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Negation is a common everyday phenomena and has been a consistent area of weakness for language models (LMs).
Learning the difference that makes a difference with counterfactually-augmented data
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Natural language information retrieval: Trec-3 report
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The ambiguity of negation in natural language queries to information retrieval systems
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Evaluating models’ local decision boundaries via contrast sets
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Sentiment classification considering negation and contrast transition
Shoushan Li and Chu-Ren Huang. 2009 · 2009
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Scikit-learn: Machine learning in Python
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Daniel Cer, Mona Diab, Eneko Agirre, Iñigo Lopez-Gazpio, and Lucia Specia. 2017 · 2017
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Neural networks for negation cue detection in Chinese
Hangfeng He, Federico Fancellu, and Bonnie Webber. 2017 · 2017
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Transforming question answering datasets into natural language inference datasets
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Retrieval of the best counterargument without prior topic knowledge
Henning Wachsmuth, Shahbaz Syed, and Benno Stein. 2018 · 2018
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A broad-coverage challenge corpus for sentence understanding through inference
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Statute law information retrieval and entailment
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Nils Reimers and Iryna Gurevych. 2019 · 2019
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Allyson Ettinger. 2020 · 2020
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Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2020
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Colbert: Efficient and effective passage search via contextualized late interaction over BERT
Omar Khattab and Matei Zaharia. 2020 · 2020
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Retrieval-augmented generation for knowledge-intensive NLP tasks
Unsupervised corpus aware language model pre-training for dense passage retrieval
Luyu Gao and Jamie Callan. 2022 · 2022
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An analysis of negation in natural language understanding corpora
Md Mosharaf Hossain, Dhivya Chinnappa, and Eduardo Blanco. 2022 · 2022
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An efficiency study for splade models
Carlos Lassance and Stéphane Clinchant. 2022 · 2022
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ABNIRML: Analyzing the behavior of neural IR models
Sean MacAvaney, Sergey Feldman, Nazli Goharian, Doug Downey, and Arman Cohan. 2022 · 2022
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Inverse scaling prize: First round winners
Ian McKenzie, Alexander Lyzhov, Alicia Parrish, Ameya Prabhu, Aaron Mueller, Najoung Kim, Sam Bowman, and Ethan Perez. 2022 · 2022
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SBERT studies meaning representations: Decomposing sentence embeddings into explainable semantic features
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Patrick S. H. Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, and Douwe Kiela. 2020 · 2020
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Document ranking with a pretrained sequence-to-sequence model
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A multilingual benchmark for probing negation-awareness with minimal pairs
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Gautier Izacard and Edouard Grave. 2021 · 2021
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RocketQA: An optimized training approach to dense passage retrieval for open-domain question answering
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RocketQAv2: A joint training method for dense passage retrieval and passage re-ranking
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Juri Opitz and Anette Frank. 2022 · 2022
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Evaluating the robustness of retrieval pipelines with query variation generators
Gustavo Penha, Arthur Câmara, and Claudia Hauff. 2022 · 2022
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The role of complex nlp in transformers for text ranking
David Rau and Jaap Kamps. 2022 · 2022
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CONDAQA: A contrastive reading comprehension dataset for reasoning about negation
Abhilasha Ravichander, Matt Gardner, and Ana Marasovic. 2022 · 2022
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ColBERTv2: Effective and efficient retrieval via lightweight late interaction
Keshav Santhanam, Omar Khattab, Jon Saad-Falcon, Christopher Potts, and Matei Zaharia. 2022b · 2022
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Transformer memory as a differentiable search index
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Inverse scaling can become u-shaped
Jason Wei, Yi Tay, and Quoc V Le. 2022 · 2022
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Representation biases in sentence transformers
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How does generative retrieval scale to millions of passages?
Ronak Pradeep, Kai Hui, Jai Gupta, Adam D Lelkes, Honglei Zhuang, Jimmy Lin, Donald Metzler, and Vinh Q Tran. 2023 · 2023
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