}, "nonreaders": {"values": []}, "writers": {"values-copied": ["ICLR.cc/2021/Conference", "{signatures}"], "description": "How your identity will be displayed."}, "signatures": {"values-regex": "ICLR.cc/2021/Conference/Paper203/AnonReviewer[0-9]+", "description": "How your identity will be displayed."}}, "expdate": 1607428800000, "duedate": 1606752000000, "multiReply": false, "readers": ["everyone"], "tcdate": 1602538148168, "tmdate": 1606915772889, "super": "ICLR.cc/2021/Conference/-/Official_Review", "signatures": ["OpenReview.net"], "writers": ["ICLR.cc/2021/Conference"], "invitees": ["ICLR.cc/2021/Conference/Paper203/Reviewers", "OpenReview.net/Support"], "id": "ICLR.cc/2021/Conference/Paper203/-/Official_Review"}}}, {"id": "T9QuyHfckA6", "original": null, "number": 2, "cdate": 1603863235857, "ddate": null, "tcdate": 1603863235857, "tmdate": 1605024740650, "tddate": null, "forum": "N33d7wjgzde", "replyto": "N33d7wjgzde", "invitation": "ICLR.cc/2021/Conference/Paper203/-/Official_Review", "content": {"title": "Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning", "review": "In this paper, the authors proposed a metric learning-based semi-supervised semantic segmentation approach. In the proposed method, unlike the conventional semantic segmentation scheme that cast semantic segmentation as pixel-wise classification, they formulate semantic segmentation as pixel-segment contrastive learning. To that end, the authors introduced different positive and negative samples mining mechanisms such as low-level image similarity, semantic annotation, semantic co-occurrence, and feature similarity. Furthermore, the proposed method leverage unlabeled data in discriminative feature learning both within and across images. The validity of the proposed method is demonstrated on Pascal Voc and Dense Pose benchmark datasets.\n\n##########################################################################################\n\n*Strength:\u00a0The formulation of pixel-to-segment based contrastive learning is intriguing. In addition to that, the authors introduced a new insight into collecting positive and negative samples that would be leveraged in contrastive learning. Moreover, the samples involve pixels that come from both intra and inter images.\n\n\n#################################################################################\n\n*Weakness:- The sub-modules used in the proposed approaches are adopted from existing methods thus there is no enough novelty in there.\n-The resulting improvement achieved is impressive however the work lacks theoretical novelty.\n\nQuestion: As some of the semantic relationships are basically generating pseudo-labels, for example, Feature Affinity. Have you conducted any experimental analysis to assess the impact of accumulated error that comes from these Pseudo labels?\n\n######################################################################################\n\n*Reason for score:\nThe proposed work is more of engineering, and it does not have any theoretical novelty; however, formulating semantic segmentation in a contrastive learning context is interesting. Furthermore, the authors demonstrate the effectiveness of the proposed method by showing improvements over the state of the art methods. ", "rating": "6: Marginally above acceptance threshold", "confidence": "4: The reviewer is confident but not absolutely certain that the evaluation is correct"}, "signatures": ["ICLR.cc/2021/Conference/Paper203/AnonReviewer4"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper203/AnonReviewer4"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning", "authorids": ["~Tsung-Wei_Ke2", "~Jyh-Jing_Hwang1", "~Stella_Yu2"], "authors": ["Tsung-Wei Ke", "Jyh-Jing Hwang", "Stella Yu"], "keywords": ["weakly supervised representation learning", "representation learning for computer vision", "metric learning", "semantic segmentation"], "abstract": "Weakly supervised segmentation is challenging as sparsely labeled pixels do not provide sufficient supervision: A semantic segment may contain multiple distinctive regions whereas adjacent segments may appear similar. Common approaches use the few labeled pixels in all training images to train a segmentation model, and then propagate labels within each image based on visual or feature similarity. Instead, we treat segmentation as a semi-supervised pixel-wise metric learning problem, where pixels in different segments are mapped to distinctive features. Naturally, our unlabeled pixels participate not only in data-driven grouping within each image, but also in discriminative feature learning within and across images. Our results on Pascal VOC and DensePose datasets demonstrate our substantial accuracy gain on various forms of weak supervision including image-level tags, bounding boxes, labeled points, and scribbles.", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "ke|universal_weakly_supervised_segmentation_by_pixeltosegment_contrastive_learning", "one-sentence_summary": "We propose a unified pixel-to-segment contrastive learning loss formulation for weakly supervised semantic segmentation with various types of annotations. ", "pdf": "/pdf/c8c53f398e0c806b3eb6ece878b69731dbd16bd5.pdf", "venueid": "ICLR.cc/2021/Conference", "venue": "ICLR 2021 Poster", "_bibtex": "@inproceedings{\nke2021universal,\ntitle={Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning},\nauthor={Tsung-Wei Ke and Jyh-Jing Hwang and Stella Yu},\nbooktitle={International Conference on Learning Representations},\nyear={2021},\nurl={https://openreview.net/forum?id=N33d7wjgzde}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"order": 1, "value-regex": ".{0,500}", "description": "Brief summary of your review.", "required": true}, "review": {"order": 2, "value-regex": "[\\S\\s]{1,200000}", "description": "Please provide an evaluation of the quality, clarity, originality and significance of this work, including a list of its pros and cons (max 200000 characters). Add formatting using Markdown and formulas using LaTeX. For more information see https://openreview.net/faq . ***Please remember to file the Code-of-Ethics report. Once you submitted the review, a link to the report will be visible in the bottom right corner of your review.***", "required": true, "markdown": true}, "rating": {"order": 3, "value-dropdown": ["10: Top 5% of accepted papers, seminal paper", "9: Top 15% of accepted papers, strong accept", "8: Top 50% of accepted papers, clear accept", "7: Good paper, accept", "6: Marginally above acceptance threshold", "5: Marginally below acceptance threshold", "4: Ok but not good enough - rejection", "3: Clear rejection", "2: Strong rejection", "1: Trivial or wrong"], "required": true}, "confidence": {"order": 4, "value-radio": ["5: The reviewer is absolutely certain that the evaluation is correct and very familiar with the relevant literature", "4: The reviewer is confident but not absolutely certain that the evaluation is correct", "3: The reviewer is fairly confident that the evaluation is correct", "2: The reviewer is willing to defend the evaluation, but it is quite likely that the reviewer did not understand central parts of the paper", "1: The reviewer's evaluation is an educated guess"], "required": true}}, "forum": "N33d7wjgzde", "replyto": "N33d7wjgzde", "readers": {"description": "Select all user groups that should be able to read this comment.", "values": ["everyone"]}, "nonreaders": {"values": []}, "writers": {"values-copied": ["ICLR.cc/2021/Conference", "{signatures}"], "description": "How your identity will be displayed."}, "signatures": {"values-regex": "ICLR.cc/2021/Conference/Paper203/AnonReviewer[0-9]+", "description": "How your identity will be displayed."}}, "expdate": 1607428800000, "duedate": 1606752000000, "multiReply": false, "readers": ["everyone"], "tcdate": 1602538148168, "tmdate": 1606915772889, "super": "ICLR.cc/2021/Conference/-/Official_Review", "signatures": ["OpenReview.net"], "writers": ["ICLR.cc/2021/Conference"], "invitees": ["ICLR.cc/2021/Conference/Paper203/Reviewers", "OpenReview.net/Support"], "id": "ICLR.cc/2021/Conference/Paper203/-/Official_Review"}}}, {"id": "QcnkjfLgdEQ", "original": null, "number": 5, "cdate": 1604721151351, "ddate": null, "tcdate": 1604721151351, "tmdate": 1605024740583, "tddate": null, "forum": "N33d7wjgzde", "replyto": "N33d7wjgzde", "invitation": "ICLR.cc/2021/Conference/Paper203/-/Official_Review", "content": {"title": "The paper performs pixel to segment metric learning based on various heuristics and obtains clear SOTA results on various weakly-supervised visual learning tasks", "review": "\nWeakly-supervised image/object segmentation can naturally be formulated as a pixel-level semi-supervised problem. To solve the insufficient supervision problem in weakly-supervised segmentation, the paper proposes to use four kinds of heuristics to provide supervision for training pixel-level metric learning. The takes the advantages of image segments generated from edge detectors (HED & gPB), then low-level image similarity, semantic annotation, semantic co-occurrence, and feature affinity.\n\nThe paper has obvious advantages summarized as follows.\n1. It unifies various weakly-supervised segmentation tasks by proposing pixel-level metric learning.\n2. The paper obtains clear SOTA results and significantly promotes the development of weakly-supervised segmentation.\n\nThe weakness of the paper is its clarity. Lots of details are missing in the paper, e.g., I cannot find how to apply semantic co-occurrence applied in training segmentation models using image classification models. I think this is not the authors' fault. The problem is caused due to there are so many contents in the paper. Thus, I think source codes should be released and well-organized to ensure the reproducibility of the paper.\n\nBesides, the terms in the papers can be re-considered. (1) Although contrastive learning is very popular now, I think the method is better termed as metric learning - its original name. (2) I think there are some redundancy in semantic annotation, semantic co-occurrence, and feature affinity. The relation between them should be clarified and justified.\n\n\n\n", "rating": "7: Good paper, accept", "confidence": "5: The reviewer is absolutely certain that the evaluation is correct and very familiar with the relevant literature"}, "signatures": ["ICLR.cc/2021/Conference/Paper203/AnonReviewer5"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper203/AnonReviewer5"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning", "authorids": ["~Tsung-Wei_Ke2", "~Jyh-Jing_Hwang1", "~Stella_Yu2"], "authors": ["Tsung-Wei Ke", "Jyh-Jing Hwang", "Stella Yu"], "keywords": ["weakly supervised representation learning", "representation learning for computer vision", "metric learning", "semantic segmentation"], "abstract": "Weakly supervised segmentation is challenging as sparsely labeled pixels do not provide sufficient supervision: A semantic segment may contain multiple distinctive regions whereas adjacent segments may appear similar. 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Our results on Pascal VOC and DensePose datasets demonstrate our substantial accuracy gain on various forms of weak supervision including image-level tags, bounding boxes, labeled points, and scribbles.", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "ke|universal_weakly_supervised_segmentation_by_pixeltosegment_contrastive_learning", "one-sentence_summary": "We propose a unified pixel-to-segment contrastive learning loss formulation for weakly supervised semantic segmentation with various types of annotations. 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{"poster":"Inquizelus","date":"2015-10-17T23:46:15.289+0000","title":"Gnar is hilarious in OFA","subforum":"[ARCHIVED] General Discussion","up_votes":1,"down_votes":1,"body":"{{item:3085}} on everyone = every member of the enemy team is taking 14+%maxHP magic damage constantly lmfao","replies":[]} |
{"poster":"Pandeonor","date":"2018-04-02T17:32:03.045+0000","title":"Gibt es eigentlich gute adc´s in Silber?","subforum":"Champions & Gameplay","up_votes":1,"down_votes":1,"body":"Ernsthaft gefragt. Ich weiss, das Silber _schlecht_ spielt. Aber he. Nach dem heutigen Tag bin ich mir nicht mehr sicher ob das nicht irgendwie an der Position liegt. Auf den übrigen gibt es ja noch deutliche Unterschiede. Also - die schlechten Midlaner und Toplaner bei mir und die deutlich besseren bei den anderen. Aber bei den adc´s .... halleluja. Habe heute keine Perle gesehen. Weder im eigenen (haha) noch im anderen Team.\r\n\r\nFür mich als sup eine Katastrophe. Habe doch heute einen gefragt ob er Zyra kennt. "Yes, basics", so die Antwort. :-/ An wen will man sich da noch hängen. An den Dia-smurf-Yasuo etwa? :-/ Ich habe heute sage und schreibe 5 Games in einer Reihe verloren mit Teams bei welchen ich teilweise nur schwer unterscheiden konnte ob die einfach schlecht spielen oder ob deren Rechner 3fps bei 2000ms anzeigen. Meine adc´s dabei 6/16, 7/10, 9/9, 4/9 und 4/9. So etwas gibt es doch nicht. Nicht wenn man trotzdem bei jedem der Spiele den gegnerischen Botlane-Turm zuerst genommen hat und man den eigenen adc zu tode carried. Der Jhin stand ja schon 0/3 nach ein paar Minuten, jede Q der Soraka aufsammelnd und z.T stehend. Ich glaube dieses Team und das Match waren wirklich das schlechteste was ich inkl. der 1000 Normals letzten Jahres jemals hatte. Das war schon nicht mehr "schlecht" das war teilweise _so schlecht_ das ich nicht unterscheiden konnte ob das nicht doch vielleicht Absicht ist. Zwei der Spiele gingen gar 1h.\r\n\r\nDie gegnerischen adc´s waren bis auf eine Quinn ja nicht viel besser. Ach so. Die war ja Toplane. Uh ja. Die Kai´sa mit der Nida sup. Und mein 6/16 Varus. Nein die Kai´sa war nicht gut und deren Tower hatten wir recht fix. In dem Match mit der 4/9 Vayne und dem Dia-Smurf-Yasuo stand ich am Ende gar 11/5/11. Haben wir (13/5 Yasuo-Smurf hin oder her) verloren mit Top und Jngl je 2/6 und eben der Vayne. Aber Nach Silber IV 70LP demote und eben ein Spiel beendet welches sich angefühlt hat wie ein _Botgame_. Der 8/0/10 WW und ich mit 6/3/13 sind da halb gelangweilt durchmarschiert. Die adc´s waren Beide voll aus der Spur. Ashe meinte sie könne nichts dagegen unternehmen das Leona sie stunned, denn sie müsse in Leonas Reichweite gehen. Der gegnerische Draven war ein Totalausfall.\r\n\r\nIch kann nix dagegen machen. {{sticker:sg-janna}} Mein Damage liegt inzwischen bei 30% über dem Schnitt der Zyras jeder beliebigen Liga. Ich bin mit 0,67 Toden in den ersten 10 Minuten m.E. ein super safer Laner. Meine KDA ist in allen drei Punkten besser als der Schnitt, meine Killbeteiligung ist besser, ich kassiere weniger Schaden. GNAAAAAAAAHHHHHHH\r\n\r\nEtwas frustriert heute. {{sticker:sg-soraka}} {{champion:143}}","replies":[{"poster":"Marksmansitter","date":"2018-04-02T21:40:54.217+0000","up_votes":5,"down_votes":0,"body":"Wirklich gut sind ADCs erst in der LCS ^^, die in deiner Elo sind einfach für den Elobereich Durchschnitt und da du da auch bist bist du teilweise nicht besser.\nBesonders mit zyra bist du egtl ziemlich selbständig im Vergleich zu anderen Supports. Du musst als Zyra das early dominieren, so funkitioniert der Champion. Der support hat generell auch meistens mehr Einfluss auf die Laningphase.\nWenn du gut genug bist carriest du die spiele.\n\nIch garantiere dir das du selber viel zu viele Fehler machst, sonst hättest du nach 105 Spielen nicht nur eine 50% winrate auf Zyra.\nIch hoffe du baust GA nicht regelmäßig auf zyra ^^ das ist einfach nur komplett verschwendet.\n\nDenk über deine Tode nach und überleg was du hättest besser machen können. Du stellst auch viel zu wenige Pinkwards..\nDu setzt alle ~30 Minuten (12 Pinks in 370 Minuten) einen pinkward. \nIch z.B. setze alle ~3 Minuten einen (84 pinks in 264 MInuten), nicht das meine Statistik perfekt ist aber pinkwards sind schon enorm wichtig, das wird besonders in silber/bronze/gold unterschätzt.\n\nViel mehr kann man nicht aus op.gg lesen, hinterfrage einfach deine Entscheidungen und versuche es aus einem anderen Blickwinkel zu betrachten.","replies":[]},{"poster":"kidsrtheworstSTD","date":"2018-04-02T17:39:18.443+0000","up_votes":3,"down_votes":0,"body":"wenn der adc gut ist, ist er niocht in silber :)","replies":[{"poster":"AI Marko","date":"2018-04-02T21:01:38.358+0000","up_votes":2,"down_votes":0,"body":"{{sticker:sg-miss-fortune}} \nxDD true","replies":[]}]},{"poster":"D4D0GE","date":"2018-04-05T09:42:28.952+0000","up_votes":2,"down_votes":1,"body":"Ich bin ADC Main und spiele dieses Spiel schon seit 4 Jahren. Ich habe erst letzte season richtig angefangen zu tryharden. Momentan bin ich in silber 3 im solo/duo. Ich spiele mit meinem Main Supp so gut wie immer botlane und ich kann das was du sagst gut nachvollziehen, aber dass heißt nicht, dass es nur schlechte ADC in silber gibt. Ich möchte ja nicht abgehoben klingen aber letzte season hat Riot zum Ende Statistiken für die einzelnen Spieler veröffentlicht und meine waren etwas besser als der durchschnittliche Platinum Spieler. Trotzdem gammel ich noch in silber rum, da es andere Komponenten gibt ( Feeder, Trolle, afkler) die einem vom climben abhalten. Ich will aber nicht sagen dass ich der beste Spieler bin, sondern, dass es auch gute ADCs in silber gibt die halt nicht climben. Die sind aber sehr sehr selten. Ich würde dir auch empfehlen mit einem ADC Main zu duoQn, da du dann besser mit deinem ADC kommunizieren kannst. Ein netter Nebeneffekt beim gemeinsamen duoQn ist, dass man sich quasi passiv verständigt bzw. dass du dich an die Spielweise deines ADCs gewöhnst und somit besser mit ihm harmonieren kannst. Wenn du noch einen ADC brauchst kannst du mich gerne adden wenn du willst. Ich hoffe ich konnte dir helfen und viel Erfolg in der Q","replies":[{"poster":"ToK Wipern","date":"2018-04-05T09:53:19.153+0000","up_votes":2,"down_votes":0,"body":"> Ich möchte ja nicht abgehoben klingen aber letzte season hat Riot zum Ende Statistiken für die einzelnen Spieler veröffentlicht und meine waren etwas besser als der durchschnittliche Platinum Spieler. Trotzdem gammel ich noch in silber rum, da es andere Komponenten gibt ( Feeder, Trolle, afkler) die einem vom climben abhalten. \n\nDas ist auch so ein Irrglaube ...... du hast bessere Stats, aber halt gegen Silber Spieler NICHT gegen Platin Spieler.... nur weil man in Silber die 10cs/min schafft heißt das nicht, dass man auch die 10cs/min in Challenger schafft. Ich kann auch in der Kreisklasse im Fußball Torschützenkönig sein, bin dann aber dennoch nicht so gut wie schlechte Bundesligaspieler ;)\n\nFeeder sind übrigens öfter im Gegnerteam also eher ein Grund zum climben (wenn man nicht selber auch mal feeded) :)","replies":[{"poster":"D4D0GE","date":"2018-04-05T10:13:46.450+0000","up_votes":1,"down_votes":0,"body":"Da hast du Recht. Ich meinte nur, dass ich mit ein bisschen Spielerfahrung spreche die ich in den letzten Wochen und Jahren gesammelt habe. Aber trotzdem danke für dein Kommentar :)","replies":[]}]}]},{"poster":"D0n Pablo","date":"2018-04-02T17:35:11.297+0000","up_votes":1,"down_votes":0,"body":"Falls du dich von meinem ADC Skills überzeugen lassen willst, dann adde mich IG: D0n Pablo\n\nSilber 1 bin ich.","replies":[{"poster":"JavaBase","date":"2018-04-02T19:48:12.065+0000","up_votes":2,"down_votes":0,"body":"Ich spiele Main Adc und kann dir sagen das ich wirklich nur sehr sehr selten einen guten Support habe. \nDie meisten ADC sind vieleicht schlecht aber zumindest wissen sie ungefähr was sie machen müssen. Farmen, nicht sterben, FEtt werden.\n\nLeider wissen viele Supports überhaupt nicht wie man als Support zu spielen hat. Passiv rumstehen ist jedes mal mein Alptraum als ADC.\nViele Supporter finden sie sollten hinten rumstehen und shillden->Komplett falsch,\nEinige meinen sie müssen das Spiel carryn als Zyra, Brand, Velkoz->Kann man machen, aber ist eigentlich nicht Support...\n\nEin guter Support baut pressure allein dadurch auf wo er steht. Sinnvoll Vision aufbauen. 99% aller Supports in Silber haben keine Plan was sie machen müssen.","replies":[]}]},{"poster":"damn bad kitty","date":"2018-04-02T19:04:23.920+0000","up_votes":2,"down_votes":4,"body":"Boa ich kann total mit dir mitempfinden... Ich bin selber Supp Main und nehm eh schon meistens Soraka um die Vollpfosten hoch zu heilen, wenn sie wieder mal blind rein marschieren... Aber was ich heute alles gesehen habe ist echt zum kotzen. Da kann man ja nicht aufsteigen... Ich bin echt mies im Farmen, da wie gesagt Supp Main - aber selbst ich spiel meistens besser ADC auch wenn mein Farm am Anfang immer mies ist. Meistens kann ich den später aufholen...\n\nAber ja, ich empfinde mit dir mit. Da läuft es anfangs gut und wenn der eigenen ADC dann nicht plötzlich anfängt zu feeden, machen es halt die andren Lanes :) Da kann die eigene KDA noch so gut sein... Keine Chance da irgendwas in die richtige Richtung lenken zu können. Da kann man nur hoffen das es wieder besser wird wenn die ganzen Kiddies wieder Schule haben ;)","replies":[{"poster":"Marksmansitter","date":"2018-04-02T21:47:11.625+0000","up_votes":2,"down_votes":0,"body":"Wenn du besser als die anderen bist steigst du garantiert auch auf.","replies":[]}]},{"poster":"ToK Wipern","date":"2018-04-03T18:00:20.968+0000","up_votes":1,"down_votes":0,"body":"also da du bei deinen wins regelmäßig die geringste Killbeteiligung hast würde ich mal daran zweifeln, dass du ein \"guter\" support bist. wer als supp besonders im late solo rumläuft versteht seine rolle nicht. du verkaufst auch relativ oft dein Supportitem, damit gebt ihr vision oder vision-deny auf. der vorteil vom supp ist doch dass er vision geben kann und gleichzeitig denien kann.","replies":[{"poster":"Pandeonor","date":"2018-04-03T21:30:09.930+0000","up_votes":1,"down_votes":0,"body":"> [{quoted}](name=ToK Wipern,realm=EUW,application-id=Wj1wcocU,discussion-id=Mg91Ks1E,comment-id=0008,timestamp=2018-04-03T18:00:20.968+0000)\n>\n> also da du bei deinen wins regelmäßig die geringste Killbeteiligung hast würde ich mal daran zweifeln, dass du ein "guter" support bist. wer als supp besonders im late solo rumläuft versteht seine rolle nicht. \n\nInteressante Betrachtung. Habe gerade nachgesehen. Meine Killbeteiligung bei den letzten 12 Siegen liegt bei 48,5%. Bei den letzten 86 Matches (Siege wie Niederlagen) liegt sie bei 49,5%. Der Schnitt der Silber-Zyras liegt bei 47,2% (Gold 47,4% Platin 47,7% Bronze 46,8% Diamant 48,2%). Wobei das kein Maßstab sein muss, da es nichts darüber aussagt wie hoch eine gute Killbeteiligung sein sollte da es nur der Schnitt ist aus guten wie weniger guten Zyras. [Ich orientiere mich oft an den diamantenen und da wäre ich mit meinen 49,5% im Verhältnis zu 48,2% als Schnitt aller Dia Zyras nicht so schlecht dabei dachte ich.]\n \nIch habe einmal bei anderen Supportern nachgesehen, darunter Nami, Thresh, Morgana, Janna und Bard. Diese haben in der Tat höhere Killbeteiligungen von gut über 50% im Schnitt [teilweise 55% und mehr]. Nur Brand hat mit rd 48% einen ähnlichen Schnitt. Das ist ein bemerkenswerter Unterschied. Wäre richtig interressant den Grund dafür herauszufinden. Sind ja ähnlich in der Anlage die beiden Champs. Und es ist ja in allen Elos identisch, so das es daran nicht liegen kann. Weshalb also?\n\n> du verkaufst auch relativ oft dein Supportitem, damit gebt ihr vision oder vision-deny auf. der vorteil vom supp ist doch dass er vision geben kann und gleichzeitig denien kann.\n\nHm. 4 mal in 24 Matches. Davon 3 verlorene [und das letzte gewonnenen heute]. Die Wahl das Sup-Item zu verkaufen ist in aller Regel die defensive Variante bzw. das \"letzte Mittel\" wenn dem Team offensichtlich eine Schadensquelle fehlt oder ich die Notwendigkeigt gesehen habe zu überleben. Im letzten verlorenen ohne Sup-Item hatte ich dann GA gebaut, da Top und Jungle [am Ende] 4/12 und 4/16 standen und auf Tank gebaut haben. Darius/Udyr haben in den 60 Minuten jeweils keine 20k Schaden gemacht. Udyr ist im 4-Minuten-Rhythmus gestorben. Im Match davor war die Akali Midlane nicht so gut dabei, ist bei 4/16 in 29 Minuten im 2-Minuten-Rhythmus gestorben [inkl. Respawn und auf die Lane laufen war sie nie länger als 1 Minute am Leben] und als Schadensquelle komplett ausgefallen und mit 5/9 ZAC jngl war keine Kompensation in Sicht. Und im Match davor... je nun... der 6/16 Varus als ADC hat in 55 Minuten nur 25k Schaden gemacht. Ich kann Dir nicht mehr sagen ob es an seinem Itembuild gelegen hat. Ich kann mich aber noch gut an seine Idee erinnern das wir (=nur er und ich... also die Zyra ohne W und E gegen eine Nidalee[sic] und Quinn) unsere Gegner im Tribusch überfallen sollen wenn diese nach dem Pull auf die Lane gehen. Er ist in den Minuten 2 und 4 gestorben. Ich glaube er hatte das Match da schon abgehakt. Auf meinen Einwand wollte er nicht hören und er hat später in dieser Qualität weitergespielt. Im letzten Match heute war es u.a. auch um die Base zu verteidigen. Wir hatten alle 3 Inhibs verloren nachdem der TF sich (und mich weil ich ihm helfen wollte - mein Fehler und WW dito) durch das alleinige Farmen auf einer Sidelane ohne jede Vision getötet hatte. Wir hätten evtl. bereits die anrückenden Supervasallen nicht aufhalten können. Das war in Minute 32 [tode] und 33 [Inhibs verloren und Verkauf des SupItems]\n\nDas waren also bewusste Entscheidungen auf Basis dessen das das Team keinen Fight gewinnen bzw. die Base nicht verteidigen kann wenn eine oder zwei Schadensquellen komplett ausfallen.","replies":[{"poster":"ToK Wipern","date":"2018-04-05T08:31:57.301+0000","up_votes":1,"down_votes":0,"body":"> Interessante Betrachtung. Habe gerade nachgesehen. Meine Killbeteiligung bei den letzten 12 Siegen liegt bei 48,5%\n\nZum Zeitpunkt des Erstellens und solo-que betrachtet hattest du in den letzten 7 Wins definitiv KEINE 48% du hattest (30,32,44,41,65,42,43). Es ging auch nicht um den Wert. Es ging um den Wert im Vergleich zum Team. Bei diesen 7 Games hast du in 2 Games die GERINGSTE Beteiligung und in 1 games die 2. niedrigste. Der supp sollte für mich NIEMALS die geringste Beteiligung haben.\n\n> Das waren also bewusste Entscheidungen auf Basis dessen das das Team keinen Fight gewinnen bzw. die Base nicht verteidigen kann wenn eine oder zwei Schadensquellen komplett ausfallen.\n\nDas ist völlig legitim, ich weise halt nur daraufhin, dass du dich beschwerst du müsstest andere rollen wie carry ersetzen als supp. aber einen Punkt der Rolle des Supps, also vision aufbauen UND vernichten, mit dem Build nicht erfüllst.","replies":[]}]}]},{"poster":"CrazyFrogEye","date":"2018-04-04T15:04:48.791+0000","up_votes":1,"down_votes":0,"body":"Ich find es immer schwierig eine bestimmte Spieler-Gruppe so pauschal zu verurteilen. Ich spiele sowohl relativ viel Support als auch ab und an ADC und hab jetzt nicht die Erfahrung gemacht, das Supports immer gut sind und alle ADCs komplette Grütze zusammenspielen. \n\nAls Support bist du gerade in der Laning-Phase eher der jenige der die Plays macht, Pressure aufbaut, Kämpfe eröffnet etc.\nUnd man muss halt auch sagen wenn die Gegner einen gefeedeten Top oder Midlaner haben, bist du als ADC ziemlich gearscht.\nDen auch wenn du behind bist, du bist squishy und in den Köpfen vieler Leute ist ADC immer das Ziel Nummer 1. \nHinten chillen seine Spells raus drücken ist mit ADC auch nicht, wenn du zu passiv ist verliert dein Team den Fight auch, weil der Damage fehlt. \n\nDas Positioning ist teilweise echt tricky, hab etwas Nachsicht mit deinen Carries. Wenn wirklich gar nichts geht kannste als Support halt nochmal etwas weniger machen als in der Top oder Midlane. Ich kenn das Gefühl.\n\nAber wegen einigen schlechten Games alle ADCs pauschal zu verurteilen ist genauso sinnfrei, wie zu sagen alle Silber-Supports sucken. Das hier niemand LCS-Level spielt ist schon klar ihr Intelligenzbestien.\n\n\nWenn du das Problem dauheraft hast ist es vieleicht ratsam sich einen festen ADC zu suchen mit dem du zockst.","replies":[]},{"poster":"Cenâreth","date":"2018-04-03T10:21:31.111+0000","up_votes":1,"down_votes":0,"body":"Naja anders gefragt gibt es noch gute Supporter?\n\nIch hab jetzt mal dass 2/9 Spiel gesehen. Du wunderst dich dass dein ADC schlecht ist intest selbst hinein gegen einen Early strongen Draven?\nUnd der war nicht mal gut, wenn er Aerys dabei gehabt hätte, hätte der euch durchaus oneshotten können mit 4 Kills die er bereits hatte.","replies":[]},{"poster":"H3nt4i K4m3n","date":"2018-04-02T18:31:12.848+0000","up_votes":1,"down_votes":0,"body":"Es ist schwer nur anhand deiner Aussagen etwas zu beurteilen.\nIN deinem letzten Game hast du zum beispiel 1 Ward in den ersten 5 Minuten platziert!!\nAber ich denke es liegt daran, dass du zu passiv deine Lane spielst und nicht genug für deinen Carry Zonest und Pokest. Dein Cs in den Games ist teilweise sehr hoch, d.H du nimmst auch sehr viel Cs weg.\n Nimm doch einfach auch mal Ignite mit, damit du ansonsten besser die Lane carrien kannst.\n\nAnsonsten ist es wie in jedem Game: Du wirst nicht immmer einen Adc Main bekommen, der weiß was er zu tun hat .","replies":[]},{"poster":"Wekra","date":"2018-04-02T18:17:44.746+0000","up_votes":1,"down_votes":0,"body":"TL;DR hier bin ich","replies":[]}]} |
{"title": "President Rajapaksa inaugurates island wide celebrations by launching Tree planting programme", "content": ["Onlanka News \u2013 By Janaka Alahapperuma (Pix by: Sudath Silva) President Mahinda Rajapaksa inaugurated island wide celebrations to mark his second term of office and his birthday this morning on 15 November at Temple Trees. \u2018Deyata Sevana\u2019, a massive tree planting campaign was launched by the President to mark the occasion today at the auspicious\u2026 "], "link": "https://www.onlanka.com/news/president-rajapaksa-inaugurates-island-wide-celebrations-by-launching-tree-planting-programme.html", "date_published": "November 16, 2010", "category": "Local News"} |
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{"forum_title": "Vélartengdir hlutir / Viðgerðir og Viðhald", "id": "12644", "title": "Vandræði með wrx 2005", "url": "http://www.live2cruize.com/spjall/showthread.php/12644-Vandræði-með-wrx-2005", "posts": [{"user_name": "Hrannar", "text": "Sælir, ég er í vandræðum með einn wrx 2005, hann kokar og gengur illa, þegar að það er sett GREEN sía í hann, hver er ástæðan?", "date": "2006-03-21 17:28:00", "post_id": 1}, {"user_name": "MJ", "text": "hvernig gengur hann án síu ? bara alveg opið ??", "date": "2006-03-21 17:31:00", "post_id": 2}, {"user_name": "Hrannar", "text": "Hann er mun skárri svoleiðis", "date": "2006-03-21 17:47:00", "post_id": 3}, {"user_name": "gulligu", "text": "ER hún nokkuð skítug eða ný þrifin og kannski verið sett of mikil olia á hana?", "date": "2006-03-21 18:11:00", "post_id": 4}, {"user_name": "gtturbo", "text": "Er þetta ekki þetta klassíska imprezu vandamál að air flow skynjarinn er orðinn skemmdur (spegillinn inni í skynjaranum er orðinn mattur) það er víst ótrúlega fljótt að gerast á sumum bílum. Þetta var allavegana mjög algengt í eldri bílunum GT að það þyrfti að skipta um þennan skynjara eftir að búið var að setja \"kraftsíu\" í bílinn.", "date": "2006-03-21 18:14:00", "post_id": 5}, {"user_name": "Andri STi", "text": "athugaði olíuna á vél ...ef hún er of mikil þá fer olía uppí loft skynjarann og veldur hikksti allavega", "date": "2006-03-21 18:24:00", "post_id": 6}, {"user_name": "MJ", "text": "ja vinur minn er með þetta vandamál á sýnum GT bíl, eg skal spurja hvað er að :wink:", "date": "2006-03-21 19:14:00", "post_id": 7}, {"user_name": "Bjaddni", "text": "prófaðu að aftengja rafgeimin í 5-10 mín og lofaðu tölvuni að endursetja sig", "date": "2006-03-21 19:24:00", "post_id": 8}, {"user_name": "MJ", "text": "að gera þetta virkaði ekki á minn!", "date": "2006-03-21 19:26:00", "post_id": 9}, {"user_name": "olinn", "text": "Er að lenda í smá böggi með minn GT líka .. ef ég botnstíg hann í t.d 2/3/4/5 og hann fer alla leið í max standard boost, eða e-ð sirka 10-12 psi, en droppar svo í 7-8, fer svo aftur upp og aftur niður.\n\r\nHringdi í Friðrik óla og lenti á fínasta gaur sem sagði þrennt;\r\n1. Kertin léleg\r\n2. Loftflæðiskynjari ónýtur (er einmitt með svepp)\r\n3. Olíubögg e-ð", "date": "2006-03-30 01:08:00", "post_id": 10}, {"user_name": "GretarK", "text": "Alltaf þegar maður hefur heyrt um svona þá er það loftflæðiskynjarinn sem að hefur verið með vesen.. einmitt útaf svepp eða álíka síu.", "date": "2006-03-31 12:29:00", "post_id": 11}, {"user_name": "Birgir Örn", "text": "Lenti í þessu eg skal segja þér hvað er að þu hefur sett of mikla oliu á bílinn.", "date": "2006-03-31 19:17:00", "post_id": 12}, {"user_name": "MJ", "text": "bara setja orignal síu box í bilinn og passa setja ekki ofmikla olíu á hana", "date": "2006-03-31 22:19:00", "post_id": 13}], "file_urls": [], "date": "2006-03-21 17:28:00", "files": []} |
{"poster":"SpielTuch","date":"2016-04-27T17:35:59.636+0000","title":"10 häufige Fehler die wir alle machen und wie man sie vermeidet","subforum":"Level Up: Guides & Tipps","up_votes":26,"down_votes":2,"body":"Hallo zusammen,\n\nich möchte euch hier 10 häufige und typische Fehler aufzeigen, die wir bestimmt alle machen. Natürlich zeige ich euch auch noch Möglichkeiten, wie er diese beseitigen könnt.\n\n1 Overstaying nach dem Teamfights\n\nDas passiert meistens nach einem erfolgreichen Teamfight. Nachdem man alle Gegner oder einen Großteil getötet hat wird meistens für Tower gepusht. Nach dem ersten Tower kann dann auch schon der zweite Tower folgen – Problem: Du oder dein Team hat wenig HP oder aber ein Teil des Teams pusht gar nicht mehr mit euch, sondern hat sich vielleicht schon zurück geportet. Das Gegner Team respawnt und bestraft euch dafür, dass ihr zu lange gepusht habt. Solche Dinge passieren meistens im late game und wir daher nicht nur mit dem Gold für das Gegner Team bestraft, sondern auch mit langen Todeszeiten, woraus in schlimmsten Fall eine Niederlage draus resultieren könnte.\n\nSo löst du das Problem: Habe ein genaues Auge auf die Gegner, die noch leben und auf die Todeszeiten der Gegner. Lieber den gegnerischen Turm am leben lassen und dafür deren Jungle nehmen und ggf. eine Drachen und dann ab ab nach Hause.\n\n2 Overstaying in der lane\n\nÄhnliche Problematik wie beim ersten Fall, nur dass es jetzt während der Laningphase ist. Folgendes Szenario: Du tötest deinen Gegner und überlebst nur knapp. Du möchtest aber noch die lane pushen, um einen noch größeren Vorteil zu haben. Doch plötzlich kommt der gegenerische Jungler oder ein anderer Gegner nutzt TP und tötet dich. Und damit kann der gerade erspielte Vorteil auch schnell wieder weg sein.\n\nSo löst du das Problem: Pushe die lane nur zum gegnerischen Turm, wenn du dir absolut sicher bist, dass dein Lane-Gegner nicht rechtzeitig zurück kommt und du weißt wo sich die restlichen Gegner auftreiben. Ansonsten kannst du 2-3 CS nehmen die wenig HP haben und dann zurück zur Homestation gehen.\n\n3 Am falschen Ort oder zur falschen Zeit zurück teleportieren\n\nWir kennen sie alle. Champions mit globalen Fähigkeiten (bzw. Fähigkeiten mit einer großen Reichweite). Draven, Lux, Jinx, Ezreal, … Diese Champions bekommen häufig Kills weil Du vielleicht nach einem Kill sofort die Backport-Taste betätigst (in Vision des Gegners, z. B. bei Minions). Ein weiteres Problem ist, dass du schon im Shop bist bevor du überhaupt in der Base bist.\n\nSo löst du das Problem: Suche dir einen sicheren Platz um die in die Base zu porten (z. B. hinter den eigenen Turm) und teleportiere dich nicht nach Hause, wenn ihr einen Teamfight gewonnen habt und keiner der Gegner überleben konnte. Es gibt niemand, der dich töten kann. Also pushe die Lane, nimm Objektive oder den gegnerischen Jungle. Beachte aber immer die Todeszeiten! :-) (siehe Fehler 1)\n\n4 Kills traden\n\nIch weiß, 15 Kills zu haben sieht schon geil aus. Gerade wenn man Assassine wie Talon, Zed oder LeBlanc spielt. Doch nicht, wenn man dafür 12x gestorben ist. Diese 12 Kills bringen den Gegner eine Menge Gold! Ich habe lieber in meinem Team einen 2-2-2 Teemo als einen 15-12 Talon, weil Teemo seine Zeit nicht damit verschwendet Tod zu sein und nichts zu tun. Er pusht nämlich anstelle dessen die Lane.\n\nSo löst du das Problem: Natürlich solltest du versuchen deinen Vorteil möglichst zu maximieren, aber nicht auf Kosten von Killtrades. Versuche lieber durch agressives spielen dein CS-Lead zu erweitern. Denn 15-20 CS haben einen Goldwert von einem Kill!\n\n5 Andere für deine Fehler blamen\n\nHast du einen All-In Champ wie Leona und denkst: Yes! Jetzt gehe kann ich rein gehen mit einer 5-Mann Ulti! Doch dann stirbst du relativ schnell um bemerkst, dass keiner deiner Kollegen gefolgt ist. Jetzt ist es natürlich logisch, dass es deren Fehler war und die geblamt werden müssen.\n\nSo löst du das Problem: Wenn du dich auf einen engage vorbereitest, signalisiere dies deinem Team indem du öfters pingst. Du solltest ebenfalls auf das Mana, Leben und auch auf die Abklingzeiten (mind. bei den Ultis) achten. Denn wenn ein Magier kein Mana hat, kann er noch so wenig bei einem tollen engage tun.\n\n6 Besserwisser über einen anderen Champion\n\nMir ist keine bessere Überschrift eingefallen, Verzeihung. Was ich aber meine beginnt hier schon im Champion Select. Bestimmt hast du schon mal geschrieben (auf Englisch wahrscheinlich) „Hmm.. spiele nicht den Champion XYZ. Ist doch ein Troll Pick…“ oder „Wir brauchen wirklich einen Tank wie XYZ, pick nicht ZYX!“ Oder auch während des Spieles den Teamkollegen sagen was er zu kaufen hat oder wie er eine Kombo zu nutzen hat.\n\nSo löst du das Problem: Sei taktvoll und höflich und frage in Champ Select z. B. ob sie nicht den Champion XYZ spielen könnten. Oder sage in game Sachen wie: „Ich habe noch nie diesen Build auf den Champion XYZ genutzt. Ist es wirklich so gut?“ oder „Ich maximiere gerne die Fähigkeit Q als erstes.“ Versuche hier eher einen Ich-Bezug zu erstellen, anstatt es so klingen zu lassen, dass du den anderen etwas vorschreiben willst.\n\n7 Warding zu vergessen\n\nIch weiß, dass weiß eigentlich jeder. Aber es ist eigentlich egal in welcher Elo, ich sehe es immer wieder, dass die Leute nicht warden. Dabei wird es und von den Items und Trinkets so einfach gemacht. In den Spielstatistiken kann man dann auch immer sehen, dass viele Spieler kein Pink Ward gekauft haben (oder max. ein) und auch generell das Trinket kaum genutzt haben.\n\nSo löst du das Problem: Normalerweise sollten auf der Map 5 Pink Wards von deinem Team sein, außer es wurde gerade einer zerstört oder ihr habt euern Fullbuild. Lasse immer einen Slot für einen Pink Ward frei und kaufen auch einen (einen Slot frei lassen alleine bring auch nichts ;-)). Upgrade dein Trinket sobald du Level 9 und in der Base bist! Supporter sollten meistens das rote Trinket verbessern, für Splitpusher eignet sich das blaue sehr gut.\n\n8 Deine Power überschätzen\n\nDies gilt für deinen persönlichen Skill und dein Damage Output in game. Folgendes Beispiel: Ein gefeedeter Master Yi macht schon Angst, keine Frage! Während du also mit Yi z. B. 10-1 stehst, dein ADC aber 2-5, dein Toplaner 1-4 und deine Mitte vielleicht 0-1, dann herrscht eine schlechte Balance in deinem Team, denn der Rest deines Teams ist nicht annähernd so stark wie du. Du kannst vielleicht einen 1v2 oder 1v3 fight gewinnen, aber auch nur solange, bis du es nicht mehr kannst. Denn irgendwann sind die Gegner zu zweit stärker als du alleine oder sie haben einen Plan, wie sie dich outplayen können. Und so gehen viele Spiele verloren. Weil man alleine sehr stark ist und dann stirbt, kann das restliche Team von dir auch nicht mehr machen.\n\nSo löst du das Problem: Spiele Intelligent. Bitte was? Wenn du so egoistisch bist und die Kills und den damit verbundenen Gold nicht teilen möchtest, dann nutzte deinen Vorteil zumindest effizienter. Sterbe einfach nicht. Sorge für tiefe Vision in der gegnerischen Hälfte, …\n\n9 Mangelnde Beteiligung\n\nDu spielst z. B. Caitlyn bot und alles was du tust ist zu farmen. Klar, einen guten Farm zu haben ist gut, bringt Gold und vielleicht hast du sogar einen Farmlead von 40+ gegenüber deinen Gegner. Und sobald ein Teamfight in der Mitte ausbricht, marschierst du auch schön dahin. Doch meistens zu spät. Der Teamfight ging verloren und du begibst dich wieder auf der Bot Lane um weiter zu farmen. Doch mit der Zeit bemerkst du, dass dein Team immer häufiger verliert, bis der Rückstand zu groß ist und das Spiel verloren geht. Vielleicht stehst du ja am Ende 4-1-2 mit über 300 CS, aber am Spiel hast du dich nicht wirklich beteiligt.\n\nSo löst du das Problem: Sei da sobald du gebraucht wirst. Das gilt auch für einen Garen oder Nasus mit TP! Nutzte dein Teleport um dich an Fights zu beteiligen anstatt damit immer wieder zur Lane zu kommen. Nutzte auch deinen Feed an Minions, denn wie schon oben gelernt: 15-20 CS = 1 Kill. Nutzte also den indirekten Killvorteil und hilf dein Team.\n\n10 Facechecking \n\nJetzt gehe mal tief in dich herein und denke darüber nach, wie oft du ohne Vision in einem Busch gegangen bist um dort z. B. eine gefeedete Irelia oder das gegnerische Team zu treffen. Du wirst innerhalb von wenigen Millisekunden getötet. Oder du verfolgst einen fast sicheren Kill in den Busch rein, obwohl sich kein anderer Gegner auf der Minimap blicken lässt? Gefährlich…\n\nSo löst du das Problem: Habe einen Überblick darüber, wo sich deine Gegner aufhalten. Weißt du es nicht, könnten sie möglicherweise ganz in deiner Nähe sein. Du kannst auch mit dem blauen Trinket Vision in den Busch bekommen, in dem dein Gegner gerade rein geht. Und sollte dich dein ganzes Team mit „Vorsichtig“-Pings an spamen, dann wird das wohl für einen guten Grund so sein.\n\n\n\nSo, ich denke wir können uns hier alle sehr gut wieder finden. Versuche also diese 10 kleinen Fehler zu vermeiden und sobald du dies unbewusst hin bekommst, bist du schon ein ganzes Stück weiter und besser geworden! Auf diese erworbenen Fähigkeiten kann man dann auch weiter aufbauen mit neuen Fertigkeiten (Dragon/Baron Kontrolle, Shot-Calling, …)\nIch hoffe ich konnte euch ein wenig helfen. :-)\n\nLieben Gruß\nSpielTuch\n\n\nEdit 1: Nun.. Mit einer solch \"großen\" Resonanz habe ich nicht gerechnet, da macht die reingesteckte Mühe doch gleich viel mehr Spaß! Gerne werde ich in Zukunft noch einige anderen Guide schreiben, um euch damit zu helfen. Ihr könnt mich bei Fragen auch gerne ingame adden. \"SpielTuch\"\nDanke auch an alle, die einige meiner Tipps verbessert oder Ergänzungen gemacht haben! :-)","replies":[{"poster":"Killerkante","date":"2016-04-27T18:34:47.584+0000","up_votes":3,"down_votes":2,"body":"Ich denke ein Großteil der Community weiß schon selbst die Antwort auf die meisten Dinge, die Kunst darin besteht allerdings das in der \"Hitze des Gefechts\" nicht zu vergessen.","replies":[{"poster":"Sophie973","date":"2016-04-28T05:55:23.951+0000","up_votes":1,"down_votes":5,"body":"Zumal Punkt 7 nicht wirklich sein sollte permanent 5 Pinkwards zu haben auf der map, sondern 3 Pink wards die effizient sind. Zb nicht 2 Pinkwards auf der Toplane weil man dies einfach nicht braucht lieber einen weniger und dafür mehr gold für items.","replies":[{"poster":"Uranbrennstab","date":"2016-04-28T07:39:28.445+0000","up_votes":2,"down_votes":0,"body":"> [{quoted}](name=fanum85,realm=EUW,application-id=vatevpvi,discussion-id=dggtgOph,comment-id=00000000,timestamp=2016-04-28T05:55:23.951+0000)\n>\n> Zumal Punkt 7 nicht wirklich sein sollte permanent 5 Pinkwards zu haben auf der map, sondern 3 Pink wards die effizient sind. Zb nicht 2 Pinkwards auf der Toplane weil man dies einfach nicht braucht lieber einen weniger und dafür mehr gold für items.\n\nWeil die 75 Gold auch so wichtig sind.\nIch denke mal jeder weiß, das du nicht 2 Pinks in den selben Busch setzen musst.","replies":[{"poster":"SpielTuch","date":"2016-04-28T13:08:46.632+0000","up_votes":4,"down_votes":0,"body":"> [{quoted}](name=Uranbrennstab,realm=EUW,application-id=vatevpvi,discussion-id=dggtgOph,comment-id=000000000000,timestamp=2016-04-28T07:39:28.445+0000)\n>\n>> Ich denke mal jeder weiß, das du nicht 2 Pinks in den selben Busch setzen musst.\n\n\n:D:D:D Da kam mir doch ein kleiner Lacher hoch. :')","replies":[]}]},{"poster":"DargPhoenix","date":"2016-04-28T08:16:12.601+0000","up_votes":1,"down_votes":0,"body":"> [{quoted}](name=fanum85,realm=EUW,application-id=vatevpvi,discussion-id=dggtgOph,comment-id=00000000,timestamp=2016-04-28T05:55:23.951+0000)\n>\n> Zumal Punkt 7 nicht wirklich sein sollte permanent 5 Pinkwards zu haben auf der map, sondern 3 Pink wards die effizient sind. Zb nicht 2 Pinkwards auf der Toplane weil man dies einfach nicht braucht lieber einen weniger und dafür mehr gold für items.\n\n\nEr will damit einfach nur andeuten, dass viel zu wenig Pinkwards gekauft werden. Sei es für Vision oder Counterplay gegen Akali/Vayne/...","replies":[]}]}]},{"poster":"sN00Bdogg","date":"2016-04-28T12:28:47.806+0000","up_votes":3,"down_votes":1,"body":"Ebenfalls ein Upvote von mir. \n\nIch erlaube mir aber ein paar Ergänzungen:\n\n1+2) Overstaying\nOft führt der Greed dazu , daß aus einem gewonnenen Teamfight ein Unentschieden wird!\nMan muss auch damit zufrieden sein, dass man einen oder zwei Kills bekommen hat (z.B. für nichts) und den TF beenden. Ich sehe es so oft, daß Spieler beim Stand von 2-0 in diesem TF glauben, sie könnten noch den \"einen\" Low-Life-Gegner rausnehmen, weil man ja jetzt 5vs3 ist ... und dann sterben sie. Selbst wenn sie den Kill noch bekommen, hat der Gegner ebenfalls noch was schnappen können. Oft springt der Supporter aus reinem Helfer-Reflex heraus hinterher und stirbt auch noch und wenns ganz dumm läuft kommt sogar noch ein Re-Engage des Gegners und schwuppdiwupp wurde aus einem 2-0 ein 3-3-Abtausch.\nDas gilt genauso in der Lane, wenn man den einen Kill schon sicher hat, dann aber noch den zweiten will und dafür nen Tower-Dive riskiert.\n\nUnd was Türme und sonstige Objects betrifft, gehe ich generell nach dem Motto vor:\n**Make an Object und GO !**\nOft wird dann versucht \"noch schnell\" die paar Minions abzufarmen und das kostet dann das Leben.\nDenn bedenke:\nIn dem Moment, wo du anfängst den Tower zu machen, sehen Dich alle und laufen los in deine Richtung, Wenn Du dann den Tower geschafft haben solltest, sind sie schon sehr nah !!!\nAlso pfeif auf die paar Minions !!!!\n\n3) Ja sehr oft kann eine Lux oder Ashe noch aus der Base heraus den Kill machen, weil man die Backport-Position des Low-Life Gegners kennt. Manchmal stehen die nämlich direkt auf einem Ward oder einfach iim nächstgelegenen Busch.\n\n4) Kills traden bzw. 1-1 abtauschen\nViele tun dies und denken \"Naja ist ja nicht wirklich was passiert und ich kann mir wenigstens ein Item kaufen, was mich stark macht\". Sie vergessen dabei, daß der Gegner davon ebenfalls stark wird. Und wenn beide Midlaner z.B. 6/6 stehen sind sie beide sich immer noch Pari, aber was passiert wenn dieser Midlaner zum Roamen geht und auf ne Top oder Bot ohne Kills trifft?\nEasy Kills sind die Folge und meist kommt dann noch vom Midlaner ein \"Report my team\" hinterher, weil er nicht begreift was er selbst da angerichtet hat!\n\n**Mein Tipp: \nVersuche so zu spielen , daß du zumindest die ersten 15 Minuten nicht stirbst bzw wähle nur Champs mit denen du dies auch erreichen kannst!\n**\nAufgrund des besseren Farms und des \"Nicht-feeden\" des Gegners bist du inm Verhältnis stärker!\n\n5) siehe 11)\n\n6) Niemals anderen vorschreiben was sie picken sollen!\nKlar kann man fragen ob der Toplaner oder Supp nicht auch einen \"guten\" Tank hat, aber ich habe oft erlebt , daß im CS steht \"Pick XY he is OP\"\nWas passiert? \nDer Top-Laner denkt \"Naja, den wollte ich ja schon immer mal spielen und wenn das Team es so will ....\" \nResultat: Unskilled Moves und verlorene Lane!\n\n**Also immer das Picken, was man beherrscht!**\n\nCounter hin oder her: In der Low Elo sind Lane-Duelle meistens Skill-Duelle\n\n7) Warding\nPink wards kann man im eigenen Dschungel sehr gut an Stellen setzen, wo sie 20 Min und mehr unentdeckt bleiben.\nWenn man sie natürlich an Stellen einsetzt , die hohen Traffic haben (z.B. Drake oder die Wasser-Büsche), wo sowieso immer per Trinket gewarded wird, dann hat man zwar eine sehr gute Vision, aber nur für kurze Zeit. Dadurch sagen sich viele: \"Ich hab 75g verloren und der Gegner noch 30 bekommen!\" und kaufen \"nie\" mehr Pink wards.\nWenn man allerdings den eigenen Blue + Red warded kann man den Gegner-Jungler beim Counterjunglen easy abfarmen. Dann hat man 75g investiert und hat dafür 300Gold plus evtl. 1-2 Assists abgegriffen. Und obendrein den Buff behalten ! Und meist bleibt der Ward weiterhin stehen, weil unentdeckt ;)\n\nAnsonsten sieht man oft die Kollegen mit vollem Trinket sterben, weil sie einfach nicht daran denken einen Ward fallen zu lassen, wenn sie irgendwo an markanten Stellen vorbei laufen (zB Drake etc)\n\n8) Power überschätzen\nTja. Das passiert eben, denn man will ja auch mal drauf gehen und traden. Gehört dazu. Nach einigen Spielen mit seinem Lieblingschamp kann man dies ungefähr einschätzen. Trotzdem verlliert man immer wieder Trades, weil der Gegner eben auch seine Tricks drauf hat. \n\nWichtig hierbei ist, daß man realisiert, was passiert ist. Nämlich: Bis eben war man sich in etwa ebenbürtig , aber jetzt hat der Gegner ein Item mehr und ist mir überlegen. Wer jetzt meint er könne den nächsten Trade gewinnen, ist meistens der Idiot, der dem Gegner den nächsten Kill (sprich das nächste Item) spendiert.\n\n**Fazit: Lerne den Schalter umzulegen, wenn Deine ersten 1-2 Offensiv-Aktionen in die Hose gehen!**\nStelle deine Taktik um, auch wenn defensives Farm-Play-under-Turret nicht so viel Spass macht ! \n\nGanz schlimm sind die Jungler, die dies nicht beherzigen können und trotz vermasselter Ganks und fehlenden Levels trotzdem so weiter spielen und weitere Tode auf den Lanes sterben.\n\n9) Mangelnde Beteiligung\nNatürlich sollst du deinem Team helfen! \nAber Du musst auch einschätzen können, wo du in ein paar Sekunden gebraucht werden könntest! (Das geht mit guter Vison einfacher und mit der Zeit entwickelt man auch ein Gespür dafür)\nUnd Du musst auch nicht blindlings allem hinterher rennen. Wenn Du als ADC siehst \"Ooops! In der Midlane wird gegankt\" dann ist es in der Regel schon zu spät, um noch hinzurennen. \nResultat: \nDu kommst an, wenn deine Mates bereits tot sind bzw der Fight vorbei, hast in der Zeit einiges an Bot-Lane Farm verloren und wenns dumm läuft stirbst du auch noch.\nGeauso muss man als ADC auch nicht jedesmal nen Fight beginnen, nur weil der Supp endlich mal nen Stun getroffen hat! \nViele Supporter flamen dich bei \"Passivität bzw Weiterfarmen\"danach, aber wenn man jedesmal bei einem Treffer gleich rein rennt, bekommt man oft von den Minions genauso viel Damage wie man dem Gegner ADC geben kann und somit ists wieder ein Risk-for-nothing.\n\nTip fpr den ADC: Manchmal einfach stur weiter farmen!\nTip für den Supp: Nicht immer alles Mana verschwenden, um vielleicht mal den EINEN Stun zu setzen, so daß man immer noch was übrig hat, wenn zB ein Gank kommt. Man kann den Gegner-ADC auch ohne grossen Mana-Verbrauch bei dessen Farming stören und so dem eigenen ADC nen Farmvorteil ermöglichen.\n\n10) Facechecking\nGehört zum grossen Thema Vision/Warding und Map Awareness. \nWenn man immer mal auf die Minimap schaut (manche empfehlen alle 5 Sekunden !!!!!), dann weiss man ungefähr, wo der Gegner Jungler ist. Und wenn ich als Supp sehe \"Ah der Gegner Jungler hat gerade die Top gegankt\", dann ist dies der Moment, wo ich mit meinem Taric zum Gegner Blue/Red laufe, um dort nen Ward zu setzen. Denn genau dort wird der Jungler hingehen, wenn er gerade auf der Top war und danach zum Shopping in der Base war \n\n11) Pingen\nVorweg: Viel Pingen heisst nicht spammen!!!!\nBedenke, daß du mit jedem Ping die Konzentration deiner Mitspieler störst, weil diese erstmal wieder auf die Minimap schauen, um zu sehen was da los ist!\nUnd wenn EIN Ping scheinbar keine Wirkung zeigt, nutzen auch 5 hintereinander meistens nichts! Bedenke, daß der Mitspieler selbst wenn er den Ping sieht, erstmal 2-3 Sekunden braucht, um zu entscheiden, was zu tun wäre bzw welche Möglichkeiten er hat, um etwas zu tun. Evtl. will er seinen Cooldown abwarten etc.\n\nDeswegen zeige immer an , wenn Du zum Roamen oder ganken irgendwo hingehst. Dann kann der Laner schon mal Mana sparen, den Cooldown abwarten UND den Gegner baiten (= in die Falle locken)! Wenn Du dann ankommst stehen ihm wenigstens alle Möglichkeiten zur Verfügung Dir auch zu helfen und es wird vielleicht eine erfolgreiche Aktion.\n\nWas ich oft erlebe ist, daß der Jungler aus der eigenen Base schon \"Komme Top\" pingt, dann aber unterwegs doch noch auf die Mid abbiegt o.ä. Das ist meist sehr ärgerlich für den Top-Laner, der seine \"lane-Pläne\" extra wegen dem Gank umgeschmissen hat.\nEbenso gibt es Jungler/Roamer, die es nicht schaffen mal 5 Sekunden im Busch stehen zu bleiben, um den richtigen Moment abzuwarten. Das sollte man auf jeden Fall tun, denn in dieser Zeit gilt es nach zu sehen:\n- wieviel HP+Mana haben die Spieler \n- wie ist die allgemeine Situation?\n- stehe ich vielleicht auf einem Ward und bin schon längst gesehen worden?\n- wieviel HP/Mana habe ich selbst? Hab ich noch Flash?\n- Ebenso ist es von Vorteil den Gegner zu markieren, den man in den Focus nehmen will.\n\nViele Jungler kommen auf die Lane und rennen direkt durch und wundern sich danach, daß der Lane-Eigner so schlecht geholfen hat!\n\n**Bedenke: Die Tugend des Jägers ist die Geduld!**\n\n12) Objectives nicht überschätzen\n\nSicherlich macht es in der LCS einen großen Unterschied, ob man mehr Türme hat als der Gegner! Die Jungs wissen genau, wie sie dieses Gold etc für ihr Team richtig einsetzen.\n\nAber für uns Normalsterbliche in der Low-ELO?\nWie oft wird dieses Gold ins \"falsche\" Item investiert?\nWieviel Farm hast Du verloren in der Zeit als du tot warst?\nWieviele Kills haben die Gegner in Deiner Todeszeit gemacht, weil sie in der Überzahl waren?\n\nDeswegen ist es meiner Meinung nach **NIEMALS \"WORTH\"** für einen Tower zu sterben oder für einen der ersten 4 Drakes. Denn den Tower und somit das Gold wird man irgendwann ja doch bekommen, also warum dafür dem Gegner einen Kill (incl. Assist) schenken?\n\nBei Inhibitoren mag es manchmal WORTH sein, aber bei den meisten Situationen hätte man den Inhib etwas später auch ohne Tod haben können, wenn man geschickter vorgegangen wäre!\n\nOhje! Hab wieder mal erst beim reinkopieren gemerkt, wie lang dieser Post wieder wurde ^^\n\nAber vielleicht könnt Ihr damit ja was anfangen ;)","replies":[{"poster":"SpielTuch","date":"2016-04-28T13:09:59.194+0000","up_votes":1,"down_votes":0,"body":"Mensch, vielen Dank für deinen Input als Ergänzung! :-)\nVieles hat sich zwar gedoppelt, aber vieles waren auch super Ergänzungen, gerade in der Tiefe. :-)","replies":[]}]},{"poster":"SKT T1 1ND3R","date":"2016-04-28T12:08:22.675+0000","up_votes":2,"down_votes":1,"body":"***","replies":[{"poster":"G13 Smoke","date":"2016-04-30T14:29:23.648+0000","up_votes":2,"down_votes":1,"body":"Du vergisst, das Champions in verschiedenen Phasen des Spiels unterschiedlich stark sind. Und dein gefeedeter Talon bringt letzendlich auch nichts mehr, wenn der gegner Adc überlebt und auch fed is. Das vergessen sehr viele in diesem Spiel, dadurch wird auch oft zu früh aufgegeben. eine 3 6 Vayne ist nach min 40 einfach stärker als ein 6 3 Lucian (sollten beide Teams eine stabile frontline haben).","replies":[{"poster":"SKT T1 1ND3R","date":"2016-04-30T14:37:14.799+0000","up_votes":1,"down_votes":0,"body":"***","replies":[{"poster":"G13 Smoke","date":"2016-04-30T15:10:56.539+0000","up_votes":1,"down_votes":1,"body":"Du kannst in diesem Spiel nicht das eine vom anderen abgrenzen. Ignorierst du das Scaling und setzt kill+ assist über einen kill wirst du keinen spaß mehr mit sivir gegen kog maw oder mit zed gegen lux haben. Darum geht es in diesem Punkt, auch wenn es nicht bis in diese Tiefe beschreiben worden ist.\nSorry für die Rechtschreibfehler, ich habs eilig...","replies":[]}]}]}]},{"poster":"Seieiryuu","date":"2016-12-04T22:39:42.571+0000","up_votes":1,"down_votes":0,"body":"Schade, dass der Beitrag nur so wenig Upvotes hat, auch wenn vieles klar ist, besser wennman es nochmal verinnerlicht{{sticker:slayer-pantheon-thumbs}}","replies":[]},{"poster":"Kata Ga Kill","date":"2016-04-29T16:26:12.862+0000","up_votes":1,"down_votes":0,"body":"Einfach super der Guide!\nSchön erklärt und richtig effektiv hoch 10.\n\nWeiter so^^","replies":[]},{"poster":"EsgibtKuchen","date":"2016-04-29T16:24:06.655+0000","up_votes":1,"down_votes":0,"body":"Sehr schöner Post :) {{sticker:slayer-pantheon-thumbs}}","replies":[]},{"poster":"Jinpaxchi","date":"2016-04-28T17:39:39.153+0000","up_votes":1,"down_votes":0,"body":"Du sprichst aktives Chatverhalten in Punkt 5 und 6 an.\n\nAber wie soll man sich verhalten wenn das geflame los geht?\n\nOder besser gleich Muten wenn man das Gefühl hat das es gleich los geht?","replies":[{"poster":"SpielTuch","date":"2016-04-28T19:35:06.894+0000","up_votes":1,"down_votes":0,"body":"Ich erzähle Dir mal wie ich es mache:\nIch habe die Chat Skalierung auf 25 gesetzt und das Fenster zwischen den Fähigkeiten und der Minimap gesetzt. Jedesmal, wenn ich relevante Informationen brauche oder welche erwarte (z. B. bin ich Jungler und sehe, dass auf der Top Lane gefightet wird. Der Gegner nutzt flash und dies wird im Chat vermerkt.) dann schaue ich mir den Chat an. Einen größeren Überblick gibt es übrigens mit der \"Y\" Taste.\nFalls ich aber momentan keine Informationen brauche beachte ich den Chat überhaupt nicht. Ich kriege es aufgrund der recht kleinen Größe nicht einmal mit wenn jemand etwas schreibt (außer ich schaue zufälligerweise dahin). Ich bekomme somit auch nicht mit, wenn jemand flamt oder ich geflamt werde. Sollte ich geflamt werden ist mir das meistens relativ egal, ich schaue, ob ich etwas konstruktives aus seinem flame raus ziehen kann, wenn nicht, reflektiere ich meistens selbst schon die Situation und weiß, was ich falsch gemacht habe.\n\nAlso kurz zusammen gefasst: Chat vielleicht etwas kleiner stellen, sodass die Flamer nicht beachtet werden. Sollte es einer aber maßlos übertreiben mute auch ich diese. Allerdings ist mal ein flame für mich kein Grund jemanden zu muten, da ich ja somit keine Infos von ihn erhalten kann.\n\nIch hoffe, ich konnte Dir helfen? :-)\n\nLieben Gruß","replies":[]}]},{"poster":"Dr Ogre","date":"2016-04-28T12:19:45.001+0000","up_votes":1,"down_votes":0,"body":"FInde ich sehr gut, diese Zusammenfassung. Wenn man in der Lage ist seinen Champ zu beherrschen und diese 10 Punkte einhalten kann, dann sollte man mit Bronze und Silber eigentlich nichts zu tun haben.","replies":[]},{"poster":"FPG LightYagami","date":"2016-04-28T09:08:14.067+0000","up_votes":1,"down_votes":0,"body":"Für Anfänger ein lehrreicher Thread mit vielen tollen Tipps! ;)\n\nMfG TDFighter","replies":[]}]} |
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[
"DataRaptor/xOM Numeracion Movil Update number inventory Request",
"ManualQueue/Inbox Comun",
"OrchestrationPlanDefinition/NUMERACIÓN MÓVIL - Modify Numeracion Movil Orch Plan",
"System/Numeracion Movil"
] |
{"code":"1118062015","province_code":"11","regency_code":"1118","district_code":"111806","name":"MUSA TEUNGOH"} |
{
"name": "users-list",
"version": "1.0.0",
"private": true,
"description": "Users list app",
"main": "index.js",
"scripts": {
"build": "next build && next export",
"checks": "prettier --check . && npm run lint && npm run types",
"dev": "next dev",
"lint": "eslint src",
"serve": "serve out",
"start": "next start",
"test": "jest",
"types": "tsc --noEmit"
},
"dependencies": {
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"@types/node": "^14.14.10",
"@types/react": "^17.0.0",
"@typescript-eslint/eslint-plugin": "^4.8.2",
"@typescript-eslint/parser": "^4.8.2",
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{"content": "The 21.5 million current and former federal employees impacted by the massive data breach in 2015 may never know if they will be targeted based on the information stolen from the Office of Personnel Management. Bill Evanina, the director of the National Counterintelligence and Security Center and the National Counterintelligence Executive, said the rate of attacks and the amount of information out there from public and private sector breaches, means hackers likely will bring together a host of data to use in spear phishing attacks. \u201cIf a foreign entity is using the data stolen from OPM, they will use it as one variable in a big matrix of targeting,\u201d Evanina said on Ask the CIO. \u201cIt\u2019s really not going to be reality to say if Bill Evanina is targeted a year from now by a foreign government, I\u2019m never going to be able to say it\u2019s because of the OPM data breach. It\u2019s one set of data that is being used against those who would be targeted. We really haven\u2019t seen any anecdotal evidence about anything and at the end of the day I don\u2019t think we will. If it was stolen for the reason which we believe it was, you\u2019ll never be able to point to the fact it was the OPM data breach\u201d. Evanina said federal employees should understand the difference between targeting. If they are getting phone calls at home, that likely isn\u2019t a foreign adversary targeting them.", "sourcefile": "684.txt", "cyberevent": {"hopper": [{"index": 0, "relation": "Same", "events": [{"index": "E1", "type": "Attack", "realis": "Actual", "nugget": {"startOffset": 79, "index": "T1", "endOffset": 90, "text": "data breach"}, "argument": [{"index": "T4", "text": "21.5 million", "endOffset": 17, "role": {"type": "Number-of-Victim"}, "startOffset": 5, "type": "Number"}, {"index": "T2", "text": "2015", "endOffset": 98, "role": {"type": "Time"}, "startOffset": 94, "type": "Time"}, {"index": "T3", "text": "federal employees", "endOffset": 54, "role": {"type": "Victim"}, "startOffset": 37, "type": "Person"}], "subtype": "Databreach"}, {"index": "E2", "type": "Attack", "realis": "Actual", "nugget": {"startOffset": 148, "index": "T5", "endOffset": 170, "text": "the information stolen"}, "argument": [{"index": "T6", "text": "the Office of Personnel Management", "endOffset": 210, "role": {"type": "Victim"}, "startOffset": 176, "type": "Organization"}], "subtype": "Databreach"}]}, {"index": 1, "relation": "Same", "events": [{"index": "E8", "type": "Attack", "realis": "Generic", "nugget": {"startOffset": 1065, "index": "T18", "endOffset": 1075, "text": "was stolen"}, "argument": [{"index": "T19", "text": "it", "endOffset": 1064, "role": {"type": "Compromised-Data"}, "startOffset": 1062, "type": "Data"}], "subtype": "Databreach"}, {"index": "E7", "type": "Attack", "realis": "Generic", "nugget": {"startOffset": 1173, "index": "T17", "endOffset": 1184, "text": "data breach"}, "argument": [{"index": "T20", "external_reference": {"dbpediaURI": "http://dbpedia.org/resource/United_States_Office_of_Personnel_Management", "wikidataid": "Q7890847"}, "endOffset": 1172, "role": {"type": "Victim"}, "text": "OPM", "startOffset": 1169, "type": "Organization"}], "subtype": "Databreach"}]}, {"index": 2, "events": [{"nugget": {"startOffset": 515, "index": "T7", "endOffset": 537, "text": "spear phishing attacks"}, "index": "E9", "type": "Attack", "subtype": "Phishing", "realis": "Generic"}]}, {"index": 3, "events": [{"index": "E6", "type": "Attack", "realis": "Generic", "nugget": {"startOffset": 859, "index": "T16", "endOffset": 870, "text": "data breach"}, "argument": [{"index": "T21", "external_reference": {"dbpediaURI": "http://dbpedia.org/resource/United_States_Office_of_Personnel_Management", "wikidataid": "Q7890847"}, "endOffset": 858, "role": {"type": "Victim"}, "text": "OPM", "startOffset": 855, "type": "Organization"}], "subtype": "Databreach"}]}, {"index": 4, "events": [{"index": "E4", "type": "Attack", "realis": "Generic", "nugget": {"startOffset": 439, "index": "T11", "endOffset": 447, "text": "breaches"}, "argument": [{"index": "T12", "text": "information", "endOffset": 397, "role": {"type": "Compromised-Data"}, "startOffset": 386, "type": "Data"}, {"index": "T10", "text": "hackers", "endOffset": 462, "role": {"type": "Attacker"}, "startOffset": 455, "type": "Person"}, {"index": "T8", "text": "data", "endOffset": 504, "role": {"type": "Compromised-Data"}, "startOffset": 500, "type": "Data"}], "subtype": "Databreach"}]}, {"index": 5, "events": [{"index": "E5", "type": "Attack", "realis": "Generic", "nugget": {"startOffset": 578, "index": "T13", "endOffset": 584, "text": "stolen"}, "argument": [{"index": "T15", "text": "the data", "endOffset": 577, "role": {"type": "Compromised-Data"}, "startOffset": 569, "type": "Data"}, {"index": "T9", "text": "foreign entity", "endOffset": 559, "role": {"type": "Attacker"}, "startOffset": 545, "type": "Organization"}, {"index": "T14", "external_reference": {"dbpediaURI": "http://dbpedia.org/resource/United_States_Office_of_Personnel_Management", "wikidataid": "Q7890847"}, "endOffset": 593, "role": {"type": "Victim"}, "text": "OPM", "startOffset": 590, "type": "Organization"}], "subtype": "Databreach"}]}]}, "info": {"title": "Feds more at risk from clicking on links than from data stolen during OPM breach - FederalNewsRadio.com", "date": "2017_02_21", "type": "text", "link": "http://federalnewsradio.com/ask-the-cio/2017/02/feds-risk-clicking-links-data-stolen-opm-breach/"}} |
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{"poster":"Christian tomson","date":"2017-03-18T08:23:00.520+0000","title":"fps/ping spikes getting out of hand","subforum":"[ARCHIVED] Help & Support","embed":{"description":"February 3rd, 2011 by Dragos M. | Filed under Uncategorized. Thank you for your bug reports and feature requests. Portable Apps is a complete, free and very useful collection of portable applications. Go get all the cool Open Source apps on an USB stick, WinMTR included!","url":"http://winmtr.net/winmtr-v0-92-now-available/","image":"http://winmtr.net/wp-content/uploads/2012/10/2012-10-250x208-serverBacon-v1.jpg"},"up_votes":1,"down_votes":0,"body":"I see there seems to be a popular issue with ping spikes and fps jumps during this patch cycle. \r\nI thought it might be my rig or my ISP giving me the short end of the bandwidth but my connectivity is above average for the region, and during game play i don't have any other CPU consuming processes running.\r\nHowever, when there is a lot of player activity (Like a 5v5 exchange) ping spikes and fps issues seem to swarm my comp, and no matter how low i set the graphics these issues don't subside. {{sticker:zombie-brand-mindblown}}","replies":[{"poster":"Broporo","date":"2017-03-18T21:18:40.249+0000","up_votes":1,"down_votes":0,"body":"Even though your connection may be 100%, when you go into team fights (or any other time there is a lot of stuff going on at once) your connection can take a dip. This happens because it's harder to process all the stuff going on at once. Go through our [Connection Guide](https://support.riotgames.com/hc/en-us/articles/201752664-Troubleshooting-Connection-Issues) to be sure you have a stable connection.\n\nLet me know if you're still having issues after that.","replies":[{"poster":"Christian tomson","date":"2017-03-25T06:53:28.147+0000","up_votes":2,"down_votes":0,"body":"Thank you for your help!{{sticker:slayer-pantheon-thumbs}} \n I know you get a lot of emails about patch issues and there isn't always a quick solution, so \nI looked through the Trouble Shooting Guide; you gave me the link to, but not even \na wired connection is not stopping the issue. \nMy firewall and packet data don't seem to be an issue and it isn't a DNS or Proxy problem.\nI'm still at a loss as to the cause,\n i think the new patch is causing some frustration to the League Servers.{{champion:32}}","replies":[{"poster":"Broporo","date":"2017-03-25T20:15:19.762+0000","up_votes":1,"down_votes":0,"body":"It sounds like you've already done a great deal of troubleshooting on your end, so your issue might be something veeeeeery specific. I'd like for us to be able to look at your issue one on one, so reach out to our tech guys in a [ticket](https://support.riotgames.com/hc/en-us/requests/new).\n\nThey'll be able to go much more in depth for you!","replies":[]}]},{"poster":"Man In Sky","date":"2017-03-19T00:44:24.743+0000","up_votes":1,"down_votes":1,"body":"You do realize a huge amount of users are having this issue due to 7.5 patch? It is not from our side. \n\nI go from 235 fps to 60-80? Please don't tell me to check your connection guide lol. Fix your damn patch already.","replies":[]}]}]} |
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{"poster":"Vankleff","date":"2016-09-11T19:44:17.240+0000","title":"Que se pueda pingear las cargas del \"Cuchillo del rastreador\"","subforum":"Charlas Generales","up_votes":4,"down_votes":0,"body":"Nada, al igual que la sighstone estaria bueno que se puediera pingear cuando no te quedan wards en el item\r\n(para los que no sepan es el Smite verde/blanco que te deja wardear)","replies":[]} |
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{
"directions": [
"Preheat an oven to 350 degrees F (175 degrees C). Grease a baking dish large enough to hold the tenderloin without folding it.",
"Heat the olive oil in a large skillet over medium-high heat, and brown the pork tenderloin on all sides. Remove the browned tenderloin to the prepared baking dish. Sprinkle all sides of the meat with salt, pepper, and parsley.",
"Cook and stir the onion and apple in the same skillet over medium heat until the onion becomes soft, about 5 minutes, and pour in the Riesling wine. Scrape all the browned flavor bits off the bottom of the skillet and stir to help dissolve them into the wine. Bring to a boil, and pour the onion, apple, and wine mixture over the tenderloin.",
"Mix together the apple jelly and balsamic vinegar in a bowl until the mixture is smooth and without lumps. Spread the jelly mixture all over the pork.",
"Bake loin in the preheated oven until an instant-read thermometer inserted into the center reads 145 degrees F (63 degrees C), 30 to 45 minutes. Allow the tenderloin to rest for 10 minutes before slicing, and serve each slice with a spoonful of the apple-onion mixture."
],
"image": "https://imagesvc.meredithcorp.io/v3/mm/image?q=85&c=sc&poi=face&w=3648&h=1910&url=https%3A%2F%2Fimages.media-allrecipes.com%2Fuserphotos%2F659754.jpg",
"ingredients": [
"1 tablespoon olive oil",
"1 (1 1/4 pound) pork tenderloin",
"kosher salt and ground black pepper to taste",
"2 teaspoons chopped fresh parsley",
"\u00bd sweet onion, diced",
"1 Gala apple, cut into chunks",
"\u00bd cup Riesling wine",
"1 cup apple jelly",
"2 tablespoons balsamic vinegar"
],
"language": "en-US",
"source": "allrecipes.com",
"tags": [],
"title": "Apple Glazed Pork Tenderloin",
"url": "http://allrecipes.com/recipe/211179/apple-glazed-pork-tenderloin/"
} |
{"id":67933,"kecid":5606,"name":"Kalaena Kiri","hash":"bd566f1c640e945f2d8a3dd83086d8ae","related":{"kecamatan":{"id":5606,"nama":"Kalaena"},"kabupaten":{"id":408,"nama":"Kabupaten Luwu Timur","ibukota":"Malili"},"provinsi":{"id":27,"nama":"Sulawesi Selatan"}}}
|
{"id":27153,"name":"Dusklight Suit♂","description":"Imbue to increase Defense and Resistance."} |
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{
"name": "salarycalculationapp",
"version": "0.0.1",
"description": "Salary calculation demo app",
"dependencies": {
"mime": "~1.2.7",
"connect": "2.19.4",
"mongoose": "latest",
"express": "4.x",
"passport": "0.2.0",
"passport-google": "0.3.0",
"ejs": "1.0.0",
"method-override": "2.0.2",
"body-parser": "1.4.2"
}
} |
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{"poster":"NøMercy","date":"2017-04-15T08:50:31.533+0000","title":"S1 sucks - why...","subforum":"Gameplay & Strategy","up_votes":1,"down_votes":0,"body":"Well tbh there isn't much difference between bronze, silver and gold and some plat players are terrible. Upon reaching S1 there happens to be very high increase in the level of stupidity and uncoordination between team members. They would constantly feed their lanes upon return to lane every single match. Yeah strange how S1 is worse and much harder to get out since it feels like your playing with a team of B5's. It's Silver 1, shouldn't it be slightly better than the previous divisions and expected to have players a bit more skillful.... but no it's the opposite - somehow.. I feel as though Silver 1 is somehow the new Bronze 5 which is weird like I said. Any reasons why this is so..... and I lost 10 games and won 1 over the duration of 2 days... rip - my Mmr dropped so hard.... Of course climbing the ladder is hard, but not in the way you get ppl who don't know what they're doing and making really dumb decisions. Cmon ppl as you get a rank higher than before you're expected to perform to the standards and not bloody feed or die idiotically. Overall S5 to S2 was fun I suppose, pretty fair matches with everyone performing well and pulling their weight. S1 hmmm how does that division become Bronze 5. Its just literally an mmr drainer and drags to down.... way dddddooooowwwwnnn to playing with mindless players. Let me hear your thought and if you've experienced a similar thing. Or if silver is just downright cancerous to play in. And yeah since being in Silver I or lower I had a team full of golds or even plats. Jeez, they're terrible as if bronze..","replies":[{"poster":"Dark Warrior","date":"2017-04-15T21:08:28.025+0000","up_votes":1,"down_votes":0,"body":"well there is a big difference between Bronze-Silver-Gold-Plat if not then these rank system till plat would not exist, and in saying so sometimes its just bad games, secondly sometimes your gold 5 player might b v/s G1 or plat 5 (skill difference) or even vs lower rank doesn't matter he can still lose bcoz of his own miss plays, so that's how he/she lose lanes which makes them TILT and lose games.\n\n\nsometimes i lose lane to Silver players lmao and i am G2 well was, just got demoted to G3 lmao but it happens, sometimes you are overconfident and lose lane or miss plays, so learn and climb that's how i climb :)\n\n\n\n\nand if you see an unranked player and you notice he is feeding, it means he is new in rank and not aware of rank games, so please tell him in a sweet way that practice more in normal's than flaming that person :( i see so many players dont want to even play normal games nowadays bcoz of this OCE community is so toxic :/","replies":[]},{"poster":"Qilli","date":"2017-04-15T12:06:06.220+0000","up_votes":1,"down_votes":0,"body":"unranked ppl start around that mmr i think :^)","replies":[]}]} |
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{
"directions": [
"Rinse clams in a strainer to remove any sand.",
"Heat the olive oil in a large pot (5-quart) over medium to low heat. Add the diced onions, stirring often, until the onions are translucent, about 5 minutes.",
"Add the sausage and garlic, red pepper flakes, and fennel. Cook until sausage is no longer pink, about 2 minutes. Drain oil.",
"Increase the heat to medium high. Pour in the wine and bring to a boil until it has reduced to about 3 tablespoons, approximately 5 minutes.",
"Stir in the Classico(R) Tomato & Basil sauce and bring to a quick boil. Add the clams, cover, and cook until clam shells open, 8 to 10 minutes. Check often to avoid overcooking.",
"Preheat oven to 375 degrees F (190 degrees C).",
"Mix together remaining 2 tablespoons olive oil, 2 cloves minced garlic, salt, and cracked pepper. Brush mixture on both sides of the baguette slices. Arrange slices on a baking sheet.",
"Bake until its golden brown, 8 to 10 minutes.",
"Ladle the clams and sauce into bowls; top with fresh parsley and shaved parmesan cheese. Serve with the crostini."
],
"ingredients": [
"48 littleneck clams, scrubbed and rinsed",
"4 tablespoons olive oil, divided",
"1/4 cup Vidalia onion, diced",
"3/4 pound bulk hot Italian sausage",
"8 large cloves garlic, minced, divided",
"1/4 teaspoon crushed red pepper flakes, or to taste",
"1 teaspoon fennel seed",
"1 cup dry white wine",
"1 (24 ounce) jar Classico\u00ae Tomato and Basil Sauce",
"2 tablespoons minced fresh flat-leaf parsley",
"2 tablespoons shaved Parmesan cheese",
"Crostini:",
"1 French baguette, sliced into 1/4 inch rounds",
"Cracked black pepper",
"Coarse sea salt"
],
"language": "en-US",
"source": "allrecipes.com",
"tags": [],
"title": "Clams and Sausage in Spicy Marinara with Crostini",
"url": "http://allrecipes.com/recipe/238621/clams-and-sausage-in-spicy-marinara-w/"
}
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{"date": "2016-01-20", "text": "Hillary Clinton released the following statement after the \u0412\u00a0National Treasury Employees Union endorsed her campaign for President. Clinton now has the endorsement of 22 national labor unions or labor alliances representing over 12 million American workers.\"I am honored to have earned the endorsement of the National Treasury Employees Union and their 150,000 employees in 31 agencies and departments.\"For decades, NTEU members have helped America work\u0412\u2014and along the way, they have helped build the American middle class by fighting for higher wages, paid family leave, and a secure and dignified retirement.\"As President, I will always stand up for workers' rights and protect retirement security, including defined benefit plans and Social Security. I'm proud to stand with federal workers, including the men and women of NTEU, to build a better future for working families. Because when workers are strong, families are strong\u0412\u2014and when families are strong, America is strong.\"", "title": "Statement on the Endorsement of the National Treasury Employees Union"}
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{"poster":"[NEM SIKERÜLT KIOLVASNI]","date":"2016-01-13T02:22:42.678+0000","title":"League Community Podcast Ep. 5","subforum":"Announcements","up_votes":1,"down_votes":2,"body":"[ÜRES]","replies":[{"poster":"NonsenseCabbage","date":"2016-01-14T22:36:27.308+0000","up_votes":10,"down_votes":0,"body":"Personally ive been around since {{champion:121}} has and i have never felt a better insight into riot itself besides the patch rundowns which dont really give us all that much detail besides explaining patch notes. this needs to happen more in my opinion","replies":[{"poster":"Zwill","date":"2016-01-15T00:16:39.520+0000","up_votes":5,"down_votes":0,"body":"Thanks Avenge! Right now we're aiming for a weekly release cadence, so be sure to subscribe for regular updates!","replies":[{"poster":"Rx Peanut","date":"2016-01-15T04:45:32.445+0000","up_votes":2,"down_votes":0,"body":" i was just about to say something similar. I love these podcasts they are great but they feel kind of sporadic and that was the only downfall of the podcast in my opinion. Without the patch rundown, it seemed like riot was the god entity that we really didnt have much communication with.","replies":[]}]},{"poster":"Mister Sunglow","date":"2016-01-15T23:36:13.405+0000","up_votes":1,"down_votes":0,"body":"I agree. It's a good thing to listen to while I install the Update LOL. So I know what to expect when it's done.","replies":[]}]},{"poster":"bahiwahi","date":"2016-01-14T20:50:58.367+0000","up_votes":1,"down_votes":22,"body":"No one Watchs the podcasts...","replies":[{"poster":"NonsenseCabbage","date":"2016-01-14T20:58:00.168+0000","up_votes":9,"down_votes":0,"body":"i watch em, its the only way i can actually see more into the development process of the game which i think is a great connection between the devs and the player","replies":[{"poster":"AntiSkillshot","date":"2016-01-14T21:45:41.473+0000","up_votes":3,"down_votes":0,"body":"That and telling us the backgrounds of the devs and some of the pro players is great for the playerbase.","replies":[{"poster":"Caitycoo","date":"2016-01-14T22:27:15.730+0000","up_votes":4,"down_votes":0,"body":"I'll probably start listening to some of them now, thanks\r\n","replies":[{"poster":"NonsenseCabbage","date":"2016-01-14T22:29:14.494+0000","up_votes":7,"down_votes":0,"body":"also yeah how the hell can you watch a podcast like really. i didnt know i grew mutant eyes coming from my ears","replies":[]}]},{"poster":"Riot TreblMuffin","date":"2016-01-15T01:25:19.657+0000","up_votes":4,"down_votes":0,"body":"This is my personal favorite part. I like to find out who people are and how that informs their decision making. ","replies":[]}]}]},{"poster":"LaoBushido","date":"2016-01-14T21:37:14.875+0000","up_votes":6,"down_votes":0,"body":"Dude these are awesome you should try listening to them.","replies":[]},{"poster":"Blüescreen","date":"2016-01-15T20:50:11.386+0000","up_votes":1,"down_votes":0,"body":"Correction, Everyone watchs the podcasts but bahiwahi","replies":[]}]},{"poster":"LaoBushido","date":"2016-01-14T21:40:29.882+0000","up_votes":4,"down_votes":0,"body":"How did much did you guys plan this? Now one saw the Shen update coming (and you guys came out with this the next day) and you guys didn't censor anything like with the poppy update. Should we expect a second riot scruffy interview when taRic comes out? ","replies":[{"poster":"A Small Man","date":"2016-01-14T22:59:54.121+0000","up_votes":5,"down_votes":0,"body":"Shen actually did come a bit out of the blue for the podcast team; fortunately, we're building our pipeline with a heavy focus on flexibility and quick turnaround times so we were able to quickly put together the episode. Staying agile like that will help us make sure we're bringing you folks timely conversations and insight, even when timelines shift or new topics emerge suddenly. Make sure to let us know how we're doing down the line!\r\n\r\nAnd yes, we will absolutely be talking Taric at some point, though guests are still up in the air.","replies":[]}]},{"poster":"Bunquez","date":"2016-01-14T21:14:05.853+0000","up_votes":1,"down_votes":7,"body":"The fact that there has been 3 comments and 1 good response tells me these aren't too popular..\r\n","replies":[{"poster":"NonsenseCabbage","date":"2016-01-14T22:31:12.313+0000","up_votes":5,"down_votes":0,"body":"they arent too popular because no one gives them a shot, and its all about youtube videos nowadays. this is probably the best thing league related besides actual gameplay ive found in quite some time.","replies":[]}]},{"poster":"JustTheBeginning","date":"2016-01-14T23:55:57.536+0000","up_votes":3,"down_votes":0,"body":"i like this\r\n","replies":[]},{"poster":"Cosnirak","date":"2016-01-15T04:23:26.995+0000","up_votes":2,"down_votes":0,"body":"\"That resolves.\" Someone's a blue mage! xD","replies":[]},{"poster":"G1NGER BEAR","date":"2016-01-15T03:43:59.155+0000","up_votes":2,"down_votes":0,"body":"I really enjoyed the podcast looking forward to hearing more :D","replies":[]},{"poster":"Overvoid00","date":"2016-01-15T02:28:22.491+0000","up_votes":2,"down_votes":0,"body":"I absolutely love these podcasts. I've always wondered about riot's design process and these give amazing insight. Please keep making them! :D\r\n","replies":[]},{"poster":"Slevin Kelevera","date":"2016-01-15T00:27:05.096+0000","up_votes":2,"down_votes":0,"body":"If this much thought was put into remaking {{champion:98}} I would love to hear the thought process behind Jhin in the next one. Also for a new podcast I think the host is doing an excellent job keeping things interesting and the topics fresh. Been loving the casts since Episode 1.","replies":[{"poster":"Zwill","date":"2016-01-15T01:02:44.269+0000","up_votes":2,"down_votes":0,"body":"Jhin may or may not already be in the pipe ;). ","replies":[]}]},{"poster":"WV Byrd","date":"2016-01-15T00:04:40.955+0000","up_votes":2,"down_votes":4,"body":"As super uninteresting this dumb podcast is I now have to wait for 30 minutes because in Queues my screen turns blurred and now I'm sitting here bored out of my damn mind because you guys manage to fuck up every patch, Thanks Rito. Now I know why Dunkey quit.","replies":[{"poster":"Sir Moonie","date":"2016-01-17T23:08:08.302+0000","up_votes":2,"down_votes":0,"body":"wow you showed them, lol","replies":[]}]},{"poster":"Ben R4mZ","date":"2018-02-07T16:03:21.575+0000","up_votes":1,"down_votes":0,"body":"EXCUSE ME?!?!? Where are they?????\r\n>:c\r\nGive me my podcasts back!!!","replies":[]},{"poster":"Enx684","date":"2016-02-25T21:22:14.300+0000","up_votes":1,"down_votes":0,"body":"{{champion:83}} {{champion:83}} {{champion:83}} ","replies":[]},{"poster":"ExecutorDill","date":"2016-01-18T05:48:21.596+0000","up_votes":1,"down_votes":0,"body":"DilonMostDirty xD you have my name xDDDD!!","replies":[]},{"poster":"Macrell","date":"2016-01-18T02:34:47.165+0000","up_votes":1,"down_votes":0,"body":"{{champion:1}} {{summoner:6}} {{champion:32}} {{summoner:3}} ","replies":[]},{"poster":"DEMAGLIOOOOOOOOO","date":"2016-01-18T01:27:30.977+0000","up_votes":1,"down_votes":0,"body":"i like listening to these in the background while I play soloQ","replies":[]},{"poster":"Zakutoys","date":"2016-01-17T21:30:25.971+0000","up_votes":1,"down_votes":0,"body":"Will Shen still be tanky because in the skin spotlights i see Shen with about only 2k hp?","replies":[]},{"poster":"Milodic Mellodi","date":"2016-01-17T19:17:17.177+0000","up_votes":1,"down_votes":0,"body":"I'm thinking about doing Graphic Design/Game Design, but I don't make much money and I haven't yet finished my pre-requisites. How would I be able to be a game designer, if I even can?","replies":[]},{"poster":"Kingcvbnmz","date":"2016-01-16T06:31:46.042+0000","up_votes":1,"down_votes":0,"body":"hi","replies":[]},{"poster":"Dreadlocks","date":"2016-01-15T20:00:10.728+0000","up_votes":1,"down_votes":0,"body":"So since you nerfed Shen's Q, and buffed his E to scale with HP, does that mean maxing E is the way to go now? Intended?","replies":[]},{"poster":"V The Support V","date":"2016-01-15T09:03:09.328+0000","up_votes":1,"down_votes":0,"body":"12:59 - 13:32 . . . Notable Mentions. . . Yi . . . Kennen . . . ","replies":[]},{"poster":"V The Support V","date":"2016-01-15T08:58:44.205+0000","up_votes":1,"down_votes":0,"body":"9:47 - 11:30 ","replies":[]},{"poster":"OhWanderer","date":"2016-01-15T02:08:39.158+0000","up_votes":1,"down_votes":0,"body":"is shen going to reach behind him and grab the sword on his back that is the spirit sword when he goes to manipulate it? or am i confused about that, the smaller fancy sword is the \"spirit sword\" right?","replies":[]},{"poster":"GuestX","date":"2016-01-15T02:01:21.761+0000","up_votes":1,"down_votes":0,"body":"These podcasts are great; They are incredibly informative of the community and aspects outside of the in game play that everyone sees. I don't understand why all these comments are mostly negative when we should be thanking the creators and the guests for taking time out of their own lives to make an informatively fun podcast (without pay I assume). Thanks, {{champion:112}} 's (Creators :P)!","replies":[]},{"poster":"Bieza","date":"2016-01-15T01:19:04.336+0000","up_votes":0,"down_votes":0,"body":"why cant I click at a specific part on the podcast to go to that section? Do I need to be on soundcloud?","replies":[]},{"poster":"Elijsha","date":"2016-01-14T20:31:29.592+0000","up_votes":1,"down_votes":5,"body":"a full hour and none commented yet lol","replies":[]}]} |
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NON _ BLOCKED ;", "}", "METHOD_END"], "methodName": ["scheduleAppend"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHolePageSink"}, {"methodBody": ["METHOD_START", "{", "checkArgument ( isSupportedType ( type ) , \" Unsupported type [ % s ] \" , type ) ;", "Slice slice ;", "if ( isVarcharType ( type ) ) {", "slice = constantSlice . slice ( 0 , Math . min ( ( ( VarcharType ) ( type ) ) . getLength ( ) , constantSlice . length ( ) ) ) ;", "} else", "if ( isLongDecimal ( type ) ) {", "slice = encodeScaledValue ( ZERO ) ;", "} else {", "slice = constantSlice ;", "}", "BlockBuil buil ;", "if ( type instanceof FixedWidthType ) {", "buil = type . createBlockBuil ( null , rowsCount ) ;", "} else {", "buil = type . createBlockBuil ( null , rowsCount , slice . length ( ) ) ;", "}", "for ( int i = 0 ; i < rowsCount ; i + + ) {", "Class < ? > javaType = type . getJavaType ( ) ;", "if ( javaType = = ( boolean . class ) ) {", "type . writeBoolean ( buil , false ) ;", "} else", "if ( javaType = = ( long . class ) ) {", "type . writeLong ( buil , 0 ) ;", "} else", "if ( javaType = = ( double . class ) ) {", "type . writeDouble ( buil , 0 . 0 ) ;", "} else", "if ( javaType = = ( Slice . class ) ) {", "requireNonNull ( slice , \" slice is null \" ) ;", "type . writeSlice ( buil , slice , 0 , slice . length ( ) ) ;", "} else {", "throw new UnsupportedOperationException ( ( \" Unknown javaType : \" + ( getName ( ) ) ) ) ;", "}", "}", "return buil . build ( ) ;", "}", "METHOD_END"], "methodName": ["createZeroBlock"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHolePageSourceProvider"}, {"methodBody": ["METHOD_START", "{", "byte [ ] constantBytes = new byte [ fieldLength ] ;", "Arrays . fill ( constantBytes , ( ( byte ) ( 4 2 ) ) ) ;", "Slice constantSlice = Slices . wrappedBuffer ( constantBytes ) ;", "Block [ ] blocks = new Block [ types . size ( ) ] ;", "for ( int i = 0 ; i < ( blocks . length ) ; i + + ) {", "blocks [ i ] = createZeroBlock ( types . get ( i ) , rowsCount , constantSlice ) ;", "}", "return new spi . Page ( rowsCount , blocks ) ;", "}", "METHOD_END"], "methodName": ["generateZeroPage"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHolePageSourceProvider"}, {"methodBody": ["METHOD_START", "{", "return ( ( ( ImmutableSet . < Type > of ( TINYINT , SMALLINT , INTEGER , BIGINT , REAL , DOUBLE , BOOLEAN , DATE , TIMESTAMP , VARBINARY ) . contains ( type ) ) | | ( isVarcharType ( type ) ) ) | | ( isLongDecimal ( type ) ) ) | | ( isShortDecimal ( type ) ) ;", "}", "METHOD_END"], "methodName": ["isSupportedType"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHolePageSourceProvider"}, {"methodBody": ["METHOD_START", "{", "return BlackHoleQueryRunner . createQueryRunner ( ImmutableMap . of ( ) ) ;", "}", "METHOD_END"], "methodName": ["createQueryRunner"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHoleQueryRunner"}, {"methodBody": ["METHOD_START", "{", "Session session = testSessionBuilder ( ) . setCatalog ( \" blackhole \" ) . setSchema ( \" default \" ) . build ( ) ;", "Distributed queryRunner = new Distributed ( session , 4 , extraProperties ) ;", "try {", "queryRunner . installPlugin ( new BlackHolePlugin ( ) ) ;", "queryRunner . createCatalog ( \" blackhole \" , \" blackhole \" , ImmutableMap . of ( ) ) ;", "queryRunner . installPlugin ( new TpchPlugin ( ) ) ;", "queryRunner . createCatalog ( \" tpch \" , \" tpch \" , ImmutableMap . of ( ) ) ;", "return queryRunner ;", "} catch ( Exception e ) {", "Closeables . closeAllSuppress ( e , queryRunner ) ;", "throw e ;", "}", "}", "METHOD_END"], "methodName": ["createQueryRunner"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHoleQueryRunner"}, {"methodBody": ["METHOD_START", "{", "Logging . initialize ( ) ;", "DistributedQueryRunner queryRunner = . createQueryRunner ( ImmutableMap . of ( \" http - server . http . port \" , \" 8 0 8 0 \" ) ) ;", "Thread . sleep ( 1 0 ) ;", "Logger log = Logger . get ( . class ) ;", "log . info ( \" = = = = = = = = SERVER STARTED = = = = = = = = \" ) ;", "log . info ( \" \\ n = = = = \\ n % s \\ n = = = = \" , queryRunner . getCoordinator ( ) . getBaseUrl ( ) ) ;", "}", "METHOD_END"], "methodName": ["main"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHoleQueryRunner"}, {"methodBody": ["METHOD_START", "{", "return fieldsLength ;", "}", "METHOD_END"], "methodName": ["getFieldsLength"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHoleSplit"}, {"methodBody": ["METHOD_START", "{", "return pageProcessingDelay ;", "}", "METHOD_END"], "methodName": ["getPageProcessingDelay"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHoleSplit"}, {"methodBody": ["METHOD_START", "{", "return pagesCount ;", "}", "METHOD_END"], "methodName": ["getPagesCount"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHoleSplit"}, {"methodBody": ["METHOD_START", "{", "return rowsPerPage ;", "}", "METHOD_END"], "methodName": ["getRowsPerPage"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHoleSplit"}, {"methodBody": ["METHOD_START", "{", "return columnHandles ;", "}", "METHOD_END"], "methodName": ["getColumnHandles"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHoleTableHandle"}, {"methodBody": ["METHOD_START", "{", "return fieldsLength ;", "}", "METHOD_END"], "methodName": ["getFieldsLength"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHoleTableHandle"}, {"methodBody": ["METHOD_START", "{", "return pageProcessingDelay ;", "}", "METHOD_END"], "methodName": ["getPageProcessingDelay"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHoleTableHandle"}, {"methodBody": ["METHOD_START", "{", "return pagesPerSplit ;", "}", "METHOD_END"], "methodName": ["getPagesPerSplit"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHoleTableHandle"}, {"methodBody": ["METHOD_START", "{", "return rowsPerPage ;", "}", "METHOD_END"], "methodName": ["getRowsPerPage"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHoleTableHandle"}, {"methodBody": ["METHOD_START", "{", "return schemaName ;", "}", "METHOD_END"], "methodName": ["getSchemaName"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHoleTableHandle"}, {"methodBody": ["METHOD_START", "{", "return splitCount ;", "}", "METHOD_END"], "methodName": ["getSplitCount"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHoleTableHandle"}, {"methodBody": ["METHOD_START", "{", "return tableName ;", "}", "METHOD_END"], "methodName": ["getTableName"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHoleTableHandle"}, {"methodBody": ["METHOD_START", "{", "return new SchemaTableName ( schemaName , tableName ) ;", "}", "METHOD_END"], "methodName": ["toSchemaTableName"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHoleTableHandle"}, {"methodBody": ["METHOD_START", "{", "return new com . facebook . presto . spi . ConnectorTableMetadata ( toSchemaTableName ( ) , columnHandles . stream ( ) . map ( BlackHoleColumnHandle : : toColumnMetadata ) . collect ( Collectors . toList ( ) ) ) ;", "}", "METHOD_END"], "methodName": ["toTableMetadata"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHoleTableHandle"}, {"methodBody": ["METHOD_START", "{", "return fieldsLength ;", "}", "METHOD_END"], "methodName": ["getFieldsLength"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHoleTableLayoutHandle"}, {"methodBody": ["METHOD_START", "{", "return pageProcessingDelay ;", "}", "METHOD_END"], "methodName": ["getPageProcessingDelay"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHoleTableLayoutHandle"}, {"methodBody": ["METHOD_START", "{", "return pagesPerSplit ;", "}", "METHOD_END"], "methodName": ["getPagesPerSplit"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHoleTableLayoutHandle"}, {"methodBody": ["METHOD_START", "{", "return rowsPerPage ;", "}", "METHOD_END"], "methodName": ["getRowsPerPage"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHoleTableLayoutHandle"}, {"methodBody": ["METHOD_START", "{", "return splitCount ;", "}", "METHOD_END"], "methodName": ["getSplitCount"], "fileName": "com.facebook.presto.plugin.blackhole.BlackHoleTableLayoutHandle"}, {"methodBody": ["METHOD_START", "{", "assertEquals ( metadata . listTables ( SESSION , null ) , ImmutableList . of ( ) , \" No table was expected \" ) ;", "}", "METHOD_END"], "methodName": ["assertThatNoTableIsCreated"], "fileName": "com.facebook.presto.plugin.blackhole.TestBlackHoleMetadata"}, {"methodBody": ["METHOD_START", "{", "assertThatNoTableIsCreated ( ) ;", "SchemaTableName schemaTableName = new SchemaTableName ( \" default \" , \" temp _ table \" ) ;", "ConnectorOutputTableHandle table = metadata . beginCreateTable ( SESSION , new spi . ConnectorTableMetadata ( schemaTableName , ImmutableList . of ( ) , tableProperties ) , Optional . empty ( ) ) ;", "assertThatNoTableIsCreated ( ) ;", "metadata . finishCreateTable ( SESSION , table , ImmutableList . of ( ) ) ;", "List < SchemaTableName > tables = metadata . listTables ( SESSION , null ) ;", "assertTrue ( ( ( tables . size ( ) ) = = 1 ) , \" Expected only one table . \" ) ;", "assertTrue ( tables . get ( 0 ) . getTableName ( ) . equals ( \" temp _ table \" ) , \" Expected table with name ' temp _ table ' \" ) ;", "}", "METHOD_END"], "methodName": ["tableIsCreatedAfterCommits"], "fileName": "com.facebook.presto.plugin.blackhole.TestBlackHoleMetadata"}, {"methodBody": ["METHOD_START", "{", "assertEquals ( metadata . listSchemaNames ( SESSION ) , ImmutableList . of ( \" default \" ) ) ;", "metadata . createSchema ( SESSION , \" test \" , ImmutableMap . of ( ) ) ;", "assertEquals ( metadata . listSchemaNames ( SESSION ) , ImmutableList . of ( \" default \" , \" test \" ) ) ;", "}", "METHOD_END"], "methodName": ["testCreateSchema"], "fileName": "com.facebook.presto.plugin.blackhole.TestBlackHoleMetadata"}, {"methodBody": ["METHOD_START", "{", "SchemaTableName schemaTableName = new SchemaTableName ( \" schema 1 \" , \" test _ table \" ) ;", "try {", "metadata . beginCreateTable ( SESSION , new spi . ConnectorTableMetadata ( schemaTableName , ImmutableList . of ( ) , tableProperties ) , Optional . empty ( ) ) ;", "fail ( \" Should fail because schema does not exist \" ) ;", "} catch ( PrestoException ex ) {", "assertEquals ( ex . getErrorCode ( ) , NOT _ FOUND . toErrorCode ( ) ) ;", "assertTrue ( ex . getMessage ( ) . equals ( \" Schema schema 1 not found \" ) ) ;", "}", "}", "METHOD_END"], "methodName": ["testCreateTableInNotExistSchema"], "fileName": "com.facebook.presto.plugin.blackhole.TestBlackHoleMetadata"}, {"methodBody": ["METHOD_START", "{", "assertTrue ( ( ( listBlackHoleTables ( ) . size ( ) ) = = 0 ) , \" No blackhole tables expected \" ) ;", "}", "METHOD_END"], "methodName": ["assertThatNoBlackHoleTableIsCreated"], "fileName": "com.facebook.presto.plugin.blackhole.TestBlackHoleSmoke"}, {"methodBody": ["METHOD_START", "{", "assertThatQueryReturnsValue ( sql , expected , null ) ;", "}", "METHOD_END"], "methodName": ["assertThatQueryReturnsValue"], "fileName": "com.facebook.presto.plugin.blackhole.TestBlackHoleSmoke"}, {"methodBody": ["METHOD_START", "{", "MaterializedResult rows = ( session = = null ) ? queryRunner . execute ( sql ) : queryRunner . execute ( session , sql ) ;", "MaterializedRow materializedRow = Iterables . getOnlyElement ( rows ) ;", "int fieldCount = materializedRow . getFieldCount ( ) ;", "assertTrue ( ( fieldCount = = 1 ) , String . format ( \" Expected only one column , but got ' % d ' \" , fieldCount ) ) ;", "Object value = materializedRow . getField ( 0 ) ;", "assertEquals ( value , expected ) ;", "assertTrue ( ( ( Iterables . getOnlyElement ( rows ) . getFieldCount ( ) ) = = 1 ) ) ;", "}", "METHOD_END"], "methodName": ["assertThatQueryReturnsValue"], "fileName": "com.facebook.presto.plugin.blackhole.TestBlackHoleSmoke"}, {"methodBody": ["METHOD_START", "{", "assertThatQueryReturnsValue ( \" CREATE TABLE nation as SELECT * FROM tpch . tiny . nation \" , 2 5 L ) ;", "List < QualifiedObjectName > tableNames = liTables ( ) ;", "assertTrue ( ( ( tableNames . size ( ) ) = = 1 ) , \" Expected only one table . \" ) ;", "assertTrue ( tableNames . get ( 0 ) . getObjectName ( ) . equals ( \" nation \" ) , \" Expected ' nation ' table . \" ) ;", "assertThatQueryReturnsValue ( \" INSERT INTO nation SELECT * FROM tpch . tiny . nation \" , 2 5 L ) ;", "assertThatQueryReturnsValue ( \" INSERT INTO nation SELECT * FROM tpch . tiny . nation \" , 2 5 L ) ;", "assertThatQueryReturnsValue ( \" SELECT count ( * ) FROM nation \" , 0 L ) ;", "assertThatQueryReturnsValue ( \" DROP TABLE nation \" , true ) ;", "}", "METHOD_END"], "methodName": ["blackHoleConnectorUsage"], "fileName": "com.facebook.presto.plugin.blackhole.TestBlackHoleSmoke"}, {"methodBody": ["METHOD_START", "{", "assertThatQueryReturnsValue ( String . format ( ( \" CREATE TABLE blackhole _ all _ types ( \" + ( ( ( ( ( ( ( ( ( ( ( ( ( \" _ varchar VARCHAR ( 1 0 ) \" + \" , _ bigint BIGINT \" ) + \" , _ integer INTEGER \" ) + \" , _ smallint SMALLINT \" ) + \" , _ tinyint TINYINT \" ) + \" , _ real REAL \" ) + \" , _ double DOUBLE \" ) + \" , _ boolean BOOLEAN \" ) + \" , _ date DATE \" ) + \" , _ timestamp TIMESTAMP \" ) + \" , _ varbinary VARBINARY \" ) + \" , _ decimal _ short DECIMAL ( 3 , 2 ) \" ) + \" , _ decimal _ long DECIMAL ( 3 0 , 1 0 ) \" ) + \" ) WITH ( % s = 1 , % s = 1 , % s = 1 ) \" ) ) , BlackHoleConnector . ROWS _ PER _ PAGE _ PROPERTY , BlackHoleConnector . PAGES _ PER _ SPLIT _ PROPERTY , BlackHoleConnector . SPLIT _ COUNT _ PROPERTY ) , true ) ;", "}", "METHOD_END"], "methodName": ["createBlackholeAllTypesTable"], "fileName": "com.facebook.presto.plugin.blackhole.TestBlackHoleSmoke"}, {"methodBody": ["METHOD_START", "{", "String createTableSql = \" CREATE TABLE nation as SELECT * FROM tpch . tiny . nation \" ;", "queryRunner . execute ( createTableSql ) ;", "try {", "queryRunner . execute ( createTableSql ) ;", "fail ( \" Expected exception to be thrown here ! \" ) ;", "} catch ( RuntimeException ex ) {", "assertTrue ( ex . getMessage ( ) . equals ( \" line 1 : 1 : Destination table ' default . nation ' already exists \" ) ) ;", "} finally {", "assertThatQueryReturnsValue ( \" DROP TABLE nation \" , true ) ;", "}", "}", "METHOD_END"], "methodName": ["createTableWhenTableIsAlreadyCreated"], "fileName": "com.facebook.presto.plugin.blackhole.TestBlackHoleSmoke"}, {"methodBody": ["METHOD_START", "{", "assertThatQueryReturnsValue ( \" CREATE TABLE distributed _ test WITH ( distributed _ on = array [ ' orderkey ' ] ) AS SELECT * FROM tpch . tiny . orders \" , 1 5 0 0 0 L ) ;", "assertThatQueryReturnsValue ( \" DROP TABLE distributed _ test \" , true ) ;", "}", "METHOD_END"], "methodName": ["createTableWithDistribution"], "fileName": "com.facebook.presto.plugin.blackhole.TestBlackHoleSmoke"}, {"methodBody": ["METHOD_START", "{", "Session session = testSessionBuilder ( ) . setCatalog ( \" blackhole \" ) . setSchema ( \" default \" ) . build ( ) ;", "assertThatQueryReturnsValue ( String . format ( \" CREATE TABLE nation WITH ( % s = 3 , % s = 2 , % s = 1 ) as SELECT * FROM tpch . tiny . nation \" , BlackHoleConnector . ROWS _ PER _ PAGE _ PROPERTY , BlackHoleConnector . PAGES _ PER _ SPLIT _ PROPERTY , BlackHoleConnector . SPLIT _ COUNT _ PROPERTY ) , 2 5 L , session ) ;", "assertThatQueryReturnsValue ( \" SELECT count ( * ) FROM nation \" , 6 L , session ) ;", "assertThatQueryReturnsValue ( \" INSERT INTO nation SELECT * FROM tpch . tiny . nation \" , 2 5 L , session ) ;", "assertThatQueryReturnsValue ( \" SELECT count ( * ) FROM nation \" , 6 L , session ) ;", "MaterializedResult rows = queryRunner . execute ( session , \" SELECT * FROM nation LIMIT 1 \" ) ;", "assertEquals ( rows . getRowCount ( ) , 1 ) ;", "MaterializedRow row = Iterables . getOnlyElement ( rows ) ;", "assertEquals ( row . getFieldCount ( ) , 4 ) ;", "assertEquals ( row . getField ( 0 ) , 0 L ) ;", "assertEquals ( row . getField ( 1 ) , \" * * * * * * * * * * * * * * * * \" ) ;", "assertEquals ( row . getField ( 2 ) , 0 L ) ;", "assertEquals ( row . getField ( 3 ) , \" * * * * * * * * * * * * * * * * \" ) ;", "assertThatQueryReturnsValue ( \" DROP TABLE nation \" , true ) ;", "}", "METHOD_END"], "methodName": ["dataGenerationUsage"], "fileName": "com.facebook.presto.plugin.blackhole.TestBlackHoleSmoke"}, {"methodBody": ["METHOD_START", "{", "assertThatQueryReturnsValue ( \" DROP TABLE IF EXISTS blackhole _ all _ types \" , true ) ;", "}", "METHOD_END"], "methodName": ["dropBlackholeAllTypesTable"], "fileName": "com.facebook.presto.plugin.blackhole.TestBlackHoleSmoke"}, {"methodBody": ["METHOD_START", "{", "Session session = testSessionBuilder ( ) . setCatalog ( \" blackhole \" ) . setSchema ( \" default \" ) . build ( ) ;", "assertThatQueryReturnsValue ( String . format ( ( \" CREATE TABLE nation WITH ( % s = 8 , % s = 1 , % s = 1 , % s = 1 ) AS \" + \" SELECT nationkey , name , regionkey , comment , ' abc ' short _ varchar FROM tpch . tiny . nation \" ) , BlackHoleConnector . FIELD _ LENGTH _ PROPERTY , BlackHoleConnector . ROWS _ PER _ PAGE _ PROPERTY , BlackHoleConnector . PAGES _ PER _ SPLIT _ PROPERTY , BlackHoleConnector . SPLIT _ COUNT _ PROPERTY ) , 2 5 L , session ) ;", "MaterializedResult rows = queryRunner . execute ( session , \" SELECT * FROM nation \" ) ;", "assertEquals ( rows . getRowCount ( ) , 1 ) ;", "MaterializedRow row = Iterables . getOnlyElement ( rows ) ;", "assertEquals ( row . getFieldCount ( ) , 5 ) ;", "assertEquals ( row . getField ( 0 ) , 0 L ) ;", "assertEquals ( row . getField ( 1 ) , \" * * * * * * * * \" ) ;", "assertEquals ( row . getField ( 2 ) , 0 L ) ;", "assertEquals ( row . getField ( 3 ) , \" * * * * * * * * \" ) ;", "assertEquals ( row . getField ( 4 ) , \" * * * \" ) ;", "assertThatQueryReturnsValue ( \" DROP TABLE nation \" , true ) ;", "}", "METHOD_END"], "methodName": ["fieldLength"], "fileName": "com.facebook.presto.plugin.blackhole.TestBlackHoleSmoke"}, {"methodBody": ["METHOD_START", "{", "return queryRunner . listTables ( queryRunner . getDefaultSession ( ) , \" blackhole \" , \" default \" ) ;", "}", "METHOD_END"], "methodName": ["listBlackHoleTables"], "fileName": "com.facebook.presto.plugin.blackhole.TestBlackHoleSmoke"}, {"methodBody": ["METHOD_START", "{", "Session session = testSessionBuilder ( ) . setCatalog ( \" blackhole \" ) . setSchema ( \" default \" ) . build ( ) ;", "try {", "assertThatQueryReturnsValue ( String . format ( \" CREATE TABLE nation WITH ( % s = 3 , % s = 1 ) as SELECT * FROM tpch . tiny . nation \" , BlackHoleConnector . ROWS _ PER _ PAGE _ PROPERTY , BlackHoleConnector . SPLIT _ COUNT _ PROPERTY ) , 2 5 L , session ) ;", "fail ( \" Expected exception to be thrown here ! \" ) ;", "} catch ( RuntimeException ex ) {", "}", "}", "METHOD_END"], "methodName": ["notAllPropertiesSetForDataGeneration"], "fileName": "com.facebook.presto.plugin.blackhole.TestBlackHoleSmoke"}, {"methodBody": ["METHOD_START", "{", "Session session = testSessionBuilder ( ) . setCatalog ( \" blackhole \" ) . setSchema ( \" default \" ) . build ( ) ;", "Duration pageProcessingDelay = new Duration ( 1 , TimeUnit . SECONDS ) ;", "assertThatQueryReturnsValue ( String . format ( ( \" CREATE TABLE nation WITH ( % s = 8 , % s = 1 , % s = 1 , % s = 1 , % s = ' % s ' ) AS \" + \" SELECT * FROM tpch . tiny . nation \" ) , BlackHoleConnector . FIELD _ LENGTH _ PROPERTY , BlackHoleConnector . ROWS _ PER _ PAGE _ PROPERTY , BlackHoleConnector . PAGES _ PER _ SPLIT _ PROPERTY , BlackHoleConnector . SPLIT _ COUNT _ PROPERTY , BlackHoleConnector . PAGE _ PROCESSING _ DELAY , pageProcessingDelay ) , 2 5 L , session ) ;", "Stopwatch stopwatch = Stopwatch . createStarted ( ) ;", "assertEquals ( queryRunner . execute ( session , \" SELECT * FROM nation \" ) . getRowCount ( ) , 1 ) ;", "queryRunner . execute ( session , \" INSERT INTO nation SELECT CAST ( null AS BIGINT ) , CAST ( null AS VARCHAR ( 2 5 ) ) , CAST ( null AS BIGINT ) , CAST ( null AS VARCHAR ( 1 5 2 ) ) \" ) ;", "stopwatch . stop ( ) ;", "Assertions . assertGreaterThan ( stopwatch . elapsed ( TimeUnit . MILLISECONDS ) , pageProcessingDelay . toMillis ( ) ) ;", "assertThatQueryReturnsValue ( \" DROP TABLE nation \" , true ) ;", "}", "METHOD_END"], "methodName": ["pageProcessingDelay"], "fileName": "com.facebook.presto.plugin.blackhole.TestBlackHoleSmoke"}, {"methodBody": ["METHOD_START", "{", "queryRunner = BlackHoleQueryRunner . createQueryRunner ( ) ;", "}", "METHOD_END"], "methodName": ["setUp"], "fileName": "com.facebook.presto.plugin.blackhole.TestBlackHoleSmoke"}, {"methodBody": ["METHOD_START", "{", "assertThatNoBlackHoleTableIsCreated ( ) ;", "queryRunner . close ( ) ;", "}", "METHOD_END"], "methodName": ["tearDown"], "fileName": "com.facebook.presto.plugin.blackhole.TestBlackHoleSmoke"}, {"methodBody": ["METHOD_START", "{", "assertEquals ( queryRunner . execute ( \" SHOW SCHEMAS FROM ) . getRowCount ( ) , 2 ) ;", "queryRunner . execute ( \" CREATE SCHEMA test \" ) ;", "assertEquals ( queryRunner . execute ( \" SHOW SCHEMAS FROM ) . getRowCount ( ) , 3 ) ;", "}", "METHOD_END"], "methodName": ["testCreateSchema"], "fileName": "com.facebook.presto.plugin.blackhole.TestBlackHoleSmoke"}, {"methodBody": ["METHOD_START", "{", "int tablesBeforeCreate = listBlackHoleTables ( ) . size ( ) ;", "String createTableSql = \" CREATE TABLE schema 1 . test _ table ( x date ) \" ;", "try {", "queryRunner . execute ( createTableSql ) ;", "fail ( \" Expected exception to be thrown here ! \" ) ;", "} catch ( RuntimeException ex ) {", "assertTrue ( ex . getMessage ( ) . equals ( \" Schema schema 1 not found \" ) ) ;", "}", "int tablesAfterCreate = listBlackHoleTables ( ) . size ( ) ;", "assertEquals ( tablesBeforeCreate , tablesAfterCreate ) ;", "}", "METHOD_END"], "methodName": ["testCreateTableInNotExistSchema"], "fileName": "com.facebook.presto.plugin.blackhole.TestBlackHoleSmoke"}, {"methodBody": ["METHOD_START", "{", "createBlackholeAllTypesTable ( ) ;", "assertThatQueryReturnsValue ( ( \" INSERT INTO _ all _ types VALUES ( \" + ( ( ( ( ( ( ( ( ( ( ( ( \" ' abc ' , \" + \" BIGINT ' 1 ' , \" ) + \" INTEGER ' 2 ' , \" ) + \" SMALLINT ' 3 ' , \" ) + \" TINYINT ' 4 ' , \" ) + \" REAL ' 5 . 1 ' , \" ) + \" DOUBLE ' 5 . 2 ' , \" ) + \" true , \" ) + \" DATE ' 2 0 1 4 - 0 1 - 0 2 ' , \" ) + \" TIMESTAMP ' 2 0 1 4 - 0 1 - 0 2 1 2 : 1 2 ' , \" ) + \" cast ( ' bar ' as varbinary ) , \" ) + \" DECIMAL ' 3 . 1 4 ' , \" ) + \" DECIMAL ' 1 2 3 4 5 6 7 8 9 0 . 1 2 3 4 5 6 7 8 9 ' ) \" ) ) , 1 L ) ;", "dropBlackholeAllTypesTable ( ) ;", "}", "METHOD_END"], "methodName": ["testInsertAllTypes"], "fileName": "com.facebook.presto.plugin.blackhole.TestBlackHoleSmoke"}, {"methodBody": ["METHOD_START", "{", "createBlackholeAllTypesTable ( ) ;", "MaterializedResult rows = queryRunner . execute ( \" SELECT * FROM _ all _ types \" ) ;", "assertEquals ( rows . getRowCount ( ) , 1 ) ;", "MaterializedRow row = Iterables . getOnlyElement ( rows ) ;", "assertEquals ( row . getFieldCount ( ) , 1 3 ) ;", "assertEquals ( row . getField ( 0 ) , \" * * * * * * * * * * \" ) ;", "assertEquals ( row . getField ( 1 ) , 0 L ) ;", "assertEquals ( row . getField ( 2 ) , 0 ) ;", "assertEquals ( row . getField ( 3 ) , ( ( short ) ( 0 ) ) ) ;", "assertEquals ( row . getField ( 4 ) , ( ( byte ) ( 0 ) ) ) ;", "assertEquals ( row . getField ( 5 ) , 0 . 0 F ) ;", "assertEquals ( row . getField ( 6 ) , 0 . 0 ) ;", "assertEquals ( row . getField ( 7 ) , false ) ;", "assertEquals ( row . getField ( 8 ) , LocalDate . ofEpochDay ( 0 ) ) ;", "assertEquals ( row . getField ( 9 ) , LocalDateTime . of ( 1 9 7 0 , 1 , 1 , 0 , 0 , 0 ) ) ;", "assertEquals ( row . getField ( 1 0 ) , \" * * * * * * * * * * * * * * * * \" . getBytes ( ) ) ;", "assertEquals ( row . getField ( 1 1 ) , new BigDecimal ( \" 0 . 0 0 \" ) ) ;", "assertEquals ( row . getField ( 1 2 ) , new BigDecimal ( \" 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 . 0 0 0 0 0 0 0 0 0 0 \" ) ) ;", "dropBlackholeAllTypesTable ( ) ;", "}", "METHOD_END"], "methodName": ["testSelectAllTypes"], "fileName": "com.facebook.presto.plugin.blackhole.TestBlackHoleSmoke"}, {"methodBody": ["METHOD_START", "{", "createBlackholeAllTypesTable ( ) ;", "MaterializedResult rows = queryRunner . execute ( \" SELECT * FROM _ all _ types where _ bigint > 1 0 \" ) ;", "assertEquals ( rows . getRowCount ( ) , 0 ) ;", "dropBlackholeAllTypesTable ( ) ;", "}", "METHOD_END"], "methodName": ["testSelectWithUnenforcedConstraint"], "fileName": "com.facebook.presto.plugin.blackhole.TestBlackHoleSmoke"}] |
{"Reviews": [{"Author": "Alex O.", "ReviewID": "bbdopfgKhJtdqlPDPiK8UQ", "Overall": "5.0", "Content": "Chef Hugo is awesome. We ate: La Rana - very good just because of the way they prepare it at your table. El Paraguas is very good. Fish tacos were good as well. Chef did prepare for us an out of this world ceviche (have 2 pictures here). I do recommend it ...but it is not on the menu.Backyard needs more light at night. Ha, the backyard is a mess!!!, I like it anyway.", "Date": "2014-07-02", "Author_Location": "New York, NY"}, {"Author": "Alex M.", "ReviewID": "Us8fmr8bHxecC2p6Y6DkPA", "Overall": "5.0", "Content": "Unbelievably good upscale mexican food. My tastes with mexican food tend to run towards the cheap n' nasty side, and I'm always a little more than suspicious when a place tries to take something simple (carnitas tacos for example) and fancy them up. That said, this place totally, 100%, unbelievably delivers on the the premise. The tortillas alone are incredible and unlike anything I've had. The rice and beans were phenomenal. The best dish we had was a sort of motza ball soup which had a tortilla ball filled with bacon in the middle of a saucer, over which was poured a steak soup that had been simmered for hours in a mason jar. Just unbelievable. The drinks were fantastic too. The have a great back garden where they screen old mexican films and hollywood blockbusters in the evening. Great for dates, will definitely go again.", "Date": "2014-07-06", "Author_Location": "New York, NY"}, {"Author": "Ludovic L.", "ReviewID": "LboQhbLEiZRBMY1uTEqBMQ", "Overall": "4.0", "Content": "Not an average Mexican for sure. Pretty sophisticated menu, anything we tasted over a few visits was great and tasty, especially the appetizers. I recommend \"la rana\" (guacomole) for a start with some typical Mexican cocktail.... Amazing!", "Date": "2014-05-18", "Author_Location": "Carroll Gardens, NY"}, {"Author": "docewa d.", "ReviewID": "6ru0Tf21N5zZVQ5XzFAHlQ", "Overall": "5.0", "Content": "Having lived in California and Phoenix, and always seeking out Mexican food, this is some of my favorite in all of New York. It's so fresh, and is just like what you could get at a nice restaurant in Mexico. They grow some of their own veggies in the backyard, the drinks and juices are great and it's good for dinner or brunch. One of my favorites anywhere.", "Date": "2014-06-19", "Author_Location": "Manhattan, NY"}, {"Author": "Uncle B.", "ReviewID": "GnfF3bj8Xn_xcHv3xJqTbg", "Overall": "5.0", "Content": "This is not a standard Mexican place with mediocre food. \u00a0The quality of the dishes are exceptional with a homemade quality down to the tortillas and chips. \u00a0 As a result there is a very different vibe that I think is great - very different than a traditional NYC Mexican restaurant.", "Date": "2014-06-22", "Author_Location": "Brooklyn, NY"}, {"Author": "Ty N.", "ReviewID": "4aqxCcDP1YM8Hukz5oSSLg", "Overall": "2.0", "Content": "Ordered some grilled tacos, got them fried instead. Small portions, high prices. They go mostly for style, you will leave hungry and unsatisfied.", "Date": "2014-05-03", "Author_Location": "Rochester, NY"}, {"Author": "Greg F.", "ReviewID": "jki6Wf2xDqyM0KECthTEkQ", "Overall": "5.0", "Content": "Best brunch I have had in years. The margarita was creative and tasted like sunshine. I had El Borracho (chilaquiles, egg, salsa, sour cream, avocado, black beans) with duck, and enjoyed every morsel.", "Date": "2014-04-21", "Author_Location": "Huntington, NY"}, {"Author": "Ajay R.", "ReviewID": "5NdXyNo-Wt1OzxnQgdrjjw", "Overall": "5.0", "Content": "5 star upgrade considered and granted. \u00a0After a few more visits to this place I'm convinced, not only is it the most unique Mexican food around... but it's one of the best bunch places in the area as well.I always have to laugh at the staff... super nice guys, but always sleepy looking, like they just rolled out of bed. \u00a0I have this vision of Chef Hugo driving around Williamsburg in a white van and clubbing hipsters over the head and abducting them, forcing them to work in his restaurant when they wake up. \u00a0They are all great though... I'm not complaining about the service at all.Onto the food:1. \u00a0The charred habanero hot sauce is amazing. \u00a0It's _actually_ hot, and adds great flavor to everything.2. \u00a0Fish tacos, win.3. \u00a0The presentation, beautiful.4. \u00a0The price, unbeatable value for money at this place.Hugo knows his food. \u00a0Best. \u00a0Brunch. \u00a0Period.", "Date": "2013-12-01", "Author_Location": "Brooklyn, NY"}, {"Author": "luvsbklyn k.", "ReviewID": "CQSLGvq9si2F3lnFoAte7g", "Overall": "4.0", "Content": "Fantastic little gem of a place. The mezcal margarita is the perfect foil for any of their super fresh dishes. Make sure to try the homemade tortillas with their selection of sauces.", "Date": "2014-04-12", "Author_Location": "Brooklyn, NY"}, {"Author": "Alyssa E.", "ReviewID": "rIYejGfpcu9FkUc2qJxCBw", "Overall": "5.0", "Content": "I feel like this is the amazing Carroll Gardens brunch spot that I simultaneously want people to know about (because it's so gooood) and selfishly don't want people to know about (because I like being able to just walk in and get a table).Really good food (and lots of it!), moderately priced, and you can tell that they take pride in what they serve. The chef came to our table and asked if we liked our food and we could tell that they don't just make dishes just to push them out of the kitchen.", "Date": "2013-11-14", "Author_Location": "Brooklyn, NY"}, {"Author": "Eric W.", "ReviewID": "GSHmMZyXiKwmYD6zI1Na7w", "Overall": "4.0", "Content": "Margarita & cucumber margarita=5Guacamole w/seafood=4Artsy chips=2.5Duck w/black mole=5Tuna=4.5Corn flan=3Service=5Ambiance=2.5Beware:You will not find burritos as big as your head here. This place is quality over quantity and it's a tad pricey but the food is really good.The duck mole was tender and perfect.... Along with the pickled onion accompaniment, it was one of the best dishes I've had in a while There's nothing horrible about the ambiance but for me it doesn't fit the price tag and food quality.", "Date": "2013-10-18", "Author_Location": "Brooklyn, NY"}, {"Author": "Tania S.", "ReviewID": "Q-i038hHy1uryokbVq-Uyw", "Overall": "5.0", "Content": "Fantastic food! Try the duck.And the Margarita was awesome: not too sweet, just the right strength.", "Date": "2013-11-09", "Author_Location": "Manorville, NY"}, {"Author": "Lauren L.", "ReviewID": "HbKN3mxHXo3yAEHC-IwoyA", "Overall": "5.0", "Content": "I love me some Slowteria. The food and ambiance together make for such a happy experience. It's really the overall spirit of the place - there's so much life and love there. The menu options are such that you can go all out, or keep it more on budget but still fill your belly.Everything I've eaten there has been mad flavorful, creative, and playful. It's nice to see plates coming out of a kitchen where it's clear the chef is having some fun.The service is casual, easy, and charming. The backyard garden is an oasis. You'd never know how close to trains and highways you are, seated among a cleverly hung garden, on homemade furniture. We feel very lucky to have Slowteria so close to home.", "Date": "2013-09-11", "Author_Location": "Brooklyn, NY"}, {"Author": "Michael T.", "ReviewID": "HnkGgYCHz_tNquutE6bf-g", "Overall": "5.0", "Content": "The holy grail of mexican food. I've been driven by blind, stubborn faith to find it because somewhere in my soul's stomach, I KNEW that \"Mexican\" food could actually be this amazing. I fully expect some crazed fan to kill the chef, so you probably ought to eat here. Like now. Fresh, careful, complex, flavorful, joyful, light, and delicious without being fussy. Most incredible (and last) hot sauce your lips will ever touch. House smoked salt. Everything here is hand made, fresh and local whenever possible. They've got a number of agua frescas (light fruit/veggie juice blends), a full bar, local microbrews and even outdoor seating with a greehouse out back where they'll be growing delicious. GO DURING THE WEEK to have any hope of getting a table before midnight. You'll have a slightly more relaxed time of it, as well. Bruch is fantastic, too. I've tried everything on the menu (really) and there are no real weak spots to mention. The gateway drug is El Diablita, a salsa sampler appetizer. Comes with the best hand made tortillas (specially prepared corn flower stained with beet juice) you will ever eat. Vegan-friendly...just ask.Portions are (too) generous and prices are fair (most mains are under $20). Place rules.", "Date": "2013-04-03", "Author_Location": "Montreal, Canada"}, {"Author": "Manoj P.", "ReviewID": "LTu3ctwN_Ly0GB3ApRjYgw", "Overall": "4.0", "Content": "Great little restaurant. \u00a0Went here on a whim (thanks yelp) and we were very pleased. \u00a0The food is delicious and presented very creatively. \u00a0In fact, this may arguably be the best Mexican food I have ever had. \u00a0The chef also dropped by to say hello and talk about the dishes...great touch. \u00a0I'm FAR from a needy customer, but I just had to knock off a star because the waiter was just so inattentive. \u00a0We were one of 3 other couples and he spent the entire time talking to some patrons at the bar about his hair and other nonsense...When I go back, I hope the service is better and that will hopefully bump this review up to 5 stars. \u00a0I highly recommend checking this place out, the food is just awesome!", "Date": "2013-04-08", "Author_Location": "Sunset Park, NY"}, {"Author": "AnnMarie N.", "ReviewID": "IR5dYefSvP9rzpK5vmXdEw", "Overall": "4.0", "Content": "We sat outside, it was pretty crowded back there but not in a bad way :) i was able to sit directly in the sun and receive some much needed tanning time. i thought it may become unbearable at some point but once the food arrived i paid attention to nothing else!!!!We had gone for Brunch Menu, and we will definitely return to experience the regular menu. The server was fantastic and accomodating and the rest of the staff were pleasant as well. A pleasure all around from mood to menu :).", "Date": "2013-08-05", "Author_Location": "Brooklyn, NY"}, {"Author": "tina p.", "ReviewID": "UNs1ZVgwXnt6PAQdMsOHFA", "Overall": "4.0", "Content": "PLEASE NOTE: this place is NOT between garnet and hamilton as the address shows. it's between 9th st. and garnet. i live around the corner so they already get 1 star- but here's the biggest draw... homemade tortillas. now they're not what you would expect, but man are they amazing. usually you'd think it would be a traditional corn small (yet still delicious) tortilla, but these... these are this amazing mix of seeds different types of corn and i have no idea what else. maybe crack?? a little more upscale? yes. a little bit of a twist? yes. a litte bit delicious? YES.anyway... they're huge and if you get them as tacos as I did they will fill you up.the staff is very friendly and accommodating. they grilled my fish instead of pan searing them for a healthier option. the meat was a little fattier than i wanted it to be, but i was happy to overlook it. the rice was a little salty, but cooked a little al dente, which i love. and the black beans were well... black beans.overall a really great meal that hit the spot. i will be returning... often.", "Date": "2013-03-16", "Author_Location": "Brooklyn, NY"}, {"Author": "Bkduc D.", "ReviewID": "IEkr0H73ZFifENYS-d0T1A", "Overall": "3.0", "Content": "I was in the mood for tacos. When i first saw the taco i was disappointed. It did not look like any taco i had ever seen before or what i was mentally prepared to eat for dinner. BUT... after eating it i was a convert. The food was outstanding and we are definitely planning to go back to try more of their dishes. However, there were a few downsides that made us fall short of giving a 4 star rating.... 1. The staff was very nice, welcoming, and attentive but not very knowledgeable about which wines would go well with the food2. The decor did not have continuity and was a bit bizarre even by brooklyn standards. The citronella candles outside had a strong odor which impacted the overall dining experience as did the kung fu movie being projected on the outside wall. I couldn't make the connection between mexican food and kung-fu. 3. The prices were high given given items 1 and 2.", "Date": "2013-10-06", "Author_Location": "Brooklyn, NY"}, {"Author": "BK Wizard S.", "ReviewID": "b8_PFfEhexyC3RwELb6QGw", "Overall": "2.0", "Content": "I'm truthfully not understanding what all the hype is about. I do however admire the amount of care that has gone into opening a restaurant that serves homemade type Mexican meals. I must say though as I've been dining out for decades that there is something very important missing from this picture.It boils down to taste and sophistication when we are looking at meals that are carefully planned and priced as the entrees are in the $23-24 range. For starters I did not at all enjoy the tasteless flour tacos that are overly, overly thick. I ordered fish tacos to start and was unpleasantly surprised by the bulk of the tasteless taco. \u00a0The sauce accompaniments were tasty, yet not enough to take away from the bulky unflavorful taco. Fish tacos made with a bland white fish need more to make your mouth and stomach smile.Next, on to the entree, which was tilapia with pumpkin seed sauce and a veggie-filled empanada. Again the fish, a bland fish with a bland sauce. The empanada arrived as a big brown, almost black burnt one with bland green zucchini inside. I know I should have returned this, but I didn't. I didn't eat the empanada encasing the zucchini because it was burnt, but wouldn't have anyway as it was way, way too thick for my liking.Maybe it's just me, or maybe it was just an off night...but this was a birthday celebration for me and so truthfully...NOT SO MUCH!One more thing. If you're in search of amazing margaritas...perhaps you'll love their creative touch with tamarind. \u00a0I did very much enjoy that at least!", "Date": "2013-06-16", "Author_Location": "Brooklyn, NY"}, {"Author": "christian svanes k.", "ReviewID": "LYi10L6g_ymP1wzgg1ta4g", "Overall": "5.0", "Content": "it's like going on a culinary retreat. absolutely delightful. we've been here four times now, while today was the first visit for brunch. freshly made juices, salads with jicama, guava, chirimoya, thinly rolled cucumber, radish, queso cotija and a raspberry sauce. every traditional dish has been re-examined, reduced to its essentials and then reinvented, resulting in a meal that is playful, surprising and full of joy. really loved it. the huevos rancheros arrived looking like two pancakes, neatly stacked - the textures were amazing, from handmade tortillas and vegetables that each have their own signature. the menu calls the chilaquiles \"el borracho\" - again, a variety of flavors and textures, which transform over time as they interact with the broth and sauces - not unlike a dish that's pleasantly getting more and more drunk (on flavor). there was an inside-out quesadilla with huitlecoche and nopales. it's obvious that chef hugo puts so much care into each dish. the love for the work shines through. you can taste it. our meal ended with a flan brul\u00e9e made from corn, side by side with a coffee flan and a spoonful of cranberries soaked in mezcal. terrific. i'd go back just to eat the warm, handmade tortillas. they are perfect.", "Date": "2014-01-11", "Author_Location": "Brooklyn, NY"}, {"Author": "Chris S.", "ReviewID": "zmmc-Bkgr67JGUR1LdwH5g", "Overall": "5.0", "Content": "I was dragged here by my girlfriend. This place looks cute so my knee jerk reaction is to veto it. I was hungover so couldn't out up much of a fight. Let me tell you I'm so glad that I didn't. This place has amazing food. It's a bit pricey but well worth it. They have this habanero paste that will light your world and mouth on fire. It's truly amazing. The staff are great. They are super attentive and despite what some reviews say reviews very knowledgable. The true gem is the head cook. He typically will come over chat and/or send over a special dish. We have become regulars doth at May not be the case with everyone's visit bit this is such. A great great especially I'm a neighborhood saturated by people commuting to try our restaurants. This place hasn't been fully discovers because it's a bit off the beaten path. Luckily that keeps most of the commuting crowd scared away. The two block adventure from Buttermilk Channel is too harrowing for their taste. All the better if your willing to make the journey. If you are you will be well rewarded with great service, warm environment and mind blowing food.", "Date": "2013-11-24", "Author_Location": "Brooklyn, NY"}, {"Author": "Marta P.", "ReviewID": "qbyLQjqgDD8Po3txOGadUw", "Overall": "5.0", "Content": "This is a place i always want to come back and bring new friends so that they know a new great place. \u00a0It doesn't seem much when you go in, (I was expecting another mexican normal place) \u00a0and then it is a great surprise: The plates are very original and taste excellent - it is very innovative Mexican food, a concept that i hadnt experienced until i came here. The decoration is all hand-made by the owner. You clearly can see how much dedication, love and good taste this man is putting in his new business. Last time i went, he was preparing the terrace for the summer and he was planning to screen movies in the big white wall that surrounds the garden. I went out of my dinner with that great feeling of having discovered an extraordinary place ran by an extraordinary self-made man.", "Date": "2013-06-16", "Author_Location": "Manhattan, NY"}, {"Author": "Michael B.", "ReviewID": "G99CC3pvjvBbR-3vo3VjGQ", "Overall": "5.0", "Content": "This place is terrific. The food is creative, thoughtful, and most importantly delicious. The setting is warm and welcoming. But what really makes this place stand out is the unmatched service (although calling it 'service' really doesn't do it justice since it is more like walking into your best friend's place who happens to be an amazing chef).I've only been a few times, but the owner and his wife have already begun welcoming me like I'm part of the family. A few personal highlights:- the homemade tortillas are outrageously good- they serve a roasted habanero condiment that's amazing (but watch out)- the pajaro (mexican stew with duck) is one of the best things i may have ever tasted- the back patio/garden is awesome! beautifully landscaped, and the owner has built a bunch of really cool furniture out of salvaged wood- they have Pacifico on tapI absolutely love this place. Amazing addition to the neighborhood!", "Date": "2012-11-30", "Author_Location": "Brooklyn, NY"}, {"Author": "Fadda M.", "ReviewID": "aZWoUsxZBcbg2roKsJAQCA", "Overall": "3.0", "Content": "The people who own, work at, and run this restaurant all seem super nice, and they are obviously putting a huge effort into putting an original, and may I say healthy, spin on Mexican food, in an upscale, Carroll Gardens-y sort of way. \u00a0However, I personally prefer $2.50 tacos in Sunset Park with a bowl of chips and guacamole, and no part of me really craves upscale Mexican food with a twist. \u00a0However, if this is your thing, then you will dig this place.", "Date": "2013-02-25", "Author_Location": "Brooklyn, NY"}, {"Author": "Jackie J.", "ReviewID": "PhBTrMH3gnR-goxtDmshvA", "Overall": "4.0", "Content": "This is a great place where you can go and forget about the climate apocalypse for an hour or two. That is until the chef brings out the complimentary crickets in salt and lime stuff which TOTALLY reminds you of what you will be eating after the climate apocalypse. The waiter was a sport and ate mine for me. Super friendly staff who clearly love food and are very sweet and proud. Amazing food - really worth the trip past ninth street. I definitely recommend the sangria - amazing with big chunks of fruity fruits. Just for dessert I'd recommend crossing the street and going to Treat Truck. They haven't *quite* got the hang of this part of the meal. Everything else was really, really great, though.", "Date": "2012-11-27", "Author_Location": "Brooklyn, NY"}, {"Author": "Bridget O.", "ReviewID": "i-2HdE1B4lH89UHsfj1N6g", "Overall": "5.0", "Content": "I had a delicious fresh brunch here a few months ago. I should really go again.", "Date": "2013-11-27", "Author_Location": "Brooklyn, NY"}, {"Author": "Sascha W.", "ReviewID": "nUtfVtNFEylSiKTTbTsYlA", "Overall": "2.0", "Content": "I REALLY wanted to like Slowteria. \u00a0There are very few great authentic Mexican restaurants in the area. \u00a0Last night I went there for my birthday dinner after hearing very positive reviews. The drinks were wonderful. The presentation was beautiful. The food was a huge disappointment. \u00a0The duck in mole negro was almost inedible. \u00a0The duck breast that was served was 80% fat (not rendered, not crispy...just thick slabs of fat). \u00a0The mole negro was not a real mole negro, it was extremely sweet and thin and oily. \u00a0If you want a delicious authentic mole negro close by (and around the same price point), try Fonda. \u00a0My boyfriend had the fish in pipian verde. \u00a0The tilapia was very dry and overcooked. The rice and beans were very bland as well. The apps were ok. \u00a0Great homemade tortillas. \u00a0When some of the dishes arrived, they has swapped out ingredients or changed preparations from the way it was described in the menu. \u00a0We had the bean dip with cheese and chorizo. \u00a0Instead of chorizo, there was roasted pork. \u00a0It was delicious, but I wish I had known what I was ordering. \u00a0We asked the waiter to describe the guac with seafood. \u00a0He said that the seafood was grilled, but when it arrived it was just lightly cured in lime juice. \u00a0All of that is fine, I just wish we knew what we were getting in advance. \u00a0The server was a sweet guy, but never asked i we enjoyed our meal and could have been more knowledgeable about the menu. Maybe the chef was out of town this week. \u00a0Maybe it was just an off night. \u00a0Overall, I think the restaurant has a great menu and concept, the food is just really not executed well.", "Date": "2013-12-29", "Author_Location": "Brooklyn, NY"}, {"Author": "Blissful L.", "ReviewID": "OaHSdHECWt_K6rlvr8QZig", "Overall": "5.0", "Content": "La Slowteria is by far, my new favorite restaurant in Brooklyn. It's my go-to place for non pretentious, yet fine Mexican food. My husband and I have had both dinner and brunch here (several times actually) and have yet to be disappointed. We've made a point to try something new every time and everything has been delicious!!I planned a birthday brunch gathering in their back yard recently and the entire staff couldn't have been more accommodating. Everything from pre-ordering drinks/apps to the food and service on the day of ran super smoothly. My guests and I had a great time and left the place thoroughly satisfied!!Chef Hugo is truly a master at his craft. The atmosphere and decor is incredibly charming with it's exposed DIY herb gardens, spice racks, and Mexican nicknacks. And his commitment to slow, natural food, and composting is another added plus! If you can't already tell, we totally love this place!", "Date": "2013-06-08", "Author_Location": "Brooklyn, NY"}, {"Author": "Victoria P.", "ReviewID": "DLFTRSF4r1nW0460GOzkZw", "Overall": "3.0", "Content": "Drinks were yummy (I had the sangria and my boyfriend had a margarita), but the food was just okay. The only thing we really enjoyed was the guacamole (add in the habanero paste - it is delicious!) I had the fish tacos and my boyfriend had the house special (pulled pork taco). Overall, it wasn't bad, but nothing spectacular.", "Date": "2013-10-06", "Author_Location": "Boston, MA"}, {"Author": "Majo T.", "ReviewID": "iZKYludDi9YkyZW-GM1w0g", "Overall": "5.0", "Content": "Food so good it makes your eyes roll to the back of your head and forces you to answer in grunts and moans when the staff stops by to ask how you are doing. That's what you're in for here.Dinner and brunch, once each with the boyfriend. We got different things to make sure we got to try more dishes and we loved it all.Forget what you know or you think you about Mexican food. If you care not only about the taste of food but also about texture, you're in for a treat. Every single bit is treat with subtly different flavors and textures.I wanted to lick my plate. I wish I had.Also, it worries me that the chicharr\u00f3n gorditas were a special. Will they be there again next time I go for brunch? Will I ever be able to have them again? I don't know, and that makes me sad, but overall I'm just glad to have food this good so close by.", "Date": "2012-09-30", "Author_Location": "Brooklyn, NY"}, {"Author": "Dani H.", "ReviewID": "_6aRGD0eejI1QNvxVsafSQ", "Overall": "4.0", "Content": "Great atmosphere, the service was awesome. \u00a0Definitely try their tacos, their tortillas were like nothing I have ever tried before. \u00a0I loved the guacamole, especially with the homemade habanero sauce. \u00a0The chef came out and saw that I inhaled all of my habanero sauce, he sent more to the table and he also sent me home with a small container that I have been putting on everything.", "Date": "2013-09-18", "Author_Location": "Manhattan, NY"}, {"Author": "Tom S.", "ReviewID": "8e2AwdokvGPNVYCPTJur1g", "Overall": "4.0", "Content": "A true original. This place is not Tex Mex - it is authentic, with an interesting and inventive menu. The chef/owner is very congenial and welcoming, and deserves much applause and recognition for his efforts to bring something a little different to Carroll Garden / Cobble Hill's Mexican scene.(I'm deducting a star only because I'm an old geezer and for me the music was a tad too loud and the decor a little confused.)", "Date": "2013-11-26", "Author_Location": "Brooklyn, NY"}, {"Author": "B. M.", "ReviewID": "mmLboV5dqCsZxGcIjvVO6g", "Overall": "5.0", "Content": "Excellent gourmet Mexican at a very reasonable price for the quality, lovely drinks, personable staff, chef and owner. \u00a0 And a nice brunch as well. It felt a lot like eating near a beach-side Yucatan luxury resort. \u00a0Top notch.", "Date": "2013-11-21", "Author_Location": "Brooklyn, NY"}, {"Author": "Brian T.", "ReviewID": "nCba24PSHV38bvVHH3QBzw", "Overall": "3.0", "Content": "Decent enough food, but it's hotter than south-central Hell in this place. The plethora of candles doesn't help matters. Feels like Mexico in July. Maybe it's a theme joint.", "Date": "2013-08-19", "Author_Location": "Brooklyn, NY"}, {"Author": "Michael M.", "ReviewID": "07lZFZ3IYCJv2eLZ2M558w", "Overall": "4.0", "Content": "Wonderfully friendly staff, and as another reviewer put it; SERIOUSLY TASTY!! Expect flavorful and healthy (as in not obese) portions. Perfectly provocative for a date.The space was light and intimate, sort of how your kitchen at home would feel.", "Date": "2012-11-18", "Author_Location": "ASTORIA, NY"}, {"Author": "Ryan D.", "ReviewID": "BrpoU4D3kSTPosfqhIS3cw", "Overall": "5.0", "Content": "Full Disclosure: I'm a regular. This has quickly become my go-to spot for both upbeat and relaxing dining. At all hours, La Slowteria is one-of-a-kind, and each time I've gone I've received not only the warmest welcome but some of the best, cared-for food I've ever eaten. Chef Hugo is warm and personable, and he comes out of the kitchen to ask his guests how they're doing, how they like the food and his vibe is one of the warmest I've ever encountered in NYC. Ordinarily, a warm-hearted pleasant chef is only part of the equation, and were it not for each dish's carefully curated charm and flair, this restaurant might come up wanting. And yet, it doesn't. La Slowteria exceeds its own charm with great dishes night after night. \u00a0An example: tonight I went in and ordered steak & bacon tacos. I received 2 of the largest tacos I've ever seen. Before that arrived, Hugo sent me an appetizer. I've been here a lot, and yet I'm always surprised. Hugo is a true scientist when it comes to food, and you can see his impassioned flair in each dish. He often surprises guests with mezcal-soaked cherries as a digestif which are a total delight. The staff is witty and quick with a helpful recommendation. It's often rare to find a crew that gels so wonderfully in a restaurant, and yet everyone working here seems to really enjoy what they're doing, quite a refreshing shift from many other succulent dining experiences.", "Date": "2013-08-08", "Author_Location": "Brooklyn, NY"}, {"Author": "Allison H.", "ReviewID": "ZioYzkY9yuiTnJK3p2l8jg", "Overall": "5.0", "Content": "I had dinner here last night with some friends. The food was delicious, fresh and inventive. I keep hearing that NYC doesn't have good Mexican restaurants and I admit that I don't know enough about real Mexican cuisine, but I thought this place was fantastic.We had an appetizer plate called La Chalupa that was really, really good. It was broiled shrimp and scallops with pico de gallo and guacamole with some crispy corn tortillas. It came with two sauces on the side: spicy and flaming hot. \u00a0The wine list is small but thoughtful. I had a really nice Mexican rose wine. The entrees we had were all really delicious. The food is a modern take on traditional Mexican food, and the presentation is also very nice. \u00a0I had La Musico, which is kind of a surf and turf -shrimp, steak and bacon -with sauteed vegetables. The only thing I would change is the hibiscus reduction on the vegetables: I didn't really taste it, so maybe there needs to be more on the plate. My husband had the deconstructed mole with pulled duck -so good!The owners are very nice and professional. It's a good addition to the neighborhood and I hope it does well!", "Date": "2012-10-01", "Author_Location": "Brooklyn, NY"}, {"Author": "Steve B.", "ReviewID": "FOr7HkVjR44WkF_ZkR3pdA", "Overall": "4.0", "Content": "Amazing. Just amazing.", "Date": "2013-07-17", "Author_Location": "Brooklyn, NY"}, {"Author": "M P.", "ReviewID": "QsPIor6pOs1xQuS_zrHdOg", "Overall": "2.0", "Content": "I had high hopes for this place considering the decor and margaritas. However, the food was overly ambitious and just not good. We ordered 4 appetizers since everything sounded delicious. The guacamole was just ok, the seafood appetizer had too many flavors and this popcorn-black bean tortilla was just good. We got a salad with steak which was horrible. The steak was pure fat. I think there were 2 edible bites in the whole thing. Mexican food has such strong flavors that you need to keep it simple- not throw sauce on everything just to do it.", "Date": "2013-08-17", "Author_Location": "Boerum Hill, Brooklyn, NY"}, {"Author": "Carey F.", "ReviewID": "ZeYH90qK0qu2PAZDEr9M4A", "Overall": "3.0", "Content": "Overall, not bad. \u00a0The food is delicious. \u00a0The service is erratic. \u00a0They are prompt with the drinks. \u00a0No water unless you continually ask. \u00a0One of our party was served the wrong entree, which the server admitted was her fault. \u00a0But they were very fast at correcting the problem, and comping us a drink. \u00a0The bartender is exceptional. \u00a0Worth his weight in gold. \u00a0Overall a three...but it won't take much to be a four+.", "Date": "2013-08-13", "Author_Location": "Sheboygan, WI"}, {"Author": "lisa k.", "ReviewID": "3m8_P8nnGniIAsVF9mSLjw", "Overall": "5.0", "Content": "This place is a gem...I plan on being a regular....and I hope for them, but not for me, that many people discover it.I'll leave it to other reviewers to get specific. \u00a0Regarding comments on dishes that don't work, or are too de-constructed.... I have loved all my dishes (except for the complementary grasshoppers!) \u00a0And if I do try something that I am not crazy about, I will return again and again for what I know works so well.In addition to the tastiness of the food, if you watch the chef he is clearly puts his heart into what he is preparing...I imagine this makes it even more delicious.", "Date": "2012-12-01", "Author_Location": "Brooklyn, NY"}, {"Author": "S. M. S.", "ReviewID": "qynIL6NKN3ssVc1sKYQiCw", "Overall": "1.0", "Content": "I've had better fish tacos at Panda Express and would rather eat at the Taco Bell in Penn Station than return here.", "Date": "2013-04-08", "Author_Location": "Boston, MA"}, {"Author": "Dan S.", "ReviewID": "d49rc0MKZhkO2zU261I7cA", "Overall": "5.0", "Content": "Firstly, I want to say that I love food! I love shopping for it, cooking it, eating it, and even cleaning up when it's all over. When my wife and I eat at La Slowteria, I get the feeling that they feel the same way about food as I do. Hugo and Stephanie are lovely, warm, welcoming and make us feel like a part of their family. The staff are friendly, relaxed, charming and we never feel \"waited on\", just taken care of. Honestly, dinner there feels like we just stopped by our best friends' house for a visit, and accidently showed up in the middle of an amazing three course dinner.It's difficult for me to describe the food at La Slowteria, because I have nothing to compare it to. It is definitely NOT like any Mexican food that I have eaten before. Hugo makes interesting, fresh, dishes which contain strange and delicious combinations of flavors and spices that just make us crazy!!! His Habanero sauce is addictive, and his home made, corn tortillas alone are worth the trip to lower Court St.Last night, my wife and I were treated to the nightly special, a green tomato based soup with beans, bacon, beef, fresh cilantro, onions and a lime wedge to squeeze into the bowl. It's the kind of thing that I could go back for day after day! Warm and satisfying comfort food that never feels heavy or over done. We tried to go there twice with our small daughters, but decided that this place was best kept to ourselves. We now use La Slowteria as the perfect excuse to splurge on a babysitter. We are real home bodies, but La Slowteria gets our tired, old butts out of the house, and into a little beach side restaurant on the coast of Mexico, where we can relax and indulge, get away from the pressures of city life, and enjoy good food, cooked with thoughtfulness and passion, that makes us talk about our next visit, even as we are walking out the door. Buen provecho!!!", "Date": "2012-11-16", "Author_Location": "Brooklyn, NY"}, {"Author": "Brian S.", "ReviewID": "Kj1evRaYyPB4q1BfRcLW0A", "Overall": "4.0", "Content": "Great food as many others have accurately described. Our only issue is that we sat down at 7:15 before the 8pm rush. We still took 2 hours to get through our meal...will go back for great food for sure.", "Date": "2013-04-12", "Author_Location": "Brooklyn, NY"}, {"Author": "Timm C.", "ReviewID": "4U3CZYronxxwQxEmsSpORA", "Overall": "5.0", "Content": "Upping the ante here and adding the elusive 5th pointy, geometric shape to their rating.My wife and I went back last night (yes, because the food is that good) and brought my brother in-law along with his wife. \u00a0Magically the \"El Diablito\" came with tiny spoons and the portions were much bigger, not to mention that the layout was way easier to navigate. \u00a0Cheers not only on the upgrades but for taking the time to listen to reviews, speaks volumes of the management. \u00a0Also, and this is something i think all the reviewers overlooked, that dish is only $6!!! \u00a0Staying in the app department we also shared the scallops which were killer and the seafood guac, no plate went un-licked, really well done all around and again it was creative and a very new kind of delicious.For main dishes my bro-in-law got the stew and loved it. \u00a0His wife got the shrimp which she shared a bit of and it was just as excellent as the other dishes (my wife and I got the same thing as last time).We have not tried the desert yet, but I would assume good things.So, they have reached 5 stars in my humble opinion BUT I still stand by my other two suggestions and the reason being that I think it would help them generate more business. \u00a0You are going to get a lot more repeat and frequent customers who can come in and get some excellent tacos, guac, beer and tequila especially with more than a quarter of the seating residing at the bar. \u00a0Take Mesa Coyoacan for example, they have all the staples along side delicious more creative/fancy dishes. \u00a0I just think that as good as the food is at Slowteria people will come back and back and back for what they know and there is less of a chance of lines out the door for their more complex dishes regardless of how good they are.Regardless, if you are contemplating trying this place, just go, there is no way you will not be seriously impressed.", "Date": "2012-09-20", "Author_Location": "Brooklyn, NY"}, {"Author": "Graceann D.", "ReviewID": "sJ7XN09uLGaH_QeF4wyf8w", "Overall": "4.0", "Content": "Update: Since I posted this review earlier today, the owner contacted me, which I very much appreciated. Like I said below, the staff are very friendly and they want to give you a great experience in their restaurant. To be fair, my coffee/price issues aside, I would try this place again, maybe for dinner since I already had brunch there and it seems dinner has received good reviews. The food was good and the environment was very warm and friendly. I really hope they succeed, since it's clear they value their customers. (Why am I even on Yelp at 11:40pm on a Friday night? Because I can't sleep knowing that I gave a bad review to people who are genuinely nice and deserve better than my pre-lunch hunger-fueled negative review. Oh, and a lifetime of Catholic-infused guilt.)Like so many earnest new restaurants, they try. They really try. And like my husband who tries to make the bed or put away the dishes..... it's a sweet gesture, but oh, look at you! You have thumbs and you're trying to use them. Like people! As my mom would say, god love 'em.Anyway, I came here for brunch a few weeks with a group of 6. I wanted to see if the new occupiers of the old Dubuque space would do them any justice. Nope. Food was good, not great. I would go back there again IF they didn't supremely annoy me with the fact that there are neither prices nor basic descriptions on the brunch menu. And THEY CHARGE FOR COFFEE BY THE CUP and nowhere on the menu do they indicate that. In fact, my friend asked the waitress (who I think might also have been the owner perhaps) \"Is this fancy coffee?\". Any person with a niblet-sized amount of social skills would interpret this is as \"Did you have to use an espresso machine or anything other than a regular drip machine to make this coffee and therefore it would be charged per cup?\". She said no, it was regular coffee. And when other wait staff came around to ask if we wanted more coffee, they never said, Oh by the way, that's going to be $2.50 for another cup of coffee. Between the 6 of us, we had about 12 or 13 cups of coffee. When we got the bill we were dumbfounded. And for some weird reason, we had three of those coffees comped. Maybe because they realized how stupid it is to charge by the cup and not tell their patrons? But not quite stupid enough to comp all but the first six cups? At that point I didn't really care that my huevos rancheros was actually pretty decent, a lot better than most places that end up making dog breakfasts out of it.I don't want to give this place two stars. I wish I could give it five, since everyone was very friendly and they clearly were trying to give us a great experience. But come ON! List your brunch prices, make it clear that you charge per cup, and give us a description beyond \"tacos\". Because I can imagine a lot of different tacos.", "Date": "2012-10-12", "Author_Location": "Brooklyn, NY"}, {"Author": "Garrett J.", "ReviewID": "jdSpMuq0s7UVjCOpt1aYuw", "Overall": "5.0", "Content": "This is my new favorite spot to eat out in NY. \u00a0Once we went for brunch and dinner in the same weekend. \u00a0I think my favorite so far (besides the amazing home made tortillas) is the Mexican steak (and I'm not a steak person at all!). \u00a0Very unique experience, as a Californian stuck in New York this place makes me very happy. \u00a0Mexican food is not just taco trucks or \"nachos with boneless wings\". \u00a0This place is very cool...", "Date": "2013-06-08", "Author_Location": "Brooklyn, NY"}, {"Author": "Rich B.", "ReviewID": "O67gReTSzoZSInlSd_0AuA", "Overall": "4.0", "Content": "I'm happy to have a new mexican restaurant in this neighborhood that hasn't really ever had a decent sit-down mexican spot. The chef is from Tulum, a little town that my wife and I have a sweet spot for (my little photo icon thing is from a trip to Tulum). He seems like a lovely fellow and their staff are all nice and friendly. That said, I totally want to love this place and heck, I gave it four stars, because I sincerely hope that things gel a bit better. A few quirks.- The drunken duck sandwich.This is a sandwich in a soup bowl. The duck was great, but the size of the bread for the sandwich part was super big. And because it was in a pool of broth, it was super soggy. Maybe I'm missing something here. It seemed like a waste of a nice piece of bread.- The deconstructed mole & duckI'm not sure I get this either. The whole awesomeness of any sauce is all the time it spends marrying the flavors together and making that whole magic. Breaking it in to the parts and then forcing the diner to somehow try to very unsuccessfully recreate the sauce... I don't get it. Duck with a mole sauce should have been a home run.- The shrimp & steak skewers dishInteresting presentation, but since this was all done on the skewers, everything is basically blackened - so, visually, not much happening here. Some guessing when biting into things. The shrimp and steak weren't especially flavorful. Maybe I'm missing something.What else..?Wine list - fun selections from Long Island and Mexico (yup). Dessert list looked nice, but I was really in the mood for a basic churro with chocolate sauce thing.Like I said, I really want this concept to work. We'll be back to try again.", "Date": "2012-12-01", "Author_Location": "Brooklyn, NY"}, {"Author": "Laura H.", "ReviewID": "Mjmjc1LsYrx70ynFR9IChQ", "Overall": "4.0", "Content": "The owner contacted me via Yelp to explain that the chewy steak was the result of not being able to get steak from their usual source due to Hurricane Sandy. Totally understandable, so I updated to a 4-star rating. Also sounds like they might be getting a liquor license soon. Looking forward to returning!", "Date": "2012-11-04", "Author_Location": "Brooklyn, NY"}, {"Author": "Joram S.", "ReviewID": "GS-JW6H4XG8gKXBsl-6wmg", "Overall": "3.0", "Content": "A caveat: someone else might very well love this place, but it wasn't for me.The service was super friendly, and the food was quite good, but I simply dislike the kind of \"fine-dining\" experience where every meal arrives \"deconstructed\" into an vast array of tiny meat morsels and squiggly smears of sauce. \u00a0I can understand that the chef would like to present something different than the giant swamp of refried beans that usually passes for Mexican food here in the city, but any way you slice it a certain heartiness is central to Latin American cuisine. \u00a0Once you get past the razzle-dazzle of the plating, you're left with the realization that you've paid 20 bucks for an entree that is essentially 5 shrimp and a pineapple slice. \u00a0My wife and I not only left hungry, but after what we spent, feeling a bit cheated. \u00a0If the talented kitchen would concentrate less on presenting 15 unique elements per plate and focused instead on delivering the sumptuous, flavorful and comforting dinner they are capable of, this place would be a real winner. \u00a0Until then, I don't think I will be back.", "Date": "2012-11-10", "Author_Location": "Brooklyn, NY"}, {"Author": "Regina R.", "ReviewID": "40ZKY0SSDtyDwvfk63K3iw", "Overall": "1.0", "Content": "overpriced margaritas, obnoxious folks behind the bar, weird thrown together look and random decor. the rice and beans had NO taste and our guacamole came in something no bigger than a shot glass. music variety could use improvement and to be turned down.the waitress got the one star for the place, she was lovely.", "Date": "2013-05-05", "Author_Location": "Brooklyn, NY"}, {"Author": "colter m.", "ReviewID": "IH82FgOqPv_FwQORGvsgWw", "Overall": "5.0", "Content": "Delicious, friendly, and unpretentious. I've eaten here twice now and everything has been so good I've wanted to slap myself. As a novice foodie I've found myself unimpressed by restaurants that everyone else drools over - clearly I know nothing about high-falutin' cuisine, but Slowteria was my first near-religious food experience that made me understand what a great meal can be.", "Date": "2012-09-30", "Author_Location": "Brooklyn, NY"}, {"Author": "Mary K.", "ReviewID": "M-CT13v2DNTlbvqILSEuQg", "Overall": "3.0", "Content": "This place has great intentions! As for the execution, though, I am on the fence. The heart of the business is providing authentic, good Mexican fare in a slow food style. In practice, I will zero in on the deconstructed mole dish as an example of where it can go wrong. The dish centers around some duck mole (the sauce is thick and a bit gloopy), a dish of rice and pickled onions (?), a side of grilled onion and tomato (?), and the deconstruction of the mole sauce on the plate. Now, I've done my share of molecular gastronomy dining and am no stranger to \"deconstructed\" food. But when you put some dried chiles and a hunk of Mexican chocolate on the plate, it's different from other deconstructed dishes (lame example: a deconstructed breakfast sandwich of eggs and bacon and bread all separated out) because...you can't really eat all the components and have them be satisfying in and of themselves, nor can you combine them if you wanted to experiment with \"reconstruction.\" And why two types of onion? And rice? There were, admittedly, delicious tortillas that came with, but they arrived when we were halfway done picking at the plate. And that's what you're forced to do with this presentation: pick. A nibble of chocolate here. Tucking the chile into a tortilla. Ignoring the pickled onion because there's already another onion and there's onion in the sauce. Slow food, to me, is simple and really invites the diner to linger and enjoy something balanced and harmonious. This dish left me scratching my head and a bit unsatisfied. Looking at the menu, I saw other presentation concepts and ingredients that, while authentic, made me think the resulting dishes would be fussy and esoteric. Maybe we just ordered wrong. The proprietors and employees were all super nice, it's right in my neighborhood, and I wish them well. But...and I'm sorry to say this...I just don't know if I'll be back until they get into gear.", "Date": "2012-09-06", "Author_Location": "San Francisco, CA"}, {"Author": "W P.", "ReviewID": "KaiWuL3cAjEaDEa2oTv1zA", "Overall": "5.0", "Content": "I almost never write reviews on Yelp, but I really want to make sure this place makes it and continues to put out such great, modern Mexican food! \u00a0My wife and I just got back from a long weekend in Mexico City, and this place brings us right back to the \"haute mexican\" food we had there. We were there today for brunch and had the scallop ceviche (fantastic - nice sea scallops, as opposed to the bay scallops you often see in scallop ceviches), the torta, which they make in a kind of \"French Dip\" style and which was FANTASTIC. \u00a0The broth it was soaked in was reallllly good. \u00a0And finally one of those handmade tortillas, fried, with slow roasted pork shoulder, a bit of guacamole, onion relish, cilantro, cabbage and radish. \u00a0It was tied together with a tomato-habanero broth which was just spicy enough.We just had coffee today, but they apparently got their liquor license recently so in addition to the fresh juices they now apparently have margaritas. \u00a0Oh and flambee mango with mezcal soaked cranberries and some sort of ice cream I believe was the dessert special - I wish we had room and that it wasn't 1pm.The few times we've been for dinner Chef Hugo hasn't disappointed either, but I'll leave that for a follow up review.", "Date": "2013-04-06", "Author_Location": "Brooklyn, NY"}, {"Author": "Rich Z.", "ReviewID": "XMGffQRz1_ynDw5zbu8N-Q", "Overall": "5.0", "Content": "Amazing neighborhood restaurant. \u00a0Food is great and menu is daring. \u00a0We had a bottle of wine which was great and reasonably priced. They played a great eclectic selection of music and the small space was decorated beautifully. \u00a0I left feeling as though I was on a Mexican culinary adventure, as every dish is exquisitely planned and unique.", "Date": "2013-01-20", "Author_Location": "Brooklyn, NY"}, {"Author": "Jenny C.", "ReviewID": "T4fLiTzP4ohXSwNsX2RLyA", "Overall": "5.0", "Content": "I absolutely love this place.We were outside checking the menu when the waiter came out to give us a run down of their specials.We picked up a friend nearby and the three of us ordered some of the most delicious brunch food plus one seafood soup we have ever had.After stuffing our faces with fresh delicious food we asked for our bill and were shocked that we were only paying $50 for 5 plates of food.This is definitely going to be our new brunch spot even though we live in bay ridge.", "Date": "2013-01-02", "Author_Location": "Brooklyn, NY"}, {"Author": "Lynn Y.", "ReviewID": "Eyi6of4e9zrMxPsWlH2BfA", "Overall": "4.0", "Content": "delicious! \u00a0friendly, cozy atmosphere. excellent food. \u00a0dinner menu might be a bit pricey, but if you don't like it, then brunch is for you! \u00a0The chef is very friendly and eager to please -- they have notes on the menu that they are happy to accommodate substitutions and kids' menu. \u00a0I would definitely go back.", "Date": "2013-03-30", "Author_Location": "Brooklyn, NY"}, {"Author": "Anna S.", "ReviewID": "ImAi7VnaGy8N8kzEd99VEw", "Overall": "5.0", "Content": "I took my husband here for his birthday on Friday and we agreed this is our new favorite restaurant and intend to come back again and again. When we arrived we told the wait staff we were vegan and they offered to either make anything on the menu vegan, or to have the chef make us something else altogether. The chef came to our table and suggested sending out a variety of small dishes until we were full and told him to stop. Every single bit of food on our plates tasted very special and authentic. My husband is a trained chef and as you can imagine, we are challenged when dining out to find food that accommodates our dietary restrictions while being fresh, healthy, \u00a0well prepared, interesting and delicious (we've suffered through a LOT of salads and french fries...). We were so appreciative of them going above and preparing us a wonderful dinner. They even gave our son a few Mexican wrestler toys to play with while we were there - nice touch!", "Date": "2012-10-08", "Author_Location": "Brooklyn, NY"}, {"Author": "A S.", "ReviewID": "SDvPPacBI0HgLgkK-0-Jcw", "Overall": "5.0", "Content": "Great date restaurant. La Slowteria is a really cute spot and the food was amazing! We started with an excellent Mexican wine, then had a scallop dish for an appetizer called La Mano - so good. I got the tuna steak and the bf got steak, both were delicious. We'll definitely be back!", "Date": "2012-09-08", "Author_Location": "Fort Greene, Brooklyn, NY"}, {"Author": "Paul T.", "ReviewID": "FpZA8ddmUXBsBI1A8g_JMA", "Overall": "5.0", "Content": "Been here 4 or 5 times and the fact is nobody is doing food like Chef Hugo is putting out here. Absolutely sublime flavors coming out of that kitchen. The mescal margarita was also amazing and a nice complex addition to the phenomenal array of flavors found in the dishes. Great vibe...solid service. Glad I'm across the street and wish I could give it six stars!", "Date": "2013-04-13", "Author_Location": "Brooklyn, NY"}, {"Author": "Stacey S.", "ReviewID": "n2mMKVi1dnKswl2e0ntj-w", "Overall": "1.0", "Content": "La Slowteria needs to get real. I went on a Saturday night with group of pals. The service was good, but the food? Odd to say the least. I understand the idea behind authentic Mexican cuisine. I really do. But I don't get this place. It's not quite right. I ordered a dish that they brought out in a steamy hot Mason jar and poured it into a bowl that was delivered to the table first. The jar contained slow-cooked steak and tomatillo broth. The lumps of meat pouring from a hot jar wrapped in a kitchen towel was not very appealing. I am not a stuffy closed-minded food person. I say bring on the rustic and the home spun. NY needs more of it! \u00a0But it was THE oddest food presentation I have ever experienced. While pouring the broth, the chef also splashed me with it. Not fun and kinda awkward for both of us. The slow-cooked steak was the most horribly tough and gristly beef I have ever tasted while dining out. If the fatty and tougher cut of meat was selected to enhance the flavor aspect of the slow-cooking process, then it needs to be cooked much longer to achieve an edible texture. But the flavor of the beef wasn't anything to rave about anyway. And the tiny amount of steak was disappointing when ordering an entree that includes the word steak. The other main ingredient in this dish were two very hard and dry \"matzo balls\" made from blue corn. After being doused with the hot liquid from the Mason jar, these balls just sat there like hard and slippery lumps that had to be chased down with a fork, or spoon or knife? My partner's pork dish was equally disappointing for different reasons. The slow-cooked pork was so dry and rock hard. The presentation was overly complicated and didn't make sense. Maybe the confusing plate styling was meant to mask the blandness and poor preparation of the dish. I was excited to experience real and interesting Mexican cuisine, but this place lost me. I will not be back.", "Date": "2013-11-18", "Author_Location": "Brooklyn, NY"}, {"Author": "Matthew C.", "ReviewID": "ePLtaMfy0HWvjspUhHiooQ", "Overall": "5.0", "Content": "Everything they have is excellent. Chef Hugo encourages you to try new things all the time.", "Date": "2013-03-05", "Author_Location": "Carroll Gardens, Brooklyn, NY"}, {"Author": "Catherine Z.", "ReviewID": "29CokfosxA_fYqWZbYlPjQ", "Overall": "5.0", "Content": "Finally, some interesting and healthy Mexican in the neighborhood! Love the juices too!", "Date": "2013-01-27", "Author_Location": "Carroll Gardens, Brooklyn, NY"}, {"Author": "John R.", "ReviewID": "jmkxzYkvsZ3L2p2NzzOdkg", "Overall": "4.0", "Content": "We had a nice dinner at the space that took over Dubuque this past Thursday, a week after the hurricane. \u00a0We shared a salad with avocado, grilled vegetables, and cheese. \u00a0It was very tasty. \u00a0I had the duck soup which was warm and comforting and the perfect meal for a cold, nasty night following a nor'easter. \u00a0We were the only ones in the restaurant and I hope they pick up some business because the food was genuinely good. \u00a0The only reason this doesn't get a 5 is because everything is about 3-5 dollars overpriced. Unfortunately, that may be keeping people away.", "Date": "2013-01-12", "Author_Location": "Brooklyn, NY"}, {"Author": "Kelly F.", "ReviewID": "EysO9BFBIRjs1OSqIh19fQ", "Overall": "4.0", "Content": "I'm going to miss Dubuque, I won't lie. \u00a0Their truffle burger was one of my favorite things on this planet. \u00a0But I dried my tears at Slowteria the other day and I was not disappointed. \u00a0Perfectly seasoned and thoughtfully prepared Mexican food! \u00a0The homemade, multi-colored, thick, crunchy tortillas will keep you up at night with cravings. \u00a0The portions are small and the prices are high, but maybe the impending liquor license will help regulate their food costs? (hint hint, I'm looking at you owners) \u00a0One tip on presentation, if you are going to do small portion sizes, get smaller plates. \u00a0They bring out a fist-sized meal on a massive, mostly empty plate that makes it look like they gave half your food to someone else. \u00a0Also, the coffee cups and other place settings are conspicuously from IKEA. \u00a0I'm all about frugal startups.... but come on. \u00a0But seriously, try this place. \u00a0What they are doing with the food is a-OK.", "Date": "2012-11-18", "Author_Location": "Brooklyn, NY"}], "RestaurantInfo": {"RestaurantID": "SYf_bgHWy787uTu4z4wMPw", "Name": "La Slowteria", "Price": "$$", "RestaurantURL": "/biz/la-slowteria-brooklyn", "Longitude": " -73.99956808650820", "Address": "548 Court StBrooklyn, NY 11231", "Latitude": " 40.675054752230999", "ImgURL": "//s3-media1.fl.yelpcdn.com/bphoto/ULFkyiiCrPOJ_xWiqllweQ/90s.jpg"}} |
{"poster":"Akilas","date":"2017-06-07T23:33:56.454+0000","title":"Busco un Main Top o Mid para Ranked Flex, nos falta 1","subforum":"Reclutamiento","up_votes":4,"down_votes":0,"body":"Somos 4, y nos falta 1, sea top o mid, preferiblemente top. Si se puede con discord.","replies":[{"poster":"ImCody501","date":"2017-06-08T14:15:18.514+0000","up_votes":1,"down_votes":0,"body":"soy main mid agregame{{champion:103}} {{champion:34}} {{champion:7}} {{champion:55}} {{champion:38}} {{champion:157}} {{champion:238}} {{champion:45}} {{champion:4}} {{champion:134}} ","replies":[]},{"poster":"LG loco Tundrax","date":"2017-06-08T07:22:34.179+0000","up_votes":1,"down_votes":0,"body":"soy main top experto en campeones frontlane y de apoyo AGreguen Tundrax","replies":[]},{"poster":"MaRiin","date":"2017-06-08T00:11:02.400+0000","up_votes":1,"down_votes":0,"body":"soy only top ;) tengo bastante variedad de champs en la linea y nunca la pierdo ;)","replies":[]},{"poster":"shaclone Bot","date":"2017-06-08T00:00:08.303+0000","up_votes":1,"down_votes":0,"body":"hola yo tengo discord y maineo top y jg mi facebook https://www.facebook.com/profile.php?id=100012624493448","replies":[]}]} |
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