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Large language models (LLMs) have experienced notable advancements in generating coherent and contextually relevant responses.
Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension, 2017
Mandar Joshi, Eunsol Choi, Daniel S. Weld, and Luke Zettlemoyer · 2017
Earlier work this paper cites.
The narrativeqa reading comprehension challenge, 2017
Tomáš Kočiský, Jonathan Schwarz, Phil Blunsom, Chris Dyer, Karl Moritz Hermann, Gábor Melis, and Edward Grefenstette · 2017
Earlier work this paper cites.
TL;DR: Mining Reddit to learn automatic summarization
Michael Völske, Martin Potthast, Shahbaz Syed, and Benno Stein · 2017
Earlier work this paper cites.
Drop: A reading comprehension benchmark requiring discrete reasoning over paragraphs, 2019
Dheeru Dua, Yizhong Wang, Pradeep Dasigi, Gabriel Stanovsky, Sameer Singh, and Matt Gardner · 2019
Earlier work this paper cites.
Asking and answering questions to evaluate the factual consistency of summaries, 2020
Alex Wang, Kyunghyun Cho, and Mike Lewis · 2020
Earlier work this paper cites.
COVID-QA: A question answering dataset for COVID-19
Timo Möller, Anthony Reina, Raghavan Jayakumar, and Malte Pietsch · 2020
Earlier work this paper cites.
Bertscore: Evaluating text generation with bert, 2020
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, and Yoav Artzi · 2020
Earlier work this paper cites.
Summeval: Re-evaluating summarization evaluation, 2021
Alexander R. Fabbri, Wojciech Kryściński, Bryan McCann, Caiming Xiong, Richard Socher, and Dragomir Radev · 2021
Earlier work this paper cites.
Mediasum: A large-scale media interview dataset for dialogue summarization, 2021
Chenguang Zhu, Yang Liu, Jie Mei, and Michael Zeng · 2021
Earlier work this paper cites.
A framework for few-shot language model evaluation, September 2021
Leo Gao, Jonathan Tow, Stella Biderman, Sid Black, Anthony DiPofi, Charles Foster, Laurence Golding, Jeffrey Hsu, Kyle McDonell, Niklas Muennighoff, Jason Phang, Laria Reynolds, Eric Tang, Anish Thite, Ben Wang, Kevin Wang, and Andy Zou · 2021
Cited alongside, same era.
True: Re-evaluating factual consistency evaluation, 2022
Or Honovich, Roee Aharoni, Jonathan Herzig, Hagai Taitelbaum, Doron Kukliansy, Vered Cohen, Thomas Scialom, Idan Szpektor, Avinatan Hassidim, and Yossi Matias · 2022
Cited alongside, same era.
Evaluating attribution in dialogue systems: The begin benchmark, 2022
Nouha Dziri, Hannah Rashkin, Tal Linzen, and David Reitter · 2022
Cited alongside, same era.
Towards a unified multi-dimensional evaluator for text generation, 2022
Ming Zhong, Yang Liu, Da Yin, Yuning Mao, Yizhu Jiao, Pengfei Liu, Chenguang Zhu, Heng Ji, and Jiawei Han · 2022
Cited alongside, same era.
Improving the domain adaptation of retrieval augmented generation (rag) models for open domain question answering, 2022
Shamane Siriwardhana, Rivindu Weerasekera, Elliott Wen, Tharindu Kaluarachchi, Rajib Rana, and Suranga Nanayakkara · 2022
Gpt-4 technical report
OpenAI · 2023
Closest in time.
Openassistant conversations – democratizing large language model alignment
Andreas Köpf, Yannic Kilcher, Dimitri von Rütte, Sotiris Anagnostidis, Zhi-Rui Tam, Keith Stevens, Abdullah Barhoum, Nguyen Minh Duc, Oliver Stanley, Richárd Nagyfi, Shahul ES, Sameer Suri, David Glushkov, Arnav Dantuluri, Andrew Maguire, Christoph Schuhmann, Huu Nguyen, and Alexander Mattick · 2023
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Measuring faithfulness in chain-of-thought reasoning, 2023
Tamera Lanham, Anna Chen, Ansh Radhakrishnan, Benoit Steiner, Carson Denison, Danny Hernandez, Dustin Li, Esin Durmus, Evan Hubinger, Jackson Kernion, Kamilė Lukošiūtė, Karina Nguyen, Newton Cheng, Nicholas Joseph, Nicholas Schiefer, Oliver Rausch, Robin Larson, Sam McCandlish, Sandipan Kundu, Saurav Kadavath, Shannon Yang, Thomas Henighan, Timothy Maxwell, Timothy Telleen-Lawton, Tristan Hume, Zac Hatfield-Dodds, Jared Kaplan, Jan Brauner, Samuel R. Bowman, and Ethan Perez · 2023
Closest in time.
Self-contradictory hallucinations of large language models: Evaluation, detection and mitigation, 2023
Niels Mündler, Jingxuan He, Slobodan Jenko, and Martin Vechev · 2023
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Self-instruct: Aligning language models with self-generated instructions, 2023
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Cited alongside, same era.
Super-naturalinstructions: Generalization via declarative instructions on 1600+ nlp tasks, 2022
Yizhong Wang, Swaroop Mishra, Pegah Alipoormolabashi, Yeganeh Kordi, Amirreza Mirzaei, Anjana Arunkumar, Arjun Ashok, Arut Selvan Dhanasekaran, Atharva Naik, David Stap, Eshaan Pathak, Giannis Karamanolakis, Haizhi Gary Lai, Ishan Purohit, Ishani Mondal, Jacob Anderson, Kirby Kuznia, Krima Doshi, Maitreya Patel, Kuntal Kumar Pal, Mehrad Moradshahi, Mihir Parmar, Mirali Purohit, Neeraj Varshney, Phani Rohitha Kaza, Pulkit Verma, Ravsehaj Singh Puri, Rushang Karia, Shailaja Keyur Sampat, Savan Doshi, Siddhartha Mishra, Sujan Reddy, Sumanta Patro, Tanay Dixit, Xudong Shen, Chitta Baral, Yejin Choi, Noah A. Smith, Hannaneh Hajishirzi, and Daniel Khashabi · 2022
Cited alongside, same era.
Evaluating the factual consistency of large language models through summarization, 2022
Derek Tam, Anisha Mascarenhas, Shiyue Zhang, Sarah Kwan, Mohit Bansal, and Colin Raffel · 2022
Cited alongside, same era.
Gptscore: Evaluate as you desire, 2023
Jinlan Fu, See-Kiong Ng, Zhengbao Jiang, and Pengfei Liu · 2023
Cited alongside, same era.
G-eval: Nlg evaluation using gpt-4 with better human alignment, 2023
Yang Liu, Dan Iter, Yichong Xu, Shuohang Wang, Ruochen Xu, and Chenguang Zhu · 2023
Cited alongside, same era.
Selfcheckgpt: Zero-resource black-box hallucination detection for generative large language models, 2023a
Potsawee Manakul, Adian Liusie, and Mark J. F. Gales
Cited in the paper.
Llama 2: Open foundation and fine-tuned chat models, 2023
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, Dan Bikel, Lukas Blecher, Cristian Canton Ferrer, Moya Chen, Guillem Cucurull, David Esiobu, Jude Fernandes, Jeremy Fu, Wenyin Fu, Brian Fuller, Cynthia Gao, Vedanuj Goswami, Naman Goyal, Anthony Hartshorn, Saghar Hosseini, Rui Hou, Hakan Inan, Marcin Kardas, Viktor Kerkez, Madian Khabsa, Isabel Kloumann, Artem Korenev, Punit Singh Koura, Marie-Anne Lachaux, Thibaut Lavril, Jenya Lee, Diana Liskovich, Yinghai Lu, Yuning Mao, Xavier Martinet, Todor Mihaylov, Pushkar Mishra, Igor Molybog, Yixin Nie, Andrew Poulton, Jeremy Reizenstein, Rashi Rungta, Kalyan Saladi, Alan Schelten, Ruan Silva, Eric Michael Smith, Ranjan Subramanian, Xiaoqing Ellen Tan, Binh Tang, Ross Taylor, Adina Williams, Jian Xiang Kuan, Puxin Xu, Zheng Yan, Iliyan Zarov, Yuchen Zhang, Angela Fan, Melanie Kambadur, Sharan Narang, Aurelien Rodriguez, Robert Stojnic, Sergey Edunov, and Thomas Scialom
Cited in the paper.
Mqag: Multiple-choice question answering and generation for assessing information consistency in summarization, 2023b
Potsawee Manakul, Adian Liusie, and Mark J. F. Gales
Cited in the paper.
Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A. Smith, Daniel Khashabi, and Hannaneh Hajishirzi · 2023
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The flan collection: Designing data and methods for effective instruction tuning, 2023
Shayne Longpre, Le Hou, Tu Vu, Albert Webson, Hyung Won Chung, Yi Tay, Denny Zhou, Quoc V. Le, Barret Zoph, Jason Wei, and Adam Roberts · 2023
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Halueval: A large-scale hallucination evaluation benchmark for large language models, 2023
Junyi Li, Xiaoxue Cheng, Wayne Xin Zhao, Jian-Yun Nie, and Ji-Rong Wen · 2023
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Evaluating factual consistency of summaries with large language models, 2023
Shiqi Chen, Siyang Gao, and Junxian He · 2023
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A discourse-aware attention model for abstractive summarization of long documents
Arman Cohan, Franck Dernoncourt, Doo Soon Kim, Trung Bui, Seokhwan Kim, Walter Chang, and Nazli Goharian · 2097
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