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Ariana Martino, Michael Iannelli and Coleen Truong · 2023
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OpenAI · 2023
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“Automatically Correcting Large Language Models: Surveying the landscape of diverse self-correction strategies”
Liangming Pan, Michael Saxon, Wenda Xu, Deepak Nathani, Xinyi Wang and William Wang · 2023
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“Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback”
Baolin Peng, Michel Galley, Pengcheng He, Hao Cheng, Yujia Xie, Yu Hu, Qiuyuan Huang, Lars Liden, Zhou Yu, Weizhu Chen and Jianfeng Gao · 2023
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“The Troubling Emergence of Hallucination in Large Language Models – An Extensive Definition, Quantification, and Prescriptive Remediations”
Vipula Rawte, Swagata Chakraborty, Agnibh Pathak, Anubhav Sarkar, S. Tonmoy, Aman Chadha, Amit. Sheth and Amitava Das · 2023
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“NeMo Guardrails: A Toolkit for Controllable and Safe LLM Applications with Programmable Rails”
Traian Rebedea, Razvan Dinu, Makesh Sreedhar, Christopher Parisien and Jonathan Cohen · 2023
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“Trusting Your Evidence: Hallucinate Less with Context-aware Decoding”
Weijia Shi, Xiaochuang Han, Mike Lewis, Yulia Tsvetkov, Luke Zettlemoyer and Scott-tau Yih · 2023
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“In-Context Pretraining: Language Modeling Beyond Document Boundaries”
Weijia Shi, Sewon Min, Maria Lomeli, Chunting Zhou, Margaret Li, Rich James, Xi Lin, Noah. Smith, Luke Zettlemoyer, Scott Yih and Mike Lewis · 2023
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“LLaMA: Open and Efficient Foundation Language Models”
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“Language Models Don’t Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting”
Miles Turpin, Julian Michael, Ethan Perez and Samuel. Bowman · 2023
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“FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation”
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“Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity”
Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, Xiangru Tang, Tianhang Zhang, Cheng Jiayang, Yunzhi Yao, Wenyang Gao, Xuming Hu, Zehan Qi, Yidong Wang, Linyi Yang, Jindong Wang, Xing Xie, Zheng Zhang and Yue Zhang · 2023
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“SCOTT: Self-Consistent Chain-of-Thought Distillation”
Peifeng Wang, Zhengyang Wang, Zheng Li, Yifan Gao, Bing Yin and Xiang Ren · 2023
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Wikipedia contributors · 2023
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“Tree of Thoughts: Deliberate Problem Solving with Large Language Models”
Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Thomas. Griffiths, Yuan Cao and Karthik Narasimhan · 2023
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“Siren’s Song in the AI Ocean: A Survey on Hallucination in Large Language Models”
Yue Zhang, Yafu Li, Leyang Cui, Deng Cai, Lemao Liu, Tingchen Fu, Xinting Huang, Enbo Zhao, Yu Zhang, Yulong Chen, Longyue Wang, Anh Luu, Wei Bi, Freda Shi and Shuming Shi · 2023
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“Verify-and-Edit: A Knowledge-Enhanced Chain-of-Thought Framework”
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Ruochen Zhao, Xingxuan Li, Shafiq Joty, Chengwei Qin and Lidong Bing · 2023
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“Airline held liable for its chatbot giving passenger bad advice - what this means for travellers” Accessed: 2024-02-22, 2024
BBC · 2024
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“Benchmarking Large Language Models in Retrieval-Augmented Generation”
Jiawei Chen, Hongyu Lin, Xianpei Han and Le Sun · 2024
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“The Pitfalls of Defining Hallucination”
Kees van Deemter · 2024
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“Stuck in the Quicksand of Numeracy, Far from AGI Summit: Evaluating LLMs’ Mathematical Competency through Ontology-guided Perturbations”
Pengfei Hong, Deepanway Ghosal, Navonil Majumder, Somak Aditya, Rada Mihalcea and Soujanya Poria · 2024
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“Calibrated Language Models Must Hallucinate”
Adam Kalai and Santosh. Vempala · 2024
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Junliang Luo, Tianyu Li, Di Wu, Michael Jenkin, Steve Liu and Gregory Dudek · 2024
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Meta Platforms, Inc · 2024
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