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Recent efforts to address hallucinations in Large Language Models (LLMs) have focused on attributed text generation, which supplements generated texts with citations of supporting sources for post-generation fact-checking and corrections.
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Controlled crowdsourcing for high-quality QA-SRL annotation
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Bridging the structural gap between encoding and decoding for data-to-text generation
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Evaluating large language models trained on code
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Summary-source proposition-level alignment: Task, datasets and supervised baseline
Ori Ernst, Ori Shapira, Ramakanth Pasunuru, Michael Lepioshkin, Jacob Goldberger, Mohit Bansal, and Ido Dagan. 2021 · 2021
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Planning with learned entity prompts for abstractive summarization
Shashi Narayan, Yao Zhao, Joshua Maynez, Gonçalo Simões, Vitaly Nikolaev, and Ryan McDonald. 2021 · 2021
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Programming puzzles
Tal Schuster, Ashwin Kalyan, Alex Polozov, and Adam Kalai. 2021 · 2021
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Re-examining system-level correlations of automatic summarization evaluation metrics
Daniel Deutsch, Rotem Dror, and Dan Roth. 2022 · 2022
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On the origin of hallucinations in conversational models: Is it the datasets or the models?
Nouha Dziri, Sivan Milton, Mo Yu, Osmar Zaiane, and Siva Reddy. 2022 · 2022
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Proposition-level clustering for multi-document summarization
Ori Ernst, Avi Caciularu, Ori Shapira, Ramakanth Pasunuru, Mohit Bansal, Jacob Goldberger, and Ido Dagan. 2022 · 2022
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Gemini: A family of highly capable multimodal models
Gemini Team Google. 2023 · 2023
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Revisiting sentence union generation as a testbed for text consolidation
Eran Hirsch, Valentina Pyatkin, Ruben Wolhandler, Avi Caciularu, Asi Shefer, and Ido Dagan. 2023 · 2023
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Evaluating verifiability in generative search engines
Nelson Liu, Tianyi Zhang, and Percy Liang. 2023 · 2023
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A novel computational and modeling foundation for automatic coherence assessment
Aviya Maimon and Reut Tsarfaty. 2023 · 2023
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Selfcheckgpt: Zero-resource black-box hallucination detection for generative large language models
Potsawee Manakul, Adian Liusie, and Mark J. F. Gales. 2023 · 2023
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TRUE: Re-evaluating factual consistency evaluation
Or Honovich, Roee Aharoni, Jonathan Herzig, Hagai Taitelbaum, Doron Kukliansy, Vered Cohen, Thomas Scialom, Idan Szpektor, Avinatan Hassidim, and Yossi Matias. 2022 · 2022
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Teaching language models to support answers with verified quotes
Jacob Menick, Maja Trebacz, Vladimir Mikulik, John Aslanides, Francis Song, Martin Chadwick, Mia Glaese, Susannah Young, Lucy Campbell-Gillingham, Geoffrey Irving, and Nat McAleese. 2022 · 2022
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Measuring attribution in natural language generation models
Hannah Rashkin, Vitaly Nikolaev, Matthew Lamm, Lora Aroyo, Michael Collins, Dipanjan Das, Slav Petrov, Gaurav Singh Tomar, Iulia Turc, and David Reitter. 2022 · 2022
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Controlled text reduction
Aviv Slobodkin, Paul Roit, Eran Hirsch, Ori Ernst, and Ido Dagan. 2022 · 2022
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ASQA: Factoid questions meet long-form answers
Ivan Stelmakh, Yi Luan, Bhuwan Dhingra, and Ming-Wei Chang. 2022 · 2022
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Lamda: Language models for dialog applications
Romal Thoppilan, Daniel De Freitas, Jamie Hall, Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze Cheng, Alicia Jin, Taylor Bos, Leslie Baker, Yu Du, YaGuang Li, Hongrae Lee, Huaixiu Steven Zheng, Amin Ghafouri, Marcelo Menegali, Yanping Huang, Maxim Krikun, Dmitry Lepikhin, James Qin, Dehao Chen, Yuanzhong Xu, Zhifeng Chen, Adam Roberts, Maarten Bosma, Vincent Zhao, Yanqi Zhou, Chung-Ching Chang, Igor Krivokon, Will Rusch, Marc Pickett, Pranesh Srinivasan, Laichee Man, Kathleen Meier-Hellstern, Meredith Ringel Morris, Tulsee Doshi, Renelito Delos Santos, Toju Duke, Johnny Soraker, Ben Zevenbergen, Vinodkumar Prabhakaran, Mark Diaz, Ben Hutchinson, Kristen Olson, Alejandra Molina, Erin Hoffman-John, Josh Lee, Lora Aroyo, Ravi Rajakumar, Alena Butryna, Matthew Lamm, Viktoriya Kuzmina, Joe Fenton, Aaron Cohen, Rachel Bernstein, Ray Kurzweil, Blaise Aguera-Arcas, Claire Cui, Marian Croak, Ed Chi, and Quoc Le. 2022 · 2022
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FActScore: Fine-grained atomic evaluation of factual precision in long form text generation
Sewon Min, Kalpesh Krishna, Xinxi Lyu, Mike Lewis, Wen-tau Yih, Pang Koh, Mohit Iyyer, Luke Zettlemoyer, and Hannaneh Hajishirzi. 2023 · 2023
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Conditional generation with a question-answering blueprint
Shashi Narayan, Joshua Maynez, Reinald Kim Amplayo, Kuzman Ganchev, Annie Louis, Fantine Huot, Anders Sandholm, Dipanjan Das, and Mirella Lapata. 2023 · 2023
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Vipula Rawte, Prachi Priya, S. M Towhidul Islam Tonmoy, S M Mehedi Zaman, Amit Sheth, and Amitava Das. 2023 · 2023
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Language models are greedy reasoners: A systematic formal analysis of chain-of-thought
Abulhair Saparov and He He. 2023 · 2023
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Semqa: Semi-extractive multi-source question answering
Tal Schuster, Adam D. Lelkes, Haitian Sun, Jai Gupta, Jonathan Berant, William W. Cohen, and Donald Metzler. 2023 · 2023
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Don’t add, don’t miss: Effective content preserving generation from pre-selected text spans
Aviv Slobodkin, Avi Caciularu, Eran Hirsch, and Ido Dagan. 2023a · 2023
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The curious case of hallucinatory (un)answerability: Finding truths in the hidden states of over-confident large language models
Aviv Slobodkin, Omer Goldman, Avi Caciularu, Ido Dagan, and Shauli Ravfogel. 2023b · 2023
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Llm lies: Hallucinations are not bugs, but features as adversarial examples
Jia-Yu Yao, Kun-Peng Ning, Zhen-Hui Liu, Mu-Nan Ning, and Li Yuan. 2023 · 2023
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The power of summary-source alignments
Ori Ernst, Ori Shapira, Aviv Slobodkin, Sharon Adar, Mohit Bansal, Jacob Goldberger, Ran Levy, and Ido Dagan. 2024 · 2024
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The dawn after the dark: An empirical study on factuality hallucination in large language models
Junyi Li, Jie Chen, Ruiyang Ren, Xiaoxue Cheng, Wayne Xin Zhao, Jian-Yun Nie, and Ji-Rong Wen. 2024 · 2024
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Multi-review fusion-in-context
Aviv Slobodkin, Ori Shapira, Ran Levy, and Ido Dagan. 2024 · 2024
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TrueTeacher: Learning factual consistency evaluation with large language models
Zorik Gekhman, Jonathan Herzig, Roee Aharoni, Chen Elkind, and Idan Szpektor. 2023 · 2070
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