id int64 0 549 | review stringlengths 314 12.7k | spans list | labels list |
|---|---|---|---|
0 | This paper describes a state-of-the-art CCG parsing model that decomposes into tagging and dependency scores, and has an efficient A* decoding algorithm.
Interestingly, the paper slightly outperforms Lee et al. (2016)'s more expressive global parsing model, presumably because this factorization makes learning easier. ... | [
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1 | The paper considers a synergistic combination of two non-HMM based speech recognition techniques: CTC and attention-based seq2seq networks. The combination is two-fold: 1. first, similarly to Kim et al. 2016 multitask learning is used to train a model with a joint CTC and seq2seq cost.
2. second (novel contribution), ... | [
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2 | The authors propose ‘morph-fitting’, a method that retrofits any given set of trained word embeddings based on a morphologically-driven objective that (1) pulls inflectional forms of the same word together (as in ‘slow’ and ‘slowing’) and (2) pushes derivational antonyms apart (as in ‘expensive’ and ‘inexpensive’). Wit... | [
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3 | This paper outlines a method to learn sense embeddings from unannotated corpora using a modular sense selection and representation process. The learning is achieved by a message passing scheme between the two modules that is cast as a reinforcement learning problem by the authors.
- Strengths: The paper is generally we... | [
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4 | - Strengths: This is a well written paper.
The paper is very clear for the most part.
The experimental comparisons are very well done.
The experiments are well designed and executed.
The idea of using KD for zero-resource NMT is impressive.
- Weaknesses: There were many sentences in the abstract and in other place... | [
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5 | - Strengths: * Elaborate evaluation data creation and evaluation scheme.
* Range of compared techniques: baseline/simple/complex - Weaknesses: * No in-depth analysis beyond overall evaluation results.
- General Discussion: This paper compares several techniques for robust HPSG parsing.
Since the main contribution o... | [
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7 | This paper presents a corpus of annotated essay revisions. It includes two examples of application for the corpus: 1) Student Revision Behavior Analysis and 2) Automatic Revision Identification The latter is essentially a text classification task using an SVM classifier and a variety of features. The authors state tha... | [
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8 | This paper presents several weakly supervised methods for developing NERs. The methods rely on some form of projection from English into another language. The overall approach is not new and the individual methods proposed are improvements of existing methods. For an ACL paper I would have expected more novel approache... | [
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9 | The paper proposes a model for the Stanford Natural Language Inference (SNLI) dataset, that builds on top of sentence encoding models and the decomposable word level alignment model by Parikh et al. (2016). The proposed improvements include performing decomposable attention on the output of a BiLSTM and feeding the att... | [
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10 | - Strengths: This paper contributes to the field of knowledge base-based question answering (KB-QA), which is to tackle the problem of retrieving results from a structured KB based on a natural language question. KB-QA is an important and challenging task.
The authors clearly identify the contributions and the novelty ... | [
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11 | paper_summary
Since only minor revisions have been made to the paper, my views of the paper have not changed. For details, please see my previous review comments.
The author’s response has answered my previous questions very well and added relevant analysis to the revised draft. In my opinion, the analysis of the negat... | [
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12 | paper_summary
The paper defines a CBMI metric over the NMT source and a target word (given the target history) and then uses it to re-weight the NMT training loss. The definition is simplified to the quotient of NMT probability and the LM probability. Experiments shows that the training strategy improves the translatio... | [
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13 | paper_summary
This paper describes the development of a data set that can be used to develop a system that can generate automated feedback to learners' responses to short-answer questions. The data set includes questions, their answers, and their feedback in the domain of computer networking, mostly in English but wit... | [
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14 | paper_summary
This paper presents a cross-lingual information retrieval approach using knowledge distillation. The underlying model is ColBERT with XLM-R as the pretained language model. The approach makes use of a teacher model based on query translation and monolingual IR in English. The student model is trained with... | [
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15 | paper_summary
The paper investigates methods to automatically generate morally framed arguments (relying on a specific stance, on the given topic focusing on the given morals), and analyses the effect of these arguments on different audiences (namely, as liberals and conservatives).
summary_of_strengths
- The topic of... | [
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17 | paper_summary
This paper is about improving the prosody of neural text-to-speech (NTTS) systems using the surrounding context of a given input text. The study introduced an extension to a well known NTTS system i.e., FastSpeech-2. The extension is a phoneme level conditional VAE. As cited in the current paper both Fast... | [
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18 | paper_summary
This paper proposes a novel refinement method to synchronously refine the previously generated words and generate the next word for language generation models. The authors accomplish this goal with an interesting implementation without introducing additional parameters. Specifically, the authors reuses th... | [
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19 | paper_summary
The paper proposes 6 test corpora for vision and language captioning systems that target specific competency. For each competency, examples are generated semi-automatically from existing language + vision tasks, such QA in V7W, and are created in a FOIL style, where one example correctly describes the ima... | [
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20 | paper_summary
Motivated by empirical findings that training models with Prompt Tuning can achieve the same performance as fully fine-tuning a model, but the training takes much longer to reach the same performance, they explore ways to exploit knowledge from already trained prompts.
They explore using already trained p... | [
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21 | paper_summary
This paper focuses on using bandit learning to learn from user feedback for Extractive QA (EQA), the binary supervisory signals from user feedback serve as rewards pushing QA systems to evolve. The learning algorithm aims to maximise the rewards of all QA examples, which consists of online learning and of... | [
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22 | paper_summary
This paper works on the problem of personalization in knowledge grounded conversation (KGC). To develop a benchmark, the authors collected a new KGC dataset based on Reddit containing personalized information (e.g. user profile and dialogue history). The authors propose a probabilistic model for utterance... | [
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24 | paper_summary
This paper proposes a solution for "Contrastive Conflicts". What exactly are “Contrastive Conflicts”? They occur when multiple questions are derived from a passage, each with different semantics. The questions are going to be close to the passage in representation space and by transitivity they are going ... | [
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26 | paper_summary
The paper presents a novel approach to understanding math problems from their textual formulations. The approach builds on those from related work, choosing syntactic representations. The key novelties are (1) an internal graph representation of the operators and (2) a novel pretraining setting. The model... | [
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29 | paper_summary
See the prior review for a summary. Based upon the author response I do raise my score slightly from 2.5 to 3.0 to reflect that the definitions referenced in the author response might be sufficient for a target audience that is intimately familiar with WSD. On the other hand, it remains open as to what th... | [] | [] |
31 | paper_summary
The paper describes a new approach towards MeSH label prediction, utilizing the title abstract journal relative information. The proposed model combines BiLSTMs, Dilated CNNs and GCNNs to extract features from abstracts, titles and the mesh term hierarchy respectively. Limiting the search MeSH space with ... | [
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34 | paper_summary
The performance of structured prediction models can be greatly improved by scaling to larger state spaces, yet the inference complexity of these models scales poorly w.r.t. the size of the state space. The goal of this work is to reduce the inference complexity of structured models by factorizing the cliq... | [
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37 | paper_summary
In this work, the authors proposed a unified model of task-oriented dialogue understanding and response generation. The two major enhancements are adopting task-oriented dialogue pre-training on a data collection, and introducing the prompt-based learning for the multi-task capability via one model. From ... | [
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38 | paper_summary
The paper studies the benefits of introducing a Bayesian perspective to abstractive summarization. The authors run the MC dropout method on two pre-trained summarization models, sampling different summarization texts according to specific dropout filters. They use BLEUVarN as a metric of uncertainty for a... | [
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39 | paper_summary
This work has created a benchmark dataset for multi-task learning for biomedical datasets. Based on this new benchmark dataset, this work has proposed instruction learning based multi-task learning, which has shown to outperform single-task learning as well as vallina multi-task learning.
summary_of_stre... | [
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41 | paper_summary
This paper propose prefix-based models for controllable text generation. Similar to [1], prefixes are token embeddings of language models (e.g., GPT-2) used for learning attribute-specific information and steering the generation of the fixed language models. The authors further add a contrastive loss to e... | [
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42 | paper_summary
The paper provides a benchmark dataset that can be used for training & evaluation of automated fact checking systems. The major contribution of this paper is that they provide a large collection of 33,697 claims with associated review articles and premise articles. In the experiment, this work presents a ... | [
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43 | paper_summary
*Note: I reviewed this paper in an earlier ARR cycle. There are no changes in the updated version that warrant a change in my score or the review. I’ve updated a summary of weaknesses to reflect the updates, and have listed a few suggestions on grammar.*
This work presents a method (X-GEAR) for zero-shot,... | [
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45 | In the present paper, the authors describe the results of a quantitative analysis of various genres in terms of coreference. They analyse a number of coreference-related features and compare the genres from the point of view of their distribution. The aim is to find the differences between spoken and written genres. Th... | [
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46 | Summary - The paper studies the problem of under-translation common in auto-regressive neural machine translation.
- Two main pieces are introduced in this research work, random noise to the length constraint, output length prediction using BERT.
- The English-Japanese ASPEC dataset is used to evaluate th... | [] | [] |
47 | Overviews: This paper focuses on Abusive Language Detection (ALD) and proposes a generic ALD model MACAS with multi-aspect embeddings for generalised characteristics of several types of ALD tasks across some domains.
Strengths: The motivation of this paper is clear, i.e., to solve the problem that "What would be the be... | [
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48 | This work built a fake news prediction model using both news and user representation from user-generated texts. Experimental results showed that the user text information contributed to predicting the fake. Moreover, the paper showed linguistic analysis to show typical expressions by users in real and fake news. Cosine... | [
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"Eval_pos_3"
] |
49 | In this paper, the authors argue that using the topmost encoder output alone is problematic or suboptimal to neural machine translation. They propose multi-view learning, where the topmost encoding layer is regarded as the primary view and one intermediate encoding layer is used as an auxiliary view. Both views, as enc... | [
[
773,
823
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[
823,
938
],
[
959,
1027
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[
1029,
1260
],
[
1261,
1502
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[
1504,
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],
[
1691,
1755
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[
1757,
2047
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[
2047,
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[
2350,
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[
2437,
2725
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[
2726,
... | [
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"Jus_neg_2",
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"Jus_neg_3",
"Eval_neg_3",
"Eval_neg_4",
"Jus_neg_4",
"Eval_neg_5",
"Jus_neg_5",
"Major_claim"
] |
50 | This paper is about characters in narrative texts, and it claims to contribute a) an operational definition of characters that is „narratologically grounded“, b) an annotated corpus (which will be released) and c) classification experiments on the automatic distinction between characters and non-characters.
This paper ... | [
[
309,
353
],
[
354,
400
],
[
401,
430
],
[
2508,
2542
],
[
2544,
2826
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[
2830,
2946
],
[
2947,
3124
],
[
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[
3413,
3443
],
[
3445,
3540
],
[
3542,
3728
]
] | [
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"Eval_neg_1",
"Jus_neg_1",
"Eval_pos_3",
"Eval_pos_4",
"Eval_neg_3",
"Eval_neg_4"
] |
52 | paper_summary
The paper presents QuALITY, a new benchmark for question answering over long passages. All the questions are multiple-choice, composed by professional writers and validated by MTurk annotators to be answerable and unambiguous. A subset of especially challenging questions is also selected in a task where a... | [
[
617,
685
],
[
690,
747
],
[
750,
857
],
[
931,
964
],
[
966,
1123
],
[
1124,
1178
],
[
1222,
1269
],
[
1275,
1356
],
[
1381,
1516
],
[
1600,
2119
]
] | [
"Jus_pos_1",
"Eval_pos_1",
"Eval_pos_2",
"Eval_pos_3",
"Jus_pos_3",
"Eval_pos_4",
"Eval_pos_5",
"Eval_pos_6",
"Eval_neg_1",
"Jus_neg_1"
] |
53 | This paper presents a comparison of several vector combination techniques on the task of relation classification.
- Strengths: The paper is clearly written and easy to understand.
- Weaknesses: My main complaint about the paper is the significance of its contributions. I believe it might be suitable as a short paper, b... | [
[
127,
179
],
[
194,
357
],
[
358,
469
],
[
470,
771
],
[
904,
1044
],
[
1044,
1120
]
] | [
"Eval_pos_1",
"Major_claim",
"Eval_neg_1",
"Jus_neg_1",
"Eval_pos_1",
"Major_claim"
] |
54 | paper_summary
The paper has not changed materially from the previous version. Please refer to my previous detailed summary. The new version addresses a few weaknesses I had pointed out previously, such as to include important results that were initially deferred to the appendix and to drop a misleading comparison. It ... | [
[
369,
436
],
[
447,
590
],
[
591,
808
],
[
812,
865
],
[
867,
995
]
] | [
"Eval_pos_1",
"Eval_neg_1",
"Eval_neg_2",
"Major_claim",
"Eval_neg_3"
] |
55 | paper_summary
**Note**: *This is only a slight revision of my previous review for a previous version of this paper. I did not re-check all the details of the paper carefully, I mostly focused on checking the parts where I had reservations towards the previous version; I simply hope that the parts which I already found ... | [
[
1631,
1818
],
[
1819,
1957
],
[
2038,
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],
[
2159,
2282
],
[
2284,
2361
],
[
2557,
2682
],
[
2684,
2801
]
] | [
"Eval_pos_1",
"Eval_pos_2",
"Major_claim",
"Eval_pos_3",
"Eval_pos_4",
"Eval_neg_1",
"Jus_neg_1"
] |
56 | paper_summary
The paper introduces a pre-trained vision language model (FewVLM) for prompt-based few-shot vision language tasks such as image captioning and vision question answering. The model is pre-trained with a combined objective of masked language modeling and prefix language modeling. Compared to giant pre-train... | [
[
930,
1005
],
[
1006,
1236
],
[
1238,
1355
],
[
1356,
1464
],
[
1489,
1634
],
[
1635,
1734
],
[
1736,
1872
],
[
1873,
2005
]
] | [
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"Eval_pos_2",
"Jus_pos_2",
"Eval_neg_1",
"Jus_neg_1",
"Eval_neg_2",
"Jus_neg_2"
] |
57 | paper_summary
The paper presents a method for representing the relevance of a linguistic dataset to the corresponding language and its speakers. As a proxy for speakers of a certain language the authors use geographical entities, particularly countries. The representation they aim to build relies on entity linking, so ... | [
[
493,
629
],
[
630,
899
],
[
1009,
1107
],
[
1109,
1189
],
[
1441,
1508
],
[
1509,
1741
],
[
1743,
1915
],
[
1948,
2581
]
] | [
"Eval_pos_1",
"Jus_pos_1",
"Eval_neg_1",
"Eval_neg_2",
"Eval_neg_3",
"Jus_neg_3",
"Eval_neg_4",
"Jus_neg_2"
] |
58 | - Strengths: The approach described in the manuscript outperformed the previous approaches and achieved the state-of-the-art result.
Regarding data, the method used the combination of market and text data.
The approach used word embeddings to define the weight of each lexicon term by extending it to the similar terms i... | [
[
13,
132
],
[
498,
581
],
[
582,
709
],
[
911,
948
]
] | [
"Eval_pos_1",
"Eval_neg_1",
"Eval_neg_2",
"Eval_neg_3"
] |
59 | paper_summary
This paper investigates the effectiveness of entity representations in multilingual language models. The proposed mLUKE model exhibits strong empirical results with the word inputs (mLUKE-W), it also also shows even better performance with the entity representations (mLUKE-E) in cross-lingual transfer tas... | [
[
1241,
1371
],
[
1405,
1482
],
[
1483,
1528
]
] | [
"Eval_neg_1",
"Eval_pos_1",
"Eval_pos_2"
] |
60 | This paper describes (1) new corpus resources for the under-resourced Kinyarwanda and Kirundi languages, (2) preliminary experiments on genre classification using these corpora. The resources are described thoroughly, and a useful survey of related work on these languages is presented. A variety of models are used in t... | [
[
178,
217
],
[
222,
285
],
[
287,
334
],
[
340,
390
],
[
391,
665
],
[
667,
727
]
] | [
"Eval_pos_1",
"Eval_pos_2",
"Eval_pos_3",
"Eval_pos_4",
"Jus_pos_4",
"Major_claim"
] |
61 | - Strengths: This paper proposes the use of HowNet to enrich embedings. The idea is interesting and gives good results.
- Weaknesses: The paper is interesting, but I am not sure the contibution is important enough for a long paper. Also, the comparision with other works may not be fair: authors should compare to other ... | [
[
72,
119
],
[
164,
230
],
[
238,
286
],
[
288,
366
],
[
400,
446
]
] | [
"Eval_pos_1",
"Major_claim",
"Eval_neg_1",
"Jus_neg_1",
"Eval_neg_2"
] |
62 | [update after reading author response: the alignment of the hidden units does not match with my intuition and experience, but I'm willing to believe I'm wrong in this case. Discussing the alignment in the paper is important (and maybe just sanity-checking that the alignment goes away if you initialize with a different... | [
[
39,
120
],
[
174,
328
],
[
625,
724
],
[
744,
799
],
[
806,
880
],
[
900,
944
],
[
951,
984
],
[
1299,
1355
],
[
1357,
1414
],
[
1415,
2492
],
[
2493,
2836
],
[
2856,
2896
... | [
"Eval_neg_1",
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"Eval_pos_2",
"Eval_neg_2",
"Eval_neg_3",
"Eval_pos_3",
"Eval_neg_4",
"Jus_neg_4",
"Jus_neg_5",
"Eval_neg_5"
] |
63 | paper_summary
This paper proposes a unified representation model Prix-LM for multilingual knowledge base (KB) construction and completion. Specifically, they leverage monolingual triples and cross-lingual links from existing multilingual KBs DBpedia, and formulate them as the autoregressive language modeling training o... | [
[
648,
828
],
[
832,
1010
]
] | [
"Eval_pos_1",
"Eval_pos_2"
] |
64 | paper_summary
*(minor edits from previous review XYZ)* Text style transfer is the task of rewriting a sentence into a target style while approximately preserving its content. Modern style transfer research operates in an "unsupervised" setting, where no parallel training data (pairs of sentences differing in style) is ... | [
[
1192,
1243
],
[
1244,
1659
],
[
1663,
1872
],
[
1873,
2186
]
] | [
"Eval_pos_1",
"Jus_pos_1",
"Eval_pos_2",
"Jus_pos_2"
] |
65 | paper_summary
This paper proposes a simple but powerful approach that uses a single Transformer architecture to tackle KG link prediction and question answering treated as sequence-to-sequence tasks. This approach can reduce the model size up to 90% compared to conventional Knowledge graph embedding (KGE) models, and t... | [
[
520,
555
],
[
562,
672
],
[
702,
814
],
[
815,
1029
]
] | [
"Eval_pos_1",
"Eval_pos_2",
"Eval_neg_1",
"Jus_neg_1"
] |
66 | paper_summary
This paper introduces a new method for MeSH indexing, combining multiple methods including, but not limited to, dilated CNNs, masked attention, and graph CNNs. Overall, the proposed approach makes substantial improvements over prior state-of-the-art methods. For example, Micro F1 improves over BERTMeSH fr... | [
[
666,
718
],
[
719,
779
],
[
780,
905
],
[
906,
1071
]
] | [
"Eval_pos_1",
"Eval_pos_2",
"Eval_pos_3",
"Jus_pos_3"
] |
67 | paper_summary
This paper describes a contrastive learning approach to automatically solving math word problems (MWP) and investigates multilingual approaches to the problem. Additionally, it provides further evidence that the top layers of BERT will learn task-specific patterns, as shown in prior works. This paper tre... | [
[
1977,
2047
],
[
2070,
2141
],
[
2143,
2325
],
[
2326,
2395
]
] | [
"Eval_pos_1",
"Eval_neg_1",
"Jus_neg_2",
"Eval_neg_2"
] |
68 | paper_summary
Existing self-explaining models mostly generate the short rationales with the assumption that short rationales are more intuitive to humans, while this work discusses the question that whether the shortest rationale is the most understandable for humans. In this work, the authors design a self-explaining ... | [
[
855,
1016
],
[
1020,
1210
],
[
1236,
1531
],
[
1532,
1652
],
[
1897,
2040
],
[
2056,
2249
]
] | [
"Eval_pos_1",
"Eval_pos_2",
"Jus_neg_1",
"Eval_neg_1",
"Eval_neg_2",
"Jus_neg_2"
] |
69 | paper_summary
This paper compares two figures, Firth and Harris, who are often cited as foundational in modern computational linguistics but who are rarely actually read, perhaps even not by the people who cite them. It does a deep dive into their work and takes an opinionated stance that Harris was “introverted”, focu... | [
[
458,
486
],
[
488,
573
],
[
574,
695
],
[
696,
731
],
[
733,
855
],
[
856,
986
],
[
986,
1018
],
[
1135,
1238
],
[
1238,
2562
]
] | [
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"Eval_pos_2",
"Jus_pos_2",
"Jus_pos_3",
"Eval_pos_3",
"Eval_neg_1",
"Jus_neg_1"
] |
70 | paper_summary
Note - I reviewed this paper in the past and had a positive criticism about it. The authors also addressed my previous comments and I keep my positive review from before.
This paper discusses methods for improving multi-domain training for dialog response generation. The authors experiment with several ap... | [
[
1547,
1655
],
[
1656,
1827
],
[
1850,
1933
],
[
1936,
2056
]
] | [
"Eval_pos_1",
"Eval_pos_2",
"Jus_neg_1",
"Eval_neg_1"
] |
71 | paper_summary
This paper proposes a new task formulation to solve complex tasks. In this new formulation, there are multiple agents, each of which is capable of solving some specific types of tasks. For example, there can be a QA agent that answers natural language (NL) questions and an instruction following agent that... | [
[
1245,
1304
],
[
1305,
1392
],
[
1393,
1467
],
[
1492,
1586
],
[
1587,
3108
],
[
3111,
3244
],
[
3245,
3858
]
] | [
"Eval_pos_1",
"Eval_pos_2",
"Eval_pos_3",
"Eval_neg_1",
"Jus_neg_1",
"Eval_neg_2",
"Jus_neg_2"
] |
72 | paper_summary
The authors proposed a Locally Aggregated Feature Attribution method and claimed that this is a novel gradient-based feature attribution method for NLP models.
summary_of_strengths
The authors proposed a Locally Aggregated Feature Attribution method
summary_of_weaknesses
Results are varying so much on t... | [
[
288,
341
]
] | [
"Eval_neg_1"
] |
73 | This paper presents a corpus study of coreferences comparing different genres (news, blogs, conversations) and media (written, transcribed speech, microblogging) based on the Ontonotes and Switchboard corpora and a dataset from Twitter sub-threads. The analysed factors include the use of pronouns and noun phrases, the ... | [
[
448,
552
],
[
553,
644
],
[
645,
719
],
[
752,
1038
],
[
1039,
1133
],
[
1138,
1202
],
[
1206,
1347
],
[
1536,
1613
],
[
1634,
1763
],
[
1764,
1832
],
[
1834,
1992
],
[
1993,
... | [
"Eval_pos_1",
"Jus_pos_1",
"Major_claim",
"Jus_neg_1",
"Eval_neg_1",
"Eval_neg_2",
"Jus_neg_2",
"Eval_neg_2",
"Eval_neg_3",
"Jus_neg_3",
"Eval_neg_4",
"Jus_neg_4",
"Eval_neg_5",
"Eval_neg_6",
"Eval_neg_7",
"Jus_neg_7"
] |
74 | paper_summary
This paper is about determining the syntactic ability of two Dutch variants of transformer based language model BERT: BERTje and RobBERT. The authors use a Multiple Context Free Grammar (MCFG) formalism to model two patterns of Dutch syntax: control verb nesting and verb raising. These rule-based grammati... | [
[
982,
1141
],
[
1142,
1188
],
[
1189,
1235
],
[
1240,
1277
],
[
1279,
1371
],
[
2468,
2544
],
[
2545,
3087
]
] | [
"Eval_pos_1",
"Eval_pos_2",
"Eval_pos_3",
"Eval_pos_4",
"Jus_pos_4",
"Eval_neg_1",
"Jus_neg_1"
] |
75 | paper_summary
This work introduces a new dataset, the Hindi Legal Documents Corpus (HLDC), a corpus with 900 thousand legal documents in Hindi. This corpus is collected from public data, and the authors intend to release (in addition to the corpus) the scripts necessary for its creation and processing, along with model... | [
[
995,
1098
],
[
1098,
1223
],
[
1227,
1298
],
[
1363,
1520
],
[
1610,
1663
],
[
1664,
1730
],
[
1736,
1774
],
[
1986,
2096
],
[
2097,
2249
]
] | [
"Eval_pos_1",
"Eval_pos_2",
"Eval_pos_3",
"Eval_pos_4",
"Eval_pos_5",
"Jus_pos_5",
"Eval_pos_6",
"Eval_neg_1",
"Jus_neg_1"
] |
76 | paper_summary
This paper proposed a confidence estimation method for neural machine translation (NMT) by jointly training the NMT model with a confidence network which learns to output a confidence score per example. The confidence score (a scalar between 0 and 1) is used to provide “hints” for the NMT model, that is i... | [
[
898,
1000
],
[
1000,
1186
],
[
1191,
1236
],
[
1237,
1283
],
[
1600,
1742
]
] | [
"Eval_pos_1",
"Eval_pos_2",
"Eval_pos_3",
"Eval_pos_4",
"Eval_neg_1"
] |
77 | The paper explores the use of probabilistic models (gaussian processes) to regress on the target variable of post-editing time/rates for quality estimation of MT output.
The paper is well structured with a clear introduction that highlights the problem of QE point estimates in real-world applications. I especially lik... | [
[
171,
225
],
[
226,
303
],
[
304,
423
],
[
585,
697
],
[
698,
803
],
[
1108,
1166
],
[
1168,
1326
],
[
1641,
1792
],
[
1795,
2009
],
[
2010,
2081
],
[
2082,
2173
],
[
2279,
23... | [
"Eval_pos_1",
"Jus_pos_1",
"Eval_pos_2",
"Eval_pos_3",
"Eval_pos_4",
"Eval_neg_1",
"Jus_neg_1",
"Eval_pos_5",
"Jus_pos_5",
"Eval_pos_6",
"Major_claim",
"Eval_neg_2",
"Jus_neg_2",
"Eval_pos_7"
] |
78 | This is a highly satisfying paper. It is a report of various NLP efforts for several Indigenous languages of Canada It goes deeply enough into the technical details of the projects to show that the efforts are viable and successful, without getting bogged down in numbers or linguistic details that are unimportant to pe... | [
[
0,
34
],
[
116,
350
],
[
1629,
1726
],
[
1727,
1777
],
[
1778,
2408
],
[
2409,
2578
],
[
2579,
2638
]
] | [
"Major_claim",
"Eval_pos_1",
"Eval_pos_2",
"Eval_pos_3",
"Jus_pos_3",
"Eval_pos_4",
"Major_claim"
] |
79 | The aim of this paper is to show that distributional information stored in word vector models contain information about POS labels. They use a version of the BNC annotated with UD POS and in which words have been replaced by lemmas. They train word embeddings on this corpus, then use the resulting vectors to train a lo... | [
[
530,
566
],
[
567,
661
],
[
662,
754
],
[
755,
785
],
[
787,
859
],
[
860,
962
],
[
980,
1082
],
[
1083,
1197
]
] | [
"Eval_pos_1",
"Eval_neg_1",
"Jus_neg_1",
"Eval_pos_2",
"Jus_pos_2",
"Major_claim",
"Eval_neg_2",
"Jus_neg_2"
] |
80 | - Strengths: This paper reports on an interesting project to enable people to design their own language for interacting with a computer program, in place of using a programming language. The specific construction that the authors focus on is the ability for people to make definitions. Very nicely, they can make recursi... | [
[
286,
387
],
[
388,
485
],
[
486,
569
],
[
585,
656
],
[
657,
746
],
[
748,
796
],
[
798,
821
],
[
824,
922
],
[
923,
1092
]
] | [
"Eval_pos_1",
"Eval_pos_2",
"Eval_pos_3",
"Eval_neg_1",
"Jus_neg_1",
"Eval_neg_2",
"Jus_neg_2",
"Eval_neg_3",
"Jus_neg_3"
] |
81 | paper_summary
This work proposes to explicitly model sentence-level representations of both the source and target side of unsupervised machine translation. The authors utilize normalizing flows to model the sentence representations in a flexible space as transformed from a (shared between languages) simple base distrib... | [
[
615,
657
],
[
660,
782
],
[
783,
896
],
[
899,
996
],
[
1021,
1081
],
[
1083,
1208
],
[
1211,
1251
],
[
1252,
1262
],
[
1449,
1547
],
[
1548,
1823
]
] | [
"Eval_pos_1",
"Eval_pos_2",
"Eval_pos_3",
"Eval_pos_4",
"Eval_neg_1",
"Jus_neg_1",
"Eval_neg_2",
"Jus_neg_2",
"Eval_neg_3",
"Jus_neg_3"
] |
82 | paper_summary
The authors present an approach for knowledge enhanced counseling reflection generation. It uses dialogue context as well as commonsense and domain knowledge for generating responses in counseling conversations. Two methods for knowledge integration are proposed: a retrieval-based method and a generative ... | [
[
883,
954
],
[
955,
1008
],
[
1010,
1063
],
[
1065,
1097
],
[
1098,
1181
],
[
1182,
1277
],
[
1284,
1336
],
[
1338,
1428
],
[
1453,
1511
],
[
1513,
1612
],
[
1645,
1936
]
] | [
"Eval_pos_1",
"Eval_pos_2",
"Eval_pos_3",
"Eval_pos_4",
"Eval_pos_5",
"Eval_pos_6",
"Eval_pos_7",
"Eval_pos_8",
"Eval_neg_1",
"Eval_neg_2",
"Jus_neg_2"
] |
84 | paper_summary
This paper presents an interesting finding, i.e., fine-tuning only the bias terms of pre-trained language models is competitive with fine-tuning the entire model. The authors compared the proposed method Bias-terms Fine-tuning (BitFit) with other parameter-efficient fine-tuning methods (e.g., Adapters, Di... | [
[
480,
529
],
[
531,
578
],
[
580,
641
],
[
664,
709
],
[
864,
914
]
] | [
"Eval_pos_1",
"Eval_pos_2",
"Eval_pos_3",
"Major_claim",
"Major_claim"
] |
85 | paper_summary
This paper proposes a novel method to explore the search space of neural text generation models. The proposed method includes two key components of a modified best-first search and a path recombination mechanism. The authors conduct experiments on text summarization and machine translation tasks. The expe... | [
[
485,
554
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[
557,
656
],
[
659,
746
],
[
771,
896
],
[
897,
929
]
] | [
"Eval_pos_1",
"Eval_pos_2",
"Eval_pos_3",
"Jus_neg_1",
"Eval_neg_1"
] |
86 | The paper proposes a convolutional neural network approach to model the coherence of texts. The model is based on the well-known entity grid representation for coherence, but puts a CNN on top of it. The approach is well motivated and described, I especially appreciate the clear discussion of the intuitions behind cer... | [
[
201,
245
],
[
247,
394
],
[
396,
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],
[
765,
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],
[
920,
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[
1194,
1277
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[
1613,
1727
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[
1924,
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1987,
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"Eval_neg_2",
"Jus_neg_2",
"Eval_pos_3",
"Major_claim",
"Eval_neg_3",
"Jus_neg_3"
] |
88 | paper_summary
The authors present a method of calibrating learned multiclass classification models during training, that is, improving model calibration (in other words, pushing accuracy-versus-model-confidence graphs towards the identity line---well-calibrated models have confidence perfectly reflecting prediction acc... | [
[
753,
824
],
[
825,
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],
[
1280,
1377
],
[
1378,
1397
],
[
1650,
1724
],
[
1735,
1871
],
[
1877,
1946
],
[
1948,
2364
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[
2376,
2455
],
[
2461,
2593
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[
2617,
2702
],
[
2703,... | [
"Eval_neg_1",
"Jus_neg_1",
"Eval_neg_3",
"Jus_neg_3",
"Jus_pos_1",
"Eval_pos_1",
"Eval_neg_4",
"Jus_neg_4",
"Major_claim",
"Eval_neg_7",
"Eval_pos_2",
"Jus_pos_2",
"Eval_pos_3",
"Jus_pos_3",
"Eval_neg_8",
"Jus_neg_8",
"Eval_neg_2",
"Jus_neg_2",
"Eval_neg_10",
"Jus_neg_10",
"E... |
90 | - Strengths: This paper tries to use the information from arguments, which is usually ignored yet actually quite important, to improve the performance of event detection. The framework is clear and simple. With the help of the supervised attention mechanism, an important method that has been used in many tasks such as ... | [
[
171,
205
],
[
206,
412
],
[
512,
590
],
[
591,
767
],
[
844,
892
],
[
897,
921
],
[
922,
946
],
[
947,
984
]
] | [
"Eval_pos_1",
"Eval_pos_2",
"Eval_neg_1",
"Jus_neg_1",
"Eval_pos_3",
"Eval_pos_4",
"Eval_pos_5",
"Major_claim"
] |
91 | paper_summary
This paper empirically studied CLIP models as few-shot learners for two vision-language understanding tasks: VQA and Visual entailment. In the VQA task, the paper proposed a two-step method to mitigate the gap between natural language description and question answering. In addition, the paper used only a ... | [
[
778,
833
],
[
838,
892
],
[
893,
1051
]
] | [
"Eval_neg_1",
"Eval_neg_2",
"Eval_neg_3"
] |
92 | Summary: This paper proposes a novel solution for abstractive dialogue summarization, which is a challenging task because it requires modeling discourse structure and long dependencies between utterances in the dialogue. The proposed approach consists of several parts: (1) Representing the input dialogue as a graph, us... | [
[
907,
974
],
[
975,
1137
],
[
1163,
1231
],
[
1260,
1487
],
[
1489,
1668
],
[
1681,
1770
],
[
1771,
1839
],
[
1841,
1881
],
[
1886,
1964
],
[
2114,
2158
],
[
2174,
2326
],
[
2327,... | [
"Eval_pos_1",
"Jus_pos_1",
"Eval_neg_1",
"Jus_neg_1",
"Major_claim",
"Eval_pos_2",
"Jus_pos_2",
"Eval_pos_3",
"Eval_pos_4",
"Eval_pos_5",
"Eval_neg_2",
"Jus_neg_2",
"Eval_neg_3",
"Eval_neg_4",
"Jus_neg_4",
"Eval_neg_5",
"Jus_neg_5",
"Eval_neg_5"
] |
93 | The paper is clearly written, and the claims are well-supported. The Related Work in particular is very thorough, and clearly establishes where the proposed work fits in the field.
I had two main questions about the method: (1) phrases are mentioned in section 3.1, but only word representations are discussed. How are... | [
[
0,
64
],
[
66,
181
]
] | [
"Eval_pos_1",
"Eval_pos_2"
] |
96 | paper_summary
The paper investigates the problem of identifying unanswerable questions in multiple choice MRC. It proposes two ways of tackling this problem: Firstly, by explicitly augmenting training data with unanswerable examples and secondly, by thresholding on (estimated) prediction uncertainty. The paper goes on ... | [
[
498,
601
],
[
602,
666
],
[
667,
829
],
[
852,
898
],
[
903,
940
],
[
941,
1426
],
[
1430,
1511
],
[
1512,
1926
],
[
2022,
2065
],
[
2066,
2190
],
[
2261,
2322
],
[
2323,
308... | [
"Eval_pos_1",
"Eval_pos_2",
"Eval_pos_3",
"Major_claim",
"Eval_neg_1",
"Jus_neg_1",
"Eval_neg_2",
"Jus_pos_1",
"Eval_neg_3",
"Jus_neg_3",
"Eval_neg_4",
"Jus_neg_4"
] |
97 | paper_summary
The paper presents AcTune, an active learning framework that combines self training on high-confident samples and data annotation on low-confident samples. The paper also proposes two new methods: (1) region-based sampling and (2) momentum-based memory bank, to improve the sampling strategy in active lear... | [
[
570,
695
],
[
717,
818
],
[
819,
945
],
[
946,
1009
],
[
1032,
1051
]
] | [
"Major_claim",
"Eval_pos_1",
"Eval_pos_2",
"Eval_pos_3",
"Major_claim"
] |
100 | - strengths This is a novel approach to modeling the compositional structure of complex categories that maintains a set theoretic interpretation of common nouns and modifiers, while also permitting a distributional interpretation of head modification. The approach is well motivated and clearly defined and the experimen... | [
[
12,
98
],
[
99,
251
],
[
252,
302
],
[
1144,
1263
]
] | [
"Eval_pos_1",
"Jus_pos_1",
"Eval_pos_2",
"Major_claim"
] |
101 | This paper develops an LSTM-based model for classifying connective uses for whether they indicate that a causal relation was intended. The guiding idea is that the expression of causal relations is extremely diverse and thus not amenable to syntactic treatment, and that the more abstract representations delivered by ne... | [
[
475,
543
],
[
761,
880
],
[
882,
1338
],
[
1362,
1465
],
[
1466,
2093
],
[
2096,
2162
],
[
2163,
2490
],
[
2616,
2681
],
[
2682,
3334
],
[
3337,
3391
],
[
3392,
3833
],
[
3834,
... | [
"Eval_pos_1",
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"Jus_neg_1",
"Eval_neg_2",
"Jus_neg_2",
"Eval_neg_3",
"Jus_neg_3",
"Eval_neg_4",
"Jus_neg_4",
"Eval_neg_5",
"Jus_neg_5",
"Jus_neg_6",
"Eval_neg_6",
"Eval_neg_7",
"Jus_neg_7",
"Eval_neg_8",
"Jus_neg_8"
] |
102 | paper_summary
This paper is about the design of an automatic phoneme transcription system for transcription assistance.
In particular, it targets endangered languages with only one speaker data, and the goal is to reduce the cost of transcription such languages.
With all due respect to previous research, the authors ... | [
[
1075,
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[
1455,
1543
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[
1546,
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],
[
1781,
1861
],
[
1862,
1913
],
[
1917,
2022
],
[
2023,
2847
],
[
2851,
2945
],
[
2946,
3471
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[
3472,
3557
],
[
37... | [
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"Eval_neg_1",
"Jus_neg_1",
"Eval_neg_2",
"Jus_neg_2",
"Eval_pos_5",
"Eval_neg_3"
] |
103 | paper_summary
The paper presents a framework for abstractive summarization of long documents that repeatedly segments text, summarizes each segment and then feeds the concatenated summaries as an input to the next iteration. When the input is below a predefined number of tokens, the final summary is generated. This des... | [
[
525,
659
],
[
661,
833
],
[
835,
885
],
[
910,
955
],
[
957,
1582
],
[
1584,
1631
],
[
1691,
1729
],
[
1731,
1785
]
] | [
"Eval_pos_1",
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"Eval_pos_3",
"Eval_neg_1",
"Jus_neg_1",
"Eval_neg_2",
"Eval_neg_3",
"Jus_neg_3"
] |
105 | This work proposes a self-learning bootstrapping approach to learning bilingual word embeddings, which achieves competitive results in tasks of bilingual lexicon induction and cross-lingual word similarity although it requires a minimal amount of bilingual supervision: the method leads to competitive performance even w... | [
[
506,
556
],
[
557,
584
],
[
585,
973
],
[
975,
1003
],
[
1005,
1096
],
[
1116,
1158
],
[
1163,
1223
],
[
1660,
1729
],
[
1730,
2209
],
[
2896,
2999
],
[
3000,
4398
],
[
5963,
... | [
"Eval_pos_1",
"Eval_pos_2",
"Jus_pos_2",
"Major_claim",
"Eval_neg_1",
"Eval_neg_2",
"Eval_neg_3",
"Eval_neg_1",
"Jus_neg_1",
"Eval_neg_3",
"Jus_neg_3",
"Eval_neg_4",
"Jus_neg_4"
] |
106 | paper_summary
The authors introduce a new annotated event detection dataset that is focused on annotation suicidal events.
The annotation focuses on the following event types: suicide-related actions, thoughts/ideation, risk factors related to life, relationship, health, and other, in addition to protective factors re... | [
[
668,
704
],
[
709,
771
],
[
773,
937
],
[
938,
1061
],
[
1064,
1156
],
[
1159,
1227
],
[
1232,
1423
],
[
1426,
1489
],
[
1492,
1572
],
[
1597,
1819
],
[
1820,
2175
],
[
2178,
... | [
"Eval_pos_1",
"Eval_pos_2",
"Eval_pos_3",
"Jus_pos_3",
"Eval_pos_4",
"Eval_pos_5",
"Jus_pos_5",
"Eval_pos_6",
"Eval_pos_7",
"Eval_neg_1",
"Jus_neg_1",
"Eval_neg_2",
"Jus_neg_2",
"Eval_neg_3",
"Jus_neg_3"
] |
109 | This paper introduces Neural Symbolic Machines (NSMs) --- a deep neural model equipped with discrete memory to facilitate symbolic execution. An NSM includes three components: (1) a manager that provides weak supervision for learning, (2) a differentiable programmer based on neural sequence to sequence model, which enc... | [
[
988,
1072
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[
1091,
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],
[
1242,
1301
],
[
1305,
1551
],
[
1554,
1664
],
[
1665,
1692
],
[
1695,
1741
],
[
1751,
1814
],
[
1815,
2015
],
[
2017,
2087
],
[
3018,
3068
],
[
306... | [
"Eval_pos_1",
"Eval_pos_2",
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"Eval_pos_3",
"Eval_pos_4",
"Eval_pos_5",
"Eval_pos_6",
"Eval_neg_1",
"Jus_neg_1",
"Major_claim",
"Eval_neg_2",
"Jus_neg_2"
] |
110 | paper_summary
This paper presents a new dataset - DISAPERE, which includes discourse related annotations over scientific peer reviews and rebuttals. Each review is paired with the first rebuttal text. The authors develop four levels for review annotation: (1) review-action, (2) aspect, (3) polarity, and (4) fine-review... | [
[
1045,
1134
],
[
1378,
1459
]
] | [
"Eval_pos_1",
"Eval_pos_2"
] |
111 | The authors proposed an unsupervised algorithm for Universal Dependencies that does not require training. The tagging is based on PageRank for the words and a small amount of hard-coded rules.
The article is well written, very detailed and the intuition behind all prior information being added to the model is explaine... | [
[
194,
331
],
[
332,
414
],
[
419,
512
]
] | [
"Eval_pos_1",
"Eval_pos_2",
"Eval_pos_3"
] |
113 | paper_summary
This paper presentes a multi task learning approach for automatic grading of English essays, by considering a holistic score as well as scores on individual essay traits. The authors proposed an LSTM based model and compared single task and multi task settings to show that Multi-task learning based system... | [
[
909,
1032
],
[
1035,
1121
],
[
1249,
1336
],
[
1337,
1668
],
[
1671,
1744
],
[
1745,
2222
],
[
2622,
2730
],
[
2731,
3109
]
] | [
"Jus_pos_1",
"Eval_pos_1",
"Eval_neg_1",
"Jus_neg_1",
"Eval_neg_2",
"Jus_neg_2",
"Eval_neg_3",
"Jus_neg_3"
] |
115 | paper_summary
This paper investigates the degree of knowledge that pre-trained LM, with only access to a vocabulary of subword tokens, have about the character composition of these tokens, and if enriching these models with orthographic information about the tokens can improve them. It proposes to use a probe they name... | [
[
1608,
1662
],
[
1668,
1728
],
[
1729,
1772
],
[
1832,
1887
],
[
1912,
1979
],
[
1980,
2400
]
] | [
"Eval_pos_1",
"Eval_pos_2",
"Jus_pos_2",
"Eval_pos_3",
"Eval_neg_1",
"Jus_neg_1"
] |
118 | paper_summary
This paper proposes to learn discriminative representations for open relation extraction. In specific, the authors first introduce three data augmentation strategies to generate positive, hard negative, and semi-hard negative samples. Then, the proposed model not only uses instance ranking to optimize eac... | [
[
426,
500
],
[
501,
554
],
[
580,
606
],
[
610,
640
],
[
641,
718
],
[
722,
757
],
[
856,
896
]
] | [
"Eval_pos_4",
"Major_claim",
"Eval_pos_1",
"Eval_pos_2",
"Jus_pos_2",
"Eval_pos_3",
"Eval_neg_1"
] |
120 | This paper introduces a joint decoder model that generates both transcript and translation, conditioned on some speech utterance as input. The decoder model, on an intuitive level, decodes transcript and translation tokens jointly with separately parameterized decoders which are conditioned not only on the source speec... | [
[
387,
585
],
[
586,
617
],
[
618,
748
],
[
749,
1003
],
[
1004,
1041
],
[
1043,
1173
],
[
1175,
1231
],
[
1232,
1352
],
[
1353,
1453
],
[
1454,
1705
]
] | [
"Eval_pos_1",
"Eval_pos_2",
"Eval_pos_3",
"Jus_pos_4",
"Eval_pos_4",
"Major_claim",
"Eval_neg_1",
"Jus_neg_1",
"Eval_neg_2",
"Jus_neg_2"
] |
121 | Related to a recent notion of Visual Dialog tasks, the paper introduces and evaluates a sophisticated neural architecture to answer queries related to images through a dialog (a sequence of several queries and answers).
There are several components in the system but the paper focuses on two of them, namely VTA to map ... | [
[
820,
875
],
[
876,
973
],
[
975,
1050
],
[
1051,
1282
]
] | [
"Eval_pos_1",
"Eval_neg_1",
"Eval_neg_2",
"Jus_neg_2"
] |
122 | paper_summary
The paper proposes a new approach named BEEP to combine information from clinical notes and relevant medical literature to enhance the prediction of patient outcomes (prolonged mechanical ventilation, in-hospital mortality and length of stay). The medical literature is retrieved from PubMed and then ranke... | [
[
551,
761
],
[
764,
882
],
[
883,
946
],
[
949,
992
],
[
993,
1056
],
[
1420,
1492
],
[
1493,
1605
],
[
1695,
1787
],
[
1790,
1856
],
[
1856,
1912
],
[
1913,
2014
],
[
2292,
2... | [
"Eval_pos_1",
"Eval_pos_2",
"Eval_pos_3",
"Eval_pos_4",
"Eval_pos_5",
"Eval_neg_1",
"Jus_neg_1",
"Eval_neg_2",
"Eval_neg_3",
"Jus_neg_3",
"Eval_neg_3",
"Eval_neg_4",
"Jus_neg_4"
] |
123 | paper_summary
The paper deals with multi-task learning. The authors find that having separate networks to learn separate tasks would lead to good performance, but requires a large memory. Using MT-DNN would save memory, but the results are not satisfying. The authors thus propose an approach that saves memory and at th... | [
[
842,
859
],
[
861,
901
],
[
902,
964
],
[
969,
1045
],
[
1046,
1238
],
[
1646,
1781
],
[
1782,
1899
],
[
1923,
2027
],
[
2028,
2055
],
[
2056,
2070
]
] | [
"Eval_pos_1",
"Eval_pos_2",
"Jus_pos_2",
"Eval_pos_3",
"Jus_pos_3",
"Eval_neg_1",
"Jus_neg_1",
"Eval_neg_2",
"Jus_neg_2",
"Eval_neg_2"
] |
124 | paper_summary
The authors aim to improve interpretability for structure and style control in knowledge-grounded conversational models. They propose to use two sequential latent variables for structure and style respectively. 1) m - binary indicator for segment boundaries within a sentence 2) z - style controller attri... | [
[
645,
695
],
[
696,
783
],
[
1098,
1209
],
[
1211,
1252
],
[
1254,
1348
],
[
1375,
1422
],
[
1423,
1576
]
] | [
"Eval_pos_1",
"Jus_pos_1",
"Eval_pos_1",
"Eval_pos_2",
"Eval_pos_2",
"Eval_neg_1",
"Jus_neg_1"
] |
126 | paper_summary
Prior work has used interpretation to improve inference, while ignoring “using inference logic to enhance interpretation.” This work deals with “mutual promotion” where they “promote” in both directions. Specifically, the “mutual promotion” is done using stepwise integration mechanism (SIM; Section 2.2). ... | [
[
935,
974
],
[
976,
1049
],
[
1050,
1100
],
[
1101,
1118
],
[
1120,
1172
],
[
1196,
1289
],
[
1290,
1409
],
[
1411,
1446
],
[
1448,
1506
],
[
1507,
1647
],
[
1648,
1689
],
[
1690,... | [
"Eval_pos_1",
"Eval_pos_2",
"Eval_pos_3",
"Jus_pos_3",
"Eval_pos_4",
"Eval_neg_1",
"Jus_neg_1",
"Eval_neg_2",
"Eval_neg_3",
"Jus_neg_3",
"Eval_neg_4",
"Jus_neg_4",
"Jus_neg_5",
"Eval_neg_5",
"Eval_neg_6"
] |
128 | The paper describes a model for morphological segmentation.
The model is a neural network that takes as input a representation of the word to segment and a representation of the context.
The model is trained and tested on mongolian data and reaches good performances (98% f measure).
The work is sound and well conduc... | [
[
189,
268
],
[
269,
284
],
[
287,
372
],
[
374,
738
],
[
739,
775
]
] | [
"Eval_pos_1",
"Jus_pos_1",
"Eval_neg_1",
"Jus_neg_1",
"Eval_pos_2"
] |
129 | paper_summary
This paper addresses the question of whether the spelling of words has been retained / encoded by large language models. First, it introduces a probe to discover the spelling of a word based on the embeddings in the model input. This probe, spelling bee, is essentially a character level language model whi... | [
[
1015,
1192
],
[
1216,
1437
],
[
1438,
1522
],
[
1524,
1645
],
[
1646,
2359
],
[
2360,
2428
],
[
2462,
2596
],
[
2597,
2639
]
] | [
"Eval_pos_1",
"Jus_neg_1",
"Eval_neg_1",
"Eval_neg_2",
"Jus_neg_2",
"Eval_neg_3",
"Eval_neg_4",
"Jus_neg_4"
] |
130 | - Strengths: Introduces a new document clustering approach and compares it to several established methods, showing that it improves results in most cases.
The analysis is very detailed and thorough--quite dense in many places and requires careful reading.
The presentation is organized and clear, and I am impressed by... | [
[
13,
155
],
[
157,
257
],
[
258,
298
],
[
303,
391
],
[
392,
414
],
[
419,
463
]
] | [
"Eval_pos_1",
"Eval_pos_2",
"Eval_pos_3",
"Eval_pos_4",
"Eval_pos_5",
"Eval_pos_6"
] |
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