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The hallucination issue is recognized as a fundamental deficiency of large language models (LLMs), especially when applied to fields such as finance, education, and law.
Billion-scale similarity search with gpus
Jeff Johnson, Matthijs Douze, and Hervé Jégou · 2019
Earlier work this paper cites.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
Earlier work this paper cites.
Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, et al · 2020
Earlier work this paper cites.
Finbert: A pretrained language model for financial communications
Yi Yang, Mark Christopher Siy Uy, and Allen Huang · 2020
Earlier work this paper cites.
Contrastive decoding: Open-ended text generation as optimization
Xiang Lisa Li, Ari Holtzman, Daniel Fried, Percy Liang, Jason Eisner, Tatsunori Hashimoto, Luke Zettlemoyer, and Mike Lewis · 2022
Earlier work this paper cites.
Self-rag: Learning to retrieve, generate, and critique through self-reflection
Akari Asai, Zeqiu Wu, Yizhong Wang, Avirup Sil, and Hannaneh Hajishirzi · 2023
Earlier work this paper cites.
Dola: Decoding by contrasting layers improves factuality in large language models
Yung-Sung Chuang, Yujia Xie, Hongyin Luo, Yoon Kim, James Glass, and Pengcheng He · 2023
Earlier work this paper cites.
Chatlaw: Open-source legal large language model with integrated external knowledge bases
Jiaxi Cui, Zongjian Li, Yang Yan, Bohua Chen, and Li Yuan · 2023
Earlier work this paper cites.
Halo: Estimation and reduction of hallucinations in open-source weak large language models
Mohamed Elaraby, Mengyin Lu, Jacob Dunn, Xueying Zhang, Yu Wang, and Shizhu Liu · 2023
Earlier work this paper cites.
Lei Huang, Weijiang Yu, Weitao Ma, Weihong Zhong, Zhangyin Feng, Haotian Wang, Qianglong Chen, Weihua Peng, Xiaocheng Feng, Bing Qin, et al · 2023
Cited alongside, same era.
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
Cited alongside, same era.
Active retrieval augmented generation
Zhengbao Jiang, Frank F Xu, Luyu Gao, Zhiqing Sun, Qian Liu, Jane Dwivedi-Yu, Yiming Yang, Jamie Callan, and Graham Neubig · 2023
Cited alongside, same era.
Can chatgpt improve investment decision? from a portfolio management perspective
Hyungjin Ko and Jaewook Lee · 2023
Cited alongside, same era.
Inference-time intervention: Eliciting truthful answers from a language model
Toolformer: Language models can teach themselves to use tools
Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Luke Zettlemoyer, Nicola Cancedda, and Thomas Scialom · 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 Wen-tau Yih · 2023
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Med-halt: Medical domain hallucination test for large language models
Logesh Kumar Umapathi, Ankit Pal, and Malaikannan Sankarasubbu · 2023
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Performance and exploration of chatgpt in medical examination, records and education in chinese: Pave the way for medical ai
Hongyan Wang, WeiZhen Wu, Zhi Dou, Liangliang He, and Liqiang Yang · 2023
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Kenneth Li, Oam Patel, Fernanda Viégas, Hanspeter Pfister, and Martin Wattenberg · 2023
Cited alongside, same era.
FinGPT: Democratizing internet-scale data for financial large language models
Xiao-Yang Liu, Guoxuan Wang, and Daochen Zha · 2023
Cited alongside, same era.
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
Cited alongside, same era.
OpenAI · 2023
Cited alongside, same era.
Gorilla: Large language model connected with massive apis
Shishir G Patil, Tianjun Zhang, Xin Wang, and Joseph E Gonzalez · 2023
Cited alongside, same era.
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, et al
Cited in the paper.
Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al
Cited in the paper.
Instruct-FinGPT: Financial sentiment analysis by instruction tuning of general-purpose large language models
Boyu Zhang, Hongyang Yang, and Xiao-Yang Liu
Cited in the paper.
Shijie Wu, Ozan Irsoy, Steven Lu, Vadim Dabravolski, Mark Dredze, Sebastian Gehrmann, Prabhanjan Kambadur, David Rosenberg, and Gideon Mann · 2023
Closest in time.
Pixiu: A large language model, instruction data and evaluation benchmark for finance
Qianqian Xie, Weiguang Han, Xiao Zhang, Yanzhao Lai, Min Peng, Alejandro Lopez-Lira, and Jimin Huang · 2023
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FinGPT: Open-source financial large language models
Hongyang Yang, Xiao-Yang Liu, and Christina Dan Wang · 2023
Closest in time.
Enhancing financial sentiment analysis via retrieval augmented large language models
Boyu Zhang, Hongyang Yang, Tianyu Zhou, Ali Babar, and Xiao-Yang Liu · 2023
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