Datasets:

joyheyueya
/

0505_train_final_pair100k_rl_rephrase

Modalities:

Formats:

Size:

Libraries:

Dataset card Data Studio Files Files and versions

Dataset Viewer

Auto-converted to Parquet Duplicate

Split (1)

train · 100k rows

abstracts sequencelengths 2 2	id_1 stringlengths 9 14	id_2 stringlengths 9 14	pair_id stringlengths 20 25	generation_prompt stringlengths 1.27k 4.48k	joint_prompt sequencelengths 2 2	paper1_prompt sequencelengths 2 2	paper2_prompt sequencelengths 2 2	no_context_prompt sequencelengths 2 2
[ [ "The ever-growing diversity of pre-training text corpora has equipped language\nmodels with generalization capabilities across various downstream tasks.\nHowever, such diverse datasets are often too large for academic budgets; hence,\nmost research on Transformer architectures, training procedures, optimizers...	2304.08442	2205.12491	2304.08442_2205.12491	You are a helpful AI Assistant that provides well-reasoned and detailed responses. Identify an insight that emerges only when both papers are considered together—something not obvious from either paper alone. You first think about the reasoning process as an internal monologue (1-3 sentences) and then provide the user ...	[ "Paper 1:\nThe ever-growing diversity of pre-training text corpora has equipped language\nmodels with generalization capabilities across various downstream tasks.\nHowever, such diverse datasets are often too large for academic budgets; hence,\nmost research on Transformer architectures, training procedures, optimi...	[ "Paper:\nThe ever-growing diversity of pre-training text corpora has equipped language\nmodels with generalization capabilities across various downstream tasks.\nHowever, such diverse datasets are often too large for academic budgets; hence,\nmost research on Transformer architectures, training procedures, optimize...	[ "Paper:\nRecent relation extraction (RE) works have shown encouraging improvements by\nconducting contrastive learning on silver labels generated by distant\nsupervision before fine-tuning on gold labels. Existing methods typically\nassume all these silver labels are accurate and treat them equally; however,\ndista...	[ "Here's an insight: ", "It’s established that: " ]
[ [ "Large language models (LLMs) have demonstrated remarkable prowess in language\nunderstanding and generation. Advancing from foundation LLMs to\ninstructionfollowing LLMs, instruction tuning plays a vital role in aligning\nLLMs to human preferences. However, the existing LLMs are usually focused on\nEnglish, ...	2306.10968	2206.11349	2306.10968_2206.11349	You are a helpful AI Assistant that provides well-reasoned and detailed responses. Identify an insight that emerges only when both papers are considered together—something not obvious from either paper alone. You first think about the reasoning process as an internal monologue (1-3 sentences) and then provide the user ...	[ "Paper 1:\nLarge language models (LLMs) have demonstrated remarkable prowess in language\nunderstanding and generation. Advancing from foundation LLMs to\ninstructionfollowing LLMs, instruction tuning plays a vital role in aligning\nLLMs to human preferences. However, the existing LLMs are usually focused on\nEngli...	[ "Paper:\nLarge language models (LLMs) have demonstrated remarkable prowess in language\nunderstanding and generation. Advancing from foundation LLMs to\ninstructionfollowing LLMs, instruction tuning plays a vital role in aligning\nLLMs to human preferences. However, the existing LLMs are usually focused on\nEnglish...	[ "Paper:\nRecent works have shown that attaching prompts to the input is effective at\nconditioning Language Models (LM) to perform specific tasks. However, prompts\nare always included in the input text during inference, thus incurring\nsubstantial computational and memory overhead. Also, there is currently no\nstr...	[ "Here's an insight: ", "It’s established that: " ]
[ [ "Several pre-training objectives, such as masked language modeling (MLM), have\nbeen proposed to pre-train language models (e.g. BERT) with the aim of learning\nbetter language representations. However, to the best of our knowledge, no\nprevious work so far has investigated how different pre-training objectiv...	2203.10415	2210.14389	2203.10415_2210.14389	You are a helpful AI Assistant that provides well-reasoned and detailed responses. Identify an insight that emerges only when both papers are considered together—something not obvious from either paper alone. You first think about the reasoning process as an internal monologue (1-3 sentences) and then provide the user ...	[ "Paper 1:\nSeveral pre-training objectives, such as masked language modeling (MLM), have\nbeen proposed to pre-train language models (e.g. BERT) with the aim of learning\nbetter language representations. However, to the best of our knowledge, no\nprevious work so far has investigated how different pre-training obje...	[ "Paper:\nSeveral pre-training objectives, such as masked language modeling (MLM), have\nbeen proposed to pre-train language models (e.g. BERT) with the aim of learning\nbetter language representations. However, to the best of our knowledge, no\nprevious work so far has investigated how different pre-training object...	[ "Paper:\nResearch on Korean grammatical error correction (GEC) is limited, compared to\nother major languages such as English. We attribute this problematic\ncircumstance to the lack of a carefully designed evaluation benchmark for\nKorean GEC. In this work, we collect three datasets from different sources\n(Kor-La...	[ "Here's an insight: ", "It’s established that: " ]
[ [ "Given a natural language statement, how to verify its veracity against a\nlarge-scale textual knowledge source like Wikipedia? Most existing neural\nmodels make predictions without giving clues about which part of a false claim\ngoes wrong. In this paper, we propose LOREN, an approach for interpretable fact\...	2012.13577	2302.06426	2012.13577_2302.06426	You are a helpful AI Assistant that provides well-reasoned and detailed responses. Identify an insight that emerges only when both papers are considered together—something not obvious from either paper alone. You first think about the reasoning process as an internal monologue (1-3 sentences) and then provide the user ...	[ "Paper 1:\nGiven a natural language statement, how to verify its veracity against a\nlarge-scale textual knowledge source like Wikipedia? Most existing neural\nmodels make predictions without giving clues about which part of a false claim\ngoes wrong. In this paper, we propose LOREN, an approach for interpretable f...	[ "Paper:\nGiven a natural language statement, how to verify its veracity against a\nlarge-scale textual knowledge source like Wikipedia? Most existing neural\nmodels make predictions without giving clues about which part of a false claim\ngoes wrong. In this paper, we propose LOREN, an approach for interpretable fac...	[ "Paper:\nLinguistic ambiguity is and has always been one of the main challenges in\nNatural Language Processing (NLP) systems. Modern Transformer architectures\nlike BERT, T5 or more recently InstructGPT have achieved some impressive\nimprovements in many NLP fields, but there is still plenty of work to do.\nMotiva...	[ "Here's an insight: ", "It’s established that: " ]
[ [ "We propose DiffCSE, an unsupervised contrastive learning framework for\nlearning sentence embeddings. DiffCSE learns sentence embeddings that are\nsensitive to the difference between the original sentence and an edited\nsentence, where the edited sentence is obtained by stochastically masking out\nthe origin...	2204.10298	2211.05172	2204.10298_2211.05172	You are a helpful AI Assistant that provides well-reasoned and detailed responses. Identify an insight that emerges only when both papers are considered together—something not obvious from either paper alone. You first think about the reasoning process as an internal monologue (1-3 sentences) and then provide the user ...	[ "Paper 1:\nWe propose DiffCSE, an unsupervised contrastive learning framework for\nlearning sentence embeddings. DiffCSE learns sentence embeddings that are\nsensitive to the difference between the original sentence and an edited\nsentence, where the edited sentence is obtained by stochastically masking out\nthe or...	[ "Paper:\nWe propose DiffCSE, an unsupervised contrastive learning framework for\nlearning sentence embeddings. DiffCSE learns sentence embeddings that are\nsensitive to the difference between the original sentence and an edited\nsentence, where the edited sentence is obtained by stochastically masking out\nthe orig...	[ "Paper:\nSelf-supervised learning (SSL) methods such as WavLM have shown promising\nspeech separation (SS) results in small-scale simulation-based experiments. In\nthis work, we extend the exploration of the SSL-based SS by massively scaling\nup both the pre-training data (more than 300K hours) and fine-tuning data...	[ "Here's an insight: ", "It’s established that: " ]
[ [ "When humans design cost or goal specifications for robots, they often produce\nspecifications that are ambiguous, underspecified, or beyond planners' ability\nto solve. In these cases, corrections provide a valuable tool for\nhuman-in-the-loop robot control. Corrections might take the form of new goal\nspeci...	2204.05186	2303.10583	2204.05186_2303.10583	You are a helpful AI Assistant that provides well-reasoned and detailed responses. Identify an insight that emerges only when both papers are considered together—something not obvious from either paper alone. You first think about the reasoning process as an internal monologue (1-3 sentences) and then provide the user ...	[ "Paper 1:\nWhen humans design cost or goal specifications for robots, they often produce\nspecifications that are ambiguous, underspecified, or beyond planners' ability\nto solve. In these cases, corrections provide a valuable tool for\nhuman-in-the-loop robot control. Corrections might take the form of new goal\ns...	[ "Paper:\nWhen humans design cost or goal specifications for robots, they often produce\nspecifications that are ambiguous, underspecified, or beyond planners' ability\nto solve. In these cases, corrections provide a valuable tool for\nhuman-in-the-loop robot control. Corrections might take the form of new goal\nspe...	[ "Paper:\nIn the early stages of the design process, designers explore opportunities by\ndiscovering unmet needs and developing innovative concepts as potential\nsolutions. From a human-centered design perspective, designers must develop\nempathy with people to truly understand their needs. However, developing\nempa...	[ "Here's an insight: ", "It’s established that: " ]
[ [ "Pre-training methods with contrastive learning objectives have shown\nremarkable success in dialog understanding tasks. However, current contrastive\nlearning solely considers the self-augmented dialog samples as positive samples\nand treats all other dialog samples as negative ones, which enforces dissimila...	2209.06638	2205.15868	2209.06638_2205.15868	You are a helpful AI Assistant that provides well-reasoned and detailed responses. Identify an insight that emerges only when both papers are considered together—something not obvious from either paper alone. You first think about the reasoning process as an internal monologue (1-3 sentences) and then provide the user ...	[ "Paper 1:\nPre-training methods with contrastive learning objectives have shown\nremarkable success in dialog understanding tasks. However, current contrastive\nlearning solely considers the self-augmented dialog samples as positive samples\nand treats all other dialog samples as negative ones, which enforces dissi...	[ "Paper:\nPre-training methods with contrastive learning objectives have shown\nremarkable success in dialog understanding tasks. However, current contrastive\nlearning solely considers the self-augmented dialog samples as positive samples\nand treats all other dialog samples as negative ones, which enforces dissimi...	[ "Paper:\nLarge-scale pretrained transformers have created milestones in text (GPT-3)\nand text-to-image (DALL-E and CogView) generation. Its application to video\ngeneration is still facing many challenges: The potential huge computation cost\nmakes the training from scratch unaffordable; The scarcity and weak rele...	[ "Here's an insight: ", "It’s established that: " ]
[ [ "Recent progress in language model pre-training has achieved a great success\nvia leveraging large-scale unstructured textual data. However, it is still a\nchallenge to apply pre-training on structured tabular data due to the absence\nof large-scale high-quality tabular data. In this paper, we propose TAPEX t...	2107.07653	2204.12679	2107.07653_2204.12679	You are a helpful AI Assistant that provides well-reasoned and detailed responses. Identify an insight that emerges only when both papers are considered together—something not obvious from either paper alone. You first think about the reasoning process as an internal monologue (1-3 sentences) and then provide the user ...	[ "Paper 1:\nRecent progress in language model pre-training has achieved a great success\nvia leveraging large-scale unstructured textual data. However, it is still a\nchallenge to apply pre-training on structured tabular data due to the absence\nof large-scale high-quality tabular data. In this paper, we propose TAP...	[ "Paper:\nRecent progress in language model pre-training has achieved a great success\nvia leveraging large-scale unstructured textual data. However, it is still a\nchallenge to apply pre-training on structured tabular data due to the absence\nof large-scale high-quality tabular data. In this paper, we propose TAPEX...	[ "Paper:\nDocument-level relation extraction (DocRE) aims to determine the relation\nbetween two entities from a document of multiple sentences. Recent studies\ntypically represent the entire document by sequence- or graph-based models to\npredict the relations of all entity pairs. However, we find that such a model...	[ "Here's an insight: ", "It’s established that: " ]
[ [ "Recent advances in NLP are brought by a range of large-scale pretrained\nlanguage models (PLMs). These PLMs have brought significant performance gains\nfor a range of NLP tasks, circumventing the need to customize complex designs\nfor specific tasks. However, most current work focus on finetuning PLMs on a\n...	2211.03154	2204.06518	2211.03154_2204.06518	You are a helpful AI Assistant that provides well-reasoned and detailed responses. Identify an insight that emerges only when both papers are considered together—something not obvious from either paper alone. You first think about the reasoning process as an internal monologue (1-3 sentences) and then provide the user ...	[ "Paper 1:\nRecent advances in NLP are brought by a range of large-scale pretrained\nlanguage models (PLMs). These PLMs have brought significant performance gains\nfor a range of NLP tasks, circumventing the need to customize complex designs\nfor specific tasks. However, most current work focus on finetuning PLMs on...	[ "Paper:\nRecent advances in NLP are brought by a range of large-scale pretrained\nlanguage models (PLMs). These PLMs have brought significant performance gains\nfor a range of NLP tasks, circumventing the need to customize complex designs\nfor specific tasks. However, most current work focus on finetuning PLMs on a...	[ "Paper:\nText-based communication is highly favoured as a communication method,\nespecially in business environments. As a result, it is often abused by sending\nmalicious messages, e.g., spam emails, to deceive users into relaying personal\ninformation, including online accounts credentials or banking details. For...	[ "Here's an insight: ", "It’s established that: " ]
[ [ "Adapter-tuning is a paradigm that transfers a pretrained language model to\ndownstream tasks by adding and tuning a small number of new parameters.\nPreviously proposed adapter architectures are all feed-forward neural networks.\nIn this paper, we investigate the effectiveness of using tiny-attention --\ni.e...	2211.01979	2306.04050	2211.01979_2306.04050	You are a helpful AI Assistant that provides well-reasoned and detailed responses. Identify an insight that emerges only when both papers are considered together—something not obvious from either paper alone. You first think about the reasoning process as an internal monologue (1-3 sentences) and then provide the user ...	[ "Paper 1:\nAdapter-tuning is a paradigm that transfers a pretrained language model to\ndownstream tasks by adding and tuning a small number of new parameters.\nPreviously proposed adapter architectures are all feed-forward neural networks.\nIn this paper, we investigate the effectiveness of using tiny-attention --\...	[ "Paper:\nAdapter-tuning is a paradigm that transfers a pretrained language model to\ndownstream tasks by adding and tuning a small number of new parameters.\nPreviously proposed adapter architectures are all feed-forward neural networks.\nIn this paper, we investigate the effectiveness of using tiny-attention --\ni...	[ "Paper:\nWe provide new estimates of an asymptotic upper bound on the entropy of\nEnglish using the large language model LLaMA-7B as a predictor for the next\ntoken given a window of past tokens. This estimate is significantly smaller\nthan currently available estimates in \\cite{cover1978convergent},\n\\cite{lutat...	[ "Here's an insight: ", "It’s established that: " ]

End of preview. Expand in Data Studio

README.md exists but content is empty.

Downloads last month: 11

Number of rows:

Total file size: