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In recent times, large language models (LLMs) have shown impressive performance on various document-level tasks such as document classification, summarization, and question-answering.
Language models are few-shot learners
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Language models are few-shot learners
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Anomalous information triggers questions when adults solve quantitative problems and comprehend stories
Arthur C Graesser and Cathy L McMahen. 1993 · 1993
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Entailment, intensionality and text understanding
Cleo Condoravdi, Dick Crouch, Valeria de Paiva, Reinhard Stolle, and Daniel G. Bobrow. 2003 · 2003
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The pascal recognising textual entailment challenge
Ido Dagan, Oren Glickman, and Bernardo Magnini. 2005 · 2005
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Negation, contrast and contradiction in text processing
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Finding contradictions in text
Marie-Catherine de Marneffe, Anna N. Rafferty, and Christopher D. Manning. 2008 · 2008
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Finding conflicting statements in the biomedical literature
Farzaneh Sarafraz. 2012 · 2012
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A large annotated corpus for learning natural language inference
Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015 · 2015
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Teaching machines to read and comprehend
Karl Moritz Hermann, Tomas Kocisky, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom. 2015 · 2015
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The detection of contradictory claims in biomedical abstracts
Abdulaziz Alamri. 2016 · 2016
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A corpus of potentially contradictory research claims from cardiovascular research abstracts
Abdulaziz Alamri and Mark Stevenson. 2016 · 2016
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Monolingual social media datasets for detecting contradiction and entailment
Piroska Lendvai, Isabelle Augenstein, Kalina Bontcheva, and Thierry Declerck. 2016 · 2016
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Contradiction detection for rumorous claims
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Pointer sentinel mixture models
Stephen Merity, Caiming Xiong, James Bradbury, and Richard Socher. 2016 · 2016
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The narrativeqa reading comprehension challenge
Tomáš Kočiskỳ, Jonathan Schwarz, Phil Blunsom, Chris Dyer, Karl Moritz Hermann, Gábor Melis, and Edward Grefenstette. 2018 · 2018
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A computational approach to finding contradictions in user opinionated text
Chuqin Li, Xi Niu, Ahmad Al-Doulat, and Noseong Park. 2018 · 2018
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Towards a characterization of apparent contradictions in the biomedical literature using context analysis
Graciela Rosemblat, Marcelo Fiszman, Dongwook Shin, and Halil Kilicoglu. 2019 · 2019
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Topological analysis of contradictions in text
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CDConv: A benchmark for contradiction detection in Chinese conversations
Chujie Zheng, Jinfeng Zhou, Yinhe Zheng, Libiao Peng, Zhen Guo, Wenquan Wu, Zheng-Yu Niu, Hua Wu, and Minlie Huang. 2022 · 2022
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Rohan Anil, Andrew M Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, et al. 2023 · 2023
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Contradiction detection in financial reports
Tobias Deußer, Maren Pielka, Lisa Pucknat, Basil Jacob, Tim Dilmaghani, Mahdis Nourimand, Bernd Kliem, Rüdiger Loitz, Christian Bauckhage, and Rafet Sifa. 2023 · 2023
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Is GPT-3 a good data annotator?
Bosheng Ding, Chengwei Qin, Linlin Liu, Yew Ken Chia, Boyang Li, Shafiq Joty, and Lidong Bing. 2023 · 2023
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Wikicontradiction: Detecting self-contradiction articles on wikipedia
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I like fish, especially dolphins: Addressing contradictions in dialogue modeling
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Want to reduce labeling cost? gpt-3 can help
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Palm: Scaling language modeling with pathways
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Improving bot response contradiction detection via utterance rewriting
Di Jin, Sijia Liu, Yang Liu, and Dilek Hakkani-Tur. 2022 · 2022
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DocInfer: Document-level natural language inference using optimal evidence selection
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Using contradictions improves question answering systems
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Self-contradictory hallucinations of large language models: Evaluation, detection and mitigation
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Document-level machine translation with large language models
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Benchmarking large language models for news summarization
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