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Large Language Models (LLMs) have gained significant popularity for their impressive performance across diverse fields.
On faithfulness and factuality in abstractive summarization
Joshua Maynez, Shashi Narayan, Bernd Bohnet, and Ryan McDonald. 2020 · 1919
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Scheduled sampling for sequence prediction with recurrent neural networks
Samy Bengio, Oriol Vinyals, Navdeep Jaitly, and Noam Shazeer. 2015 · 2015
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spacy 2: Natural language understanding with bloom embeddings, convolutional neural networks and incremental parsing
Matthew Honnibal and Ines Montani. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Don’t give me the details, just the summary! topic-aware convolutional neural networks for extreme summarization
Shashi Narayan, Shay B Cohen, and Mirella Lapata. 2018 · 2018
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Ranking generated summaries by correctness: An interesting but challenging application for natural language inference
Tobias Falke, Leonardo FR Ribeiro, Prasetya Ajie Utama, Ido Dagan, and Iryna Gurevych. 2019 · 2019
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Stolen probability: A structural weakness of neural language models
David Demeter, Gregory Kimmel, and Doug Downey. 2020 · 2020
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What have we achieved on text summarization?
Dandan Huang, Leyang Cui, Sen Yang, Guangsheng Bao, Kun Wang, Jun Xie, and Yue Zhang. 2020 · 2020
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Evaluating the factual consistency of abstractive text summarization
Wojciech Kryściński, Bryan McCann, Caiming Xiong, and Richard Socher. 2020 · 2020
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Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020 · 2020
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On long-tailed phenomena in neural machine translation
Vikas Raunak, Siddharth Dalmia, Vivek Gupta, and Florian Metze. 2020 · 2020
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Summeval: Re-evaluating summarization evaluation
Alexander R Fabbri, Wojciech Kryściński, Bryan McCann, Caiming Xiong, Richard Socher, and Dragomir Radev. 2021 · 2021
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The factual inconsistency problem in abstractive text summarization: A survey
Yichong Huang, Xiachong Feng, Xiaocheng Feng, and Bing Qin. 2021 · 2021
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Text-in-context: Token-level error detection for table-to-text generation
Zdeněk Kasner, Simon Mille, and Ondřej Dušek. 2021 · 2021
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Entity-based knowledge conflicts in question answering
Shayne Longpre, Kartik Perisetla, Anthony Chen, Nikhil Ramesh, Chris DuBois, and Sameer Singh. 2021 · 2021
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Entity-level factual consistency of abstractive text summarization
Feng Nan, Ramesh Nallapati, Zhiguo Wang, Cicero dos Santos, Henghui Zhu, Dejiao Zhang, Kathleen Mckeown, and Bing Xiang. 2021 · 2021
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Understanding factuality in abstractive summarization with frank: A benchmark for factuality metrics
Artidoro Pagnoni, Vidhisha Balachandran, and Yulia Tsvetkov. 2021 · 2021
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Increasing faithfulness in knowledge-grounded dialogue with controllable features
Hannah Rashkin, David Reitter, Gaurav Singh Tomar, and Dipanjan Das. 2021 · 2021
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GPT-J-6B: A 6 Billion Parameter Autoregressive Language Model
Ben Wang and Aran Komatsuzaki. 2021 · 2021
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On hallucination and predictive uncertainty in conditional language generation
Yijun Xiao and William Yang Wang. 2021 · 2021
Cited alongside, same era.
Gpt-neox-20b: An open-source autoregressive language model
Sidney Black, Stella Biderman, Eric Hallahan, Quentin Anthony, Leo Gao, Laurence Golding, Horace He, Connor Leahy, Kyle McDonell, Jason Phang, et al. 2022 · 2022
Cited alongside, same era.
Hallucinated but factual! inspecting the factuality of hallucinations in abstractive summarization
Meng Cao, Yue Dong, and Jackie Chi Kit Cheung. 2022 · 2022
Cited alongside, same era.
David Dale, Elena Voita, Loïc Barrault, and Marta R Costa-jussà. 2022 · 2022
Cited alongside, same era.
Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, Wenliang Dai, Dan Su, Bryan Wilie, Holy Lovenia, Ziwei Ji, Tiezheng Yu, Willy Chung, et al. 2023 · 2023
Closest in time.
Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E. Gonzalez, Ion Stoica, and Eric P. Xing. 2023 · 2023
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Redpajama: An open source recipe to reproduce llama training dataset
Together Computer. 2023 · 2023
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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 · 2023
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Yue Dong, John Wieting, and Pat Verga. 2022 · 2022
Cited alongside, same era.
On the origin of hallucinations in conversational models: Is it the datasets or the models?
Nouha Dziri, Sivan Milton, Mo Yu, Osmar R Zaiane, and Siva Reddy. 2022 · 2022
Cited alongside, same era.
Nuno M Guerreiro, Elena Voita, and André FT Martins. 2022 · 2022
Cited alongside, same era.
The survey: Text generation models in deep learning
Touseef Iqbal and Shaima Qureshi. 2022 · 2022
Cited alongside, same era.
Summac: Re-visiting nli-based models for inconsistency detection in summarization
Philippe Laban, Tobias Schnabel, Paul N Bennett, and Marti A Hearst. 2022 · 2022
Cited alongside, same era.
A token-level reference-free hallucination detection benchmark for free-form text generation
Tianyu Liu, Yizhe Zhang, Chris Brockett, Yi Mao, Zhifang Sui, Weizhu Chen, and William B Dolan. 2022 · 2022
Cited alongside, same era.
Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022 · 2022
Cited alongside, same era.
Controlling hallucinations at word level in data-to-text generation
Clément Rebuffel, Marco Roberti, Laure Soulier, Geoffrey Scoutheeten, Rossella Cancelliere, and Patrick Gallinari. 2022 · 2022
Cited alongside, same era.
Nuno M Guerreiro, Duarte Alves, Jonas Waldendorf, Barry Haddow, Alexandra Birch, Pierre Colombo, and André FT Martins. 2023 · 2023
Closest in time.
Chatgpt for healthcare services: An emerging stage for an innovative perspective
Mohd Javaid, Abid Haleem, and Ravi Pratap Singh. 2023 · 2023
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Survey of hallucination in natural language generation
Ziwei Ji, Nayeon Lee, Rita Frieske, Tiezheng Yu, Dan Su, Yan Xu, Etsuko Ishii, Ye Jin Bang, Andrea Madotto, and Pascale Fung. 2023 · 2023
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Benefits, limits, and risks of gpt-4 as an ai chatbot for medicine
Peter Lee, Sebastien Bubeck, and Joseph Petro. 2023 · 2023
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Reta-llm: A retrieval-augmented large language model toolkit
Jiongnan Liu, Jiajie Jin, Zihan Wang, Jiehan Cheng, Zhicheng Dou, and Ji-Rong Wen. 2023 · 2023
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Can chatgpt forecast stock price movements? return predictability and large language models
Alejandro Lopez-Lira and Yuehua Tang. 2023 · 2023
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Selfcheckgpt: Zero-resource black-box hallucination detection for generative large language models
Potsawee Manakul, Adian Liusie, and Mark JF Gales. 2023 · 2023
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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 Wei Koh, Mohit Iyyer, Luke Zettlemoyer, and Hannaneh Hajishirzi. 2023 · 2023
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Self-contradictory hallucinations of large language models: Evaluation, detection and mitigation
Niels Mündler, Jingxuan He, Slobodan Jenko, and Martin Vechev. 2023 · 2023
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The utility of chatgpt as an example of large language models in healthcare education, research and practice: Systematic review on the future perspectives and potential limitations
Malik Sallam. 2023 · 2023
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Stanford alpaca: An instruction-following llama model
Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, and Tatsunori B. Hashimoto. 2023 · 2023
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What if the devil is my guardian angel: Chatgpt as a case study of using chatbots in education
Ahmed Tlili, Boulus Shehata, Michael Agyemang Adarkwah, Aras Bozkurt, Daniel T Hickey, Ronghuai Huang, and Brighter Agyemang. 2023 · 2023
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Bloomberggpt: A large language model for finance
Shijie Wu, Ozan Irsoy, Steven Lu, Vadim Dabravolski, Mark Dredze, Sebastian Gehrmann, Prabhanjan Kambadur, David Rosenberg, and Gideon Mann. 2023 · 2023
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Understanding and detecting hallucinations in neural machine translation via model introspection
Weijia Xu, Sweta Agrawal, Eleftheria Briakou, Marianna J Martindale, and Marine Carpuat. 2023 · 2023
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