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While recent advancements in Neural Ranking Models have resulted in significant improvements over traditional statistical retrieval models, it is generally acknowledged that the use of large neural architectures and the application of complex language models in Information Retrieval (IR) have reduced the transparency of retrieval methods.
Language Models are Few-Shot Learners. In Advances in Neural Information Processing Systems , H. Larochelle, M. Ranzato, R. Hadsell, M.F. Balcan, and H. Lin (Eds.), Vol. 33. Curran Associates, Inc., 1877–1901
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 1901
Earlier work this paper cites.
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2023 · 1910
Earlier work this paper cites.
Explain Like I Am BM25: Interpreting a Dense Model’s Ranked-List with a Sparse Approximation. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (Taipei, Taiwan) (SIGIR ’23) . Association for Computing Machinery, New York, NY, USA, 1976–1980
Michael Llordes, Debasis Ganguly, Sumit Bhatia, and Chirag Agarwal. 2023 · 1980
Earlier work this paper cites.
A Formal Study of Information Retrieval Heuristics. In Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (Sheffield, United Kingdom) (SIGIR ’04) . Association for Computing Machinery, New York, NY, USA, 49–56
Hui Fang, Tao Tao, and ChengXiang Zhai. 2004 · 2004
Earlier work this paper cites.
An Exploration of Axiomatic Approaches to Information Retrieval. In Proceedings of SIGIR 2005 . 480–487
Hui Fang and ChengXiang Zhai. 2005 · 2005
Earlier work this paper cites.
Distilling Dense Representations for Ranking using Tightly-Coupled Teachers
Sheng-Chieh Lin, Jheng-Hong Yang, and Jimmy Lin. 2020 · 2010
Earlier work this paper cites.
A similarity measure for indefinite rankings
William Webber, Alistair Moffat, and Justin Zobel. 2010 · 2010
Earlier work this paper cites.
Learning Word Vectors for Sentiment Analysis. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies . Association for Computational Linguistics, Portland, Oregon, USA, 142–150
Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. 2011 · 2011
Earlier work this paper cites.
Xiang Zhang, Junbo Zhao, and Yann LeCun. 2015 · 2015
Earlier work this paper cites.
Axiomatic Result Re-Ranking. In Proc. of CIKM 2016 . 721–730
Matthias Hagen, Michael Völske, Steve Göring, and Benno Stein. 2016 · 2016
Earlier work this paper cites.
"Why Should I Trust You?": Explaining the Predictions of Any Classifier. In Proc.of SIGKDD 2016 . 1135–1144
Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin. 2016 · 2016
Earlier work this paper cites.
Axiomatic Thinking for Information Retrieval: And Related Tasks. In Proc. of SIGIR 2017 . 1419–1420
Enrique Amigó, Hui Fang, Stefano Mizzaro, and ChengXiang Zhai. 2017 · 2017
Earlier work this paper cites.
Learning Important Features Through Propagating Activation Differences. In Proceedings of the 34th International Conference on Machine Learning, ICML 2017, Sydney, NSW, Australia, 6-11 August 2017 (Proceedings of Machine Learning Research, Vol. 70) , Doina Precup and Yee Whye Teh (Eds.). PMLR, 3145–3153
Avanti Shrikumar, Peyton Greenside, and Anshul Kundaje. 2017 · 2017
Earlier work this paper cites.
Axiomatic Attribution for Deep Networks. In Proc of ICML 2017 (Proceedings of Machine Learning Research) . 3319–3328
Mukund Sundararajan, Ankur Taly, and Qiqi Yan. 2017 · 2017
Earlier work this paper cites.
Anserini: Enabling the Use of Lucene for Information Retrieval Research. In Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (Shinjuku, Tokyo, Japan) (SIGIR ’17) . Association for Computing Machinery, New York, NY, USA, 1253–1256
Peilin Yang, Hui Fang, and Jimmy Lin. 2017 · 2017
Earlier work this paper cites.
BERT: Pre-training of deep bidirectional transformers for language understanding. In NAACL-HLT
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Earlier work this paper cites.
EXS: Explainable Search Using Local Model Agnostic Interpretability. In Proc. of WSDM 2019 . 770–773
Jaspreet Singh and Avishek Anand. 2019 · 2019
Cited alongside, same era.
LIRME: Locally Interpretable Ranking Model Explanation. In Proc. of SIGIR 2019 . 1281–1284
Manisha Verma and Debasis Ganguly. 2019 · 2019
Cited alongside, same era.
Generalized linear rule models. In International conference on machine learning . PMLR, 6687–6696
Dennis Wei, Sanjeeb Dash, Tian Gao, and Oktay Gunluk. 2019 · 2019
Cited alongside, same era.
AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models
Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilović, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, and Yunfeng Zhang. 2020 · 2020
Cited alongside, same era.
Cross-Encoder for MS Marco
Nils Reimers. 2021 · 2021
Later among the works it cites.
Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval. In International Conference on Learning Representations
Lee Xiong, Chenyan Xiong, Ye Li, Kwok-Fung Tang, Jialin Liu, Paul N. Bennett, Junaid Ahmed, and Arnold Overwijk. 2021 · 2021
Later among the works it cites.
Explainable Information Retrieval: A Survey
Avishek Anand, Lijun Lyu, Maximilian Idahl, Yumeng Wang, Jonas Wallat, and Zijian Zhang. 2022 · 2022
Later among the works it cites.
Axiomatic Retrieval Experimentation with ir_axioms. In 45th International ACM Conference on Research and Development in Information Retrieval (SIGIR 2022) . ACM
Alexander Bondarenko, Maik Fröbe, Jan Heinrich Reimer, Benno Stein, Michael Völske, and Matthias Hagen. 2022 · 2022
Later among the works it cites.
PaLM: Scaling Language Modeling with Pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, and Noah Fiedel. 2022 · 2022
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Zhuyun Dai and Jamie Callan. 2020 · 2020
Cited alongside, same era.
ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT. In Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, SIGIR 2020, Virtual Event, China, July 25-30, 2020 . ACM, 39–48
Omar Khattab and Matei Zaharia. 2020 · 2020
Cited alongside, same era.
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks. In Advances in Neural Information Processing Systems , H. Larochelle, M. Ranzato, R. Hadsell, M.F. Balcan, and H. Lin (Eds.), Vol. 33. Curran Associates, Inc., 9459–9474
Patrick 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
Cited alongside, same era.
Declarative Experimentation inInformation Retrieval using PyTerrier. In Proceedings of ICTIR 2020
Craig Macdonald and Nicola Tonellotto. 2020 · 2020
Cited alongside, same era.
Document Ranking with a Pretrained Sequence-to-Sequence Model. In Findings of the Association for Computational Linguistics: EMNLP 2020 , Trevor Cohn, Yulan He, and Yang Liu (Eds.). Association for Computational Linguistics, Online, 708–718
Rodrigo Nogueira, Zhiying Jiang, Ronak Pradeep, and Jimmy Lin. 2020 · 2020
Cited alongside, same era.
Model agnostic interpretability of rankers via intent modelling. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (Barcelona, Spain) (FAT* ’20) . Association for Computing Machinery, New York, NY, USA, 618–628
Jaspreet Singh and Avishek Anand. 2020 · 2020
Cited alongside, same era.
AI Explainability 360 Toolkit. In Proceedings of the 3rd ACM India Joint International Conference on Data Science & Management of Data (8th ACM IKDD CODS & 26th COMAD) (Bangalore, India) (CODS-COMAD ’21) . Association for Computing Machinery, New York, NY, USA, 376–379
Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilović, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, and Yunfeng Zhang. 2021 · 2021
Cited alongside, same era.
Pyserini: A Python Toolkit for Reproducible Information Retrieval Research with Sparse and Dense Representations. In Proceedings of the 44th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021) . 2356–2362
Jimmy Lin, Xueguang Ma, Sheng-Chieh Lin, Jheng-Hong Yang, Ronak Pradeep, and Rodrigo Nogueira. 2021 · 2021
Cited alongside, same era.
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Training language models to follow instructions with human feedback
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul Christiano, Jan Leike, and Ryan Lowe. 2022 · 2022
Later among the works it cites.
Explainability of Text Processing and Retrieval Methods: A Critical Survey
Sourav Saha, Debapriyo Majumdar, and Mandar Mitra. 2022 · 2022
Later among the works it cites.
Explainable Information Retrieval. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (Taipei, Taiwan) (SIGIR ’23) . Association for Computing Machinery, New York, NY, USA, 3448–3451
Avishek Anand, Procheta Sen, Sourav Saha, Manisha Verma, and Mandar Mitra. 2023 · 2023
Later among the works it cites.
Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models
Bernd Bohnet, Vinh Q. Tran, Pat Verga, Roee Aharoni, Daniel Andor, Livio Baldini Soares, Massimiliano Ciaramita, Jacob Eisenstein, Kuzman Ganchev, Jonathan Herzig, Kai Hui, Tom Kwiatkowski, Ji Ma, Jianmo Ni, Lierni Sestorain Saralegui, Tal Schuster, William W. Cohen, Michael Collins, Dipanjan Das, Donald Metzler, Slav Petrov, and Kellie Webster. 2023 · 2023
Later among the works it cites.
Extractive Explanations for Interpretable Text Ranking
Jurek Leonhardt, Koustav Rudra, and Avishek Anand. 2023 · 2023
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Listwise Explanations for Ranking Models Using Multiple Explainers. In Advances in Information Retrieval , Jaap Kamps, Lorraine Goeuriot, Fabio Crestani, Maria Maistro, Hideo Joho, Brian Davis, Cathal Gurrin, Udo Kruschwitz, and Annalina Caputo (Eds.). Springer Nature Switzerland, Cham, 653–668
Lijun Lyu and Avishek Anand. 2023 · 2023
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LLaMA: Open and Efficient Foundation Language Models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurelien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample. 2023 · 2023
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A Critical Evaluation of Evaluations for Long-form Question Answering. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , Anna Rogers, Jordan Boyd-Graber, and Naoaki Okazaki (Eds.). Association for Computational Linguistics, Toronto, Canada, 3225–3245
Fangyuan Xu, Yixiao Song, Mohit Iyyer, and Eunsol Choi. 2023 · 2023
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Model Internals-based Answer Attribution for Trustworthy Retrieval-Augmented Generation. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing , Yaser Al-Onaizan, Mohit Bansal, and Yun-Nung Chen (Eds.). Association for Computational Linguistics, Miami, Florida, USA, 6037–6053
Jirui Qi, Gabriele Sarti, Raquel Fernández, and Arianna Bisazza. 2024 · 2024
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Causal Probing for Dual Encoders. In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (Boise, ID, USA) (CIKM ’24) . Association for Computing Machinery, New York, NY, USA, 2292–2303
Jonas Wallat, Hauke Hinrichs, and Avishek Anand. 2024 · 2024
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A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions
Lei Huang, Weijiang Yu, Weitao Ma, Weihong Zhong, Zhangyin Feng, Haotian Wang, Qianglong Chen, Weihua Peng, Xiaocheng Feng, Bing Qin, and Ting Liu. 2025 · 2025
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