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_id stringlengths 1 5	task stringclasses 7 values	src stringlengths 22 884	tgt stringlengths 0 697
81200	coherence	Fix coherence mistakes in this sentence: Many soldiers have large heads with highly modified powerful jaws so enlarged they can not feed themselves. Like juveniles, soldiers are fed by workers.	Many soldiers have large heads with highly modified powerful jaws so enlarged they can not feed themselves. Instead, like juveniles, they are fed by workers.
81201	coherence	Make the text more cohesive: Jump up ^ Highland Hills 2003-06-22. Highland Hills is the Encyclopedia of Cleveland History.	Jump up ^ Highland Hills, The Encyclopedia of Cleveland History, 2003-06-22.
81202	coherence	Fix coherence in this text: His latest book The Gold Eaters was published in 2015. His latest book The Gold Eaters is a novel set during the Spanish invasion of the Inca Empire in the 1520s-1540s.	His latest book The Gold Eaters, a novel set during the Spanish invasion of the Inca Empire in the 1520s-1540s, was published in 2015.
81203	coherence	Make the text more coherent: Jump up ^ News: 3 December 2003 retrieved on 10 June 2011. Jump up ^ News: 3 December 2003 is the Tribe Official Website.	Jump up ^ News: 3 December 2003, The Tribe Official Website, retrieved on 10 June 2011.
81204	coherence	Fix coherence mistakes in this sentence: Joshua Wentzel (born 1999) is a finalist in the 2013 Broadcom MASTERS for his physical sciences project. The 2013 Broadcom MASTERS are a math and science competition for middle school students.	Joshua Wentzel (born 1999) is a finalist in the 2013 Broadcom MASTERS, a math and science competition for middle school students, for his physical sciences project.
81205	coherence	Make the text more consistent: The highway began at a diamond interchange with I-70 and US-40 between Hays and Russell. US-40 run concurrently east -- west.	The highway began at a diamond interchange with I-70 and US-40, which run concurrently east -- west, between Hays and Russell.
81206	coherence	Make the text more cohesive: Kim Davis a math and science competition for middle school students. Kim Davis is a mentor of finalist in the 2014 Broadcom MASTERS.	Kim Davis, a mentor of finalist in the 2014 Broadcom MASTERS, a math and science competition for middle school students.
81207	coherence	Fix coherence of the sentence: Silver went to Japan's Miho Takagi in a time of 1: 54.55. Bronze went to Marrit Leenstra of the Netherlands in a time of 1.	Silver went to Japan's Miho Takagi in a time of 1: 54.55, while bronze went to Marrit Leenstra of the Netherlands in a time of 1.
81208	coherence	Improve the cohesiveness of the text: Heather Blonsky a math and science competition for middle-school students. Heather Blonsky is a mentor of a finalist in the 2011 Broadcom MASTERS.	Heather Blonsky, a mentor of a finalist in the 2011 Broadcom MASTERS, a math and science competition for middle-school students.
81209	clarity	Clarify: This has been widely demonstrated for English using contextualized word representations such as OpenAI GPT (Radford et al., 2018 ), BERT (Devlin et al., 2019 ), or XLNet (Yang et al., 2019b).	This has been widely demonstrated for English using contextualized word representations such as OpenAI GPT (Radford et al., 2018 ), BERT (Devlin et al., 2019; Yang et al., 2019b).
81210	clarity	Use clearer wording: We apply our French language models to complex NLP tasks (natural language inference, parsing, word sense disambiguation) and show that most of the time they outperform other pre-training approaches.	We apply our French language models to diverse NLP tasks (natural language inference, parsing, word sense disambiguation) and show that most of the time they outperform other pre-training approaches.
81211	clarity	Make the text more understandable: The method was not able to utilize the available huge amount of monolingual data because of the inability of models to differentiate between the authentic and synthetic parallel data.	The method was not able to utilize the available huge amount of existing monolingual data because of the inability of models to differentiate between the authentic and synthetic parallel data.
81212	clarity	Rewrite this sentence clearly: The method was not able to utilize the available huge amount of monolingual data because of the inability of models to differentiate between the authentic and synthetic parallel data.	The method was not able to utilize the available huge amount of monolingual data because of the inability of models to differentiate between the authentic and synthetic parallel data during training.
81213	clarity	Clarify this sentence: The approach-tag-less back-translation-trains the model on the synthetic data and fine-tunes it on the authentic data. Experiments have shown the approach to outperform the baseline and standard back-translation by 4.0 and 0.7 BLEU respectively on low resource English-Vietnamese NMT. While the ne...	The approach-tag-less back-translation approaches on low resource English-Vietnamese NMT. While the need for tagging (noising) the dataset has been removed, the technique outperformed tagged back-translation by 0.4 BLEU.
81214	clarity	Clarify this sentence: Experiments have shown the approach to outperform the baseline and standard back-translation by 4.0 and 0.7 BLEU respectively on low resource English-Vietnamese NMT. While the need for tagging (noising) the dataset has been removed, the technique outperformed tagged back-translation by 0.4 BLEU. ...	Experiments have shown the approach to outperform the baseline and standard back-translation by 4.0 and 0.7 BLEU respectively on low resource English-Vietnamese and English-German neural machine translation.
81215	clarity	Make the sentence clearer: While deep learning methods have been applied to classification-based approaches, current similarity-based methods only embody static notions of similarity.	While deep learning methods have been applied to classification-based approaches, applications to similarity-based methods only embody static notions of similarity.
81216	clarity	Rewrite this sentence for readability: Siamese networks have been used to develop learned notions of similarity in one-shot image tasks, and also for tasks of semantic relatedness in NLP.	Siamese networks have been used to develop learned notions of similarity in one-shot image tasks, and also for tasks of mostly semantic relatedness in NLP.
81217	clarity	Rewrite this sentence clearly: Classification-based approaches work well for small numbers of candidate authors, but only similarity-based methods are applicable for larger numbers of authors or for authors beyond the training set. While deep learning methodshave been applied to classification-based approaches, applica...	Classification-based approaches work well for small numbers of candidate authors, but only similarity-based methods are applicable for larger numbers of authors or for authors beyond the training set; these existing similarity-based applications have been limited, and most similarity-based methods only embody static no...
81218	clarity	Clarify the sentence: We examine their application to the stylistic task of authorship attribution on datasets with large numbers of authors, looking at multiple energy functions and neural network architectures, and show that they can substantially outperform both classification- and existing similarity-based approach...	We examine their application to the stylistic task of authorship attribution on datasets with large numbers of authors, looking at multiple energy functions and neural network architectures, and show that they can substantially outperform previous approaches.
81219	clarity	Write a better readable version of the sentence: While many algorithms exploit this fact in summary generation, it has a detrimental effect on teaching the model to discriminate and extract important information.	While many algorithms exploit this fact in summary generation, it has a detrimental effect on teaching the model to discriminate and extract important information in general.
81220	clarity	Clarification: We propose that the lead bias can be leveraged in a simple and effective way in our favor to pretrain abstractive news summarization models on large-scale unlabeled corpus: predicting the leading sentences using the rest of an article.	We propose that the lead bias can be leveraged in a simple and effective way to pre-train abstractive news summarization models on large-scale unlabeled corpus: predicting the leading sentences using the rest of an article.
81221	clarity	Rewrite this sentence for readability: We propose that the lead bias can be leveraged in a simple and effective way in our favor to pretrain abstractive news summarization models on large-scale unlabeled corpus: predicting the leading sentences using the rest of an article.	We propose that the lead bias can be leveraged in a simple and effective way in our favor to pretrain abstractive news summarization models on large-scale unlabeled news corpora: predicting the leading sentences using the rest of an article.
81222	clarity	Write a clarified version of the sentence: Via careful data cleaning and filtering, our transformer-based pretrained model without any finetuning achieves remarkable results over various news summarization tasks.	We collect a massive news corpus and conduct data cleaning and filtering, our transformer-based pretrained model without any finetuning achieves remarkable results over various news summarization tasks.
81223	clarity	Make this sentence more readable: Lead bias is a common phenomenon in news summarization, where early parts of an article often contain the most salient information.	A typical journalistic convention in news articles is to deliver the most salient information.
81224	clarity	Make the text more understandable: Lead bias is a common phenomenon in news summarization, where early parts of an article often contain the most salient information. While many algorithms exploit this fact in summary generation, it has a detrimental effect on teaching the model to discriminate and extract important in...	Lead bias is a common phenomenon in news summarization, where early parts of an article often contain the most salient information in the beginning, also known as the lead bias. While this phenomenon can be exploited in generating a summary, it has a detrimental effect on teaching the model to discriminate and extract ...
81225	clarity	Write a clearer version for the sentence: While many algorithms exploit this fact in summary generation, it has a detrimental effect on teaching the model to discriminate and extract important information in general.	While many algorithms exploit this fact in summary generation, it has a detrimental effect on teaching a model to discriminate and extract important information in general.
81226	clarity	Rewrite this sentence for readability: We then apply the proposed self-supervised pre-training to existing generation models BART and T5 for domain adaptation.	We then apply self-supervised pre-training to existing generation models BART and T5 for domain adaptation.
81227	clarity	Write a clarified version of the sentence: We also leverage the image features to incorporate the style information of words in LayoutLM.	We also leverage the image features to incorporate the visual information of words in LayoutLM.
81228	clarity	Rewrite this sentence for clarity: In this paper, we develop variants of layer-wise relevance backpropagation (LRP) and gradient backpropagation, tailored to image captioning with attention. The result provides simultaneously pixel-wise image explanation and linguistic explanation for each word in the captions.	In this paper, we develop variants of layer-wise relevance backpropagation (LRP) and gradient backpropagation, tailored to image captioning models with attention mechanisms. The explanations provide simultaneously pixel-wise image explanation and linguistic explanation for each word in the captions.
81229	clarity	Make the sentence clear: We show that given a word in the caption to be explained, explanation methods such as LRP reveal supporting and opposing pixels as well as words.	We show that given a word in the caption to be explained, explanation methods such as LRP reveal supporting and opposing pixels as well as preceding words.
81230	clarity	Improve this sentence for readability: We show that explanation methods, firstly, correlate to object locations with higher precision than attention, secondly, are able to identify object words that are unsupported by image content, and thirdly, provide guidance to debias and improve the model.	We show that explanation methods, firstly, correlate to object locations with higher precision than attention, secondly, are able to identify object words that are unsupported by image content, and thirdly, provide guidance to improve and de-bias the model.
81231	clarity	Clarify: Results are reported for image captioning using two different attention models trained with Flickr30K and MSCOCO2017 datasets.	Results are reported using two different attention models trained with Flickr30K and MSCOCO2017 datasets.
81232	clarity	Rewrite this sentence for readability: Results are reported for image captioning using two different attention models trained with Flickr30K and MSCOCO2017 datasets.	Results are reported for image captioning using two different image captioning attention models trained with Flickr30K and MSCOCO2017 datasets.
81233	clarity	Make this sentence better readable: This paper explains predictions of image captioning models with attention mechanisms beyond visualizing the attention itself.	This paper interprets the predictions of image captioning models with attention mechanisms beyond visualizing the attention itself.
81234	clarity	Clarification: In this paper, we develop variants of layer-wise relevance backpropagation (LRP) and gradient backpropagation, tailored to image captioning models with attention mechanisms.	In this paper, we develop variants of layer-wise relevance propagation (LRP) and gradient backpropagation, tailored to image captioning models with attention mechanisms.
81235	clarity	Make this sentence better readable: In this paper, we develop variants of layer-wise relevance backpropagation (LRP) and gradient backpropagation, tailored to image captioning models with attention mechanisms.	In this paper, we develop variants of layer-wise relevance backpropagation (LRP) and gradient-based explanation methods, tailored to image captioning models with attention mechanisms.
81236	clarity	Make this easier to read: The explanations provide simultaneously pixel-wise image explanation and linguistic explanation for each word in the captions. We show that given a word in the caption to be explained, explanation methods such as LRP reveal supporting and opposing pixels as well as preceding words. We compare ...	We compare the interpretability of attention heatmaps systematically against those computed with explanation methods such as LRP, Grad-CAM and Guided Grad-CAM.
81237	clarity	Clarify this sentence: We compare the properties of attention heatmaps systematically against those computed with explanation methods such as LRP, Grad-CAM and Guided Grad-CAM.	We compare the properties of attention heatmaps systematically against the explanations computed with explanation methods such as LRP, Grad-CAM and Guided Grad-CAM.
81238	clarity	Rewrite this sentence clearly: Experimental results show ProphetNet achieves the best performance on both abstractive summarization and question generation tasks compared to the models using the same base scale pre-training dataset. For the large scale dataset pre-training, ProphetNet achieves new state-of-the-art resu...	Experimental results show ProphetNet achieves the best performance on both abstractive summarization and question generation tasks. Experimental results show that ProphetNet achieves new state-of-the-art results on Gigaword and comparable results on CNN/DailyMail using only about 1/5 pre-training epochs of the previous...
81239	clarity	Write a clarified version of the sentence: For the large scale dataset pre-training, ProphetNet achieves new state-of-the-art results on Gigaword and comparable results on CNN/DailyMail using only about 1/5 pre-training epochs of the previous model.	For the large scale dataset pre-training, ProphetNet achieves new state-of-the-art results on all these datasets compared to the models using the same scale pre-training epochs of the previous model.