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Large Language Models (LLMs) have shown remarkable capabilities across a wide variety of Natural Language Processing (NLP) tasks and have attracted attention from multiple domains, including financial services.
Good debt or bad debt: Detecting semantic orientations in economic texts
Pekka Malo, Ankur Sinha, Pekka Korhonen, Jyrki Wallenius, and Pyry Takala · 2014
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Domain adaption of named entity recognition to support credit risk assessment
Julio Cesar Salinas Alvarado, Karin Verspoor, and Timothy Baldwin · 2015
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Semeval-2017 task 5: Fine-grained sentiment analysis on financial microblogs and news
Keith Cortis, André Freitas, Tobias Daudert, et al · 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
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Www’18 open challenge: financial opinion mining and question answering
Macedo Maia, Siegfried Handschuh, André Freitas, et al · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al · 2018
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Hybrid deep sequential modeling for social text-driven stock prediction
Huizhe Wu, Wei Zhang, Weiwei Shen, and Jun Wang · 2018
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Stock movement prediction from tweets and historical prices
Yumo Xu and Shay B Cohen · 2018
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Finbert: Financial sentiment analysis with pre-trained language models
Dogu Araci · 2019
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Multiling 2019: Financial narrative summarisation
Mahmoud El-Haj · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, et al · 2020
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Efficient intent detection with dual sentence encoders
Iñigo Casanueva, Tadas Temčinas, Daniela Gerz, Matthew Henderson, and Ivan Vulić · 2020
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Electra: Pre-training text encoders as discriminators rather than generators
Kevin Clark, Minh-Thang Luong, Quoc V Le, and Christopher D Manning · 2020
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Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, et al · 2020
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Maec: A multimodal aligned earnings conference call dataset for financial risk prediction
Jiazheng Li, Linyi Yang, Barry Smyth, and Ruihai Dong · 2020
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The financial document causality detection shared task (fincausal 2020)
Dominique Mariko, Hanna Abi Akl, Estelle Labidurie, et al · 2020
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Finbert: A pretrained language model for financial communications
Yi Yang, Mark Christopher Siy Uy, and Allen Huang · 2020
Cited alongside, same era.
On the opportunities and risks of foundation models
Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Altman, et al · 2021
Cited alongside, same era.
Finqa: A dataset of numerical reasoning over financial data
Zhiyu Chen, Wenhu Chen, Charese Smiley, Sameena Shah, Iana Borova, et al · 2021
Cited alongside, same era.
Multilingual and cross-lingual intent detection from spoken data
Daniela Gerz, Pei-Hao Su, Razvan Kusztos, Avishek Mondal, Michał Lis, et al · 2021
Cited alongside, same era.
Lora: Low-rank adaptation of large language models
Edward J Hu, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, et al · 2021
Cited alongside, same era.
Accurate stock movement prediction with self-supervised learning from sparse noisy tweets
Yejun Soun, Jaemin Yoo, Minyong Cho, Jihyeong Jeon, and U Kang · 2022
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Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, et al · 2022
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Is chatgpt a financial expert? evaluating language models on financial natural language processing
Yue Guo, Zian Xu, and Yi Yang · 2023
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Multifin: A dataset for multilingual financial nlp
Rasmus Jørgensen, Oliver Brandt, Mareike Hartmann, Xiang Dai, Christian Igel, and Desmond Elliott · 2023
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Stockemotions: Discover investor emotions for financial sentiment analysis and multivariate time series
Jean Lee, Hoyoul Luis Youn, Josiah Poon, and Soyeon Caren Han · 2023
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Fednlp: an interpretable nlp system to decode federal reserve communications
Jean Lee, Hoyoul Luis Youn, Nicholas Stevens, Josiah Poon, and Soyeon Caren Han · 2021
Cited alongside, same era.
Finbert: A pre-trained financial language representation model for financial text mining
Zhuang Liu, Degen Huang, Kaiyu Huang, Zhuang Li, and Jun Zhao · 2021
Cited alongside, same era.
Impact of news on the commodity market: Dataset and results
Ankur Sinha and Tanmay Khandait · 2021
Cited alongside, same era.
Global table extractor (gte): A framework for joint table identification and cell structure recognition using visual context
Xinyi Zheng, Douglas Burdick, Lucian Popa, Xu Zhong, and Nancy Xin Ru Wang · 2021
Cited alongside, same era.
Trade the event: Corporate events detection for news-based event-driven trading
Zhihan Zhou, Liqian Ma, and Han Liu · 2021
Cited alongside, same era.
Convfinqa: Exploring the chain of numerical reasoning in conversational finance question answering
Zhiyu Chen, Shiyang Li, Charese Smiley, Zhiqiang Ma, Sameena Shah, and William Yang Wang · 2022
Cited alongside, same era.
Continual pre-training of language models
Zixuan Ke, Yijia Shao, Haowei Lin, Tatsuya Konishi, Gyuhak Kim, and Bing Liu · 2022
Cited alongside, same era.
Are chatgpt and gpt-4 general-purpose solvers for financial text analytics? a study on several typical tasks
Xianzhi Li, Samuel Chan, Xiaodan Zhu, et al · 2023
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Large language models in finance: A survey
Yinheng Li, Shaofei Wang, Han Ding, and Hang Chen · 2023
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Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing
Pengfei Liu, Weizhe Yuan, Jinlan Fu, et al · 2023
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Trillion dollar words: A new financial dataset, task & market analysis
Agam Shah, Suvan Paturi, and Sudheer Chava · 2023
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Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, et al · 2023
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Fingpt: Instruction tuning benchmark for open-source large language models in financial datasets
Neng Wang, Hongyang Yang, and Christina Dan Wang · 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
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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
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Harnessing the power of llms in practice: A survey on chatgpt and beyond
Jingfeng Yang, Hongye Jin, Ruixiang Tang, Xiaotian Han, Qizhang Feng, Haoming Jiang, Bing Yin, and Xia Hu · 2023
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Investlm: A large language model for investment using financial domain instruction tuning
Yi Yang, Yixuan Tang, and Kar Yan Tam · 2023
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Instruction tuning for large language models: A survey
Shengyu Zhang, Linfeng Dong, Xiaoya Li, Sen Zhang, Xiaofei Sun, Shuhe Wang, et al · 2023
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A survey of large language models
Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, , Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, et al · 2023
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