FinMTEB: Finance Massive Text Embedding Benchmark

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Representation learning with contrastive predictive coding

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Don’t stop pretraining: Adapt language models to domains and tasks

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Exploring the limits of transfer learning with a unified text-to-text transformer

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FinQA: A dataset of numerical reasoning over financial data

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Multilingual and cross-lingual intent detection from spoken data

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Mdfend: Multi-domain fake news detection

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Impact of news on the commodity market: Dataset and results

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BEIR: A heterogeneous benchmark for zero-shot evaluation of information retrieval models

Nandan Thakur, Nils Reimers, Andreas Rücklé, Abhishek Srivastava, and Iryna Gurevych. 2021 · 2021

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Trade the event: Corporate events detection for news-based event-driven trading

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Tat-qa: A question answering benchmark on a hybrid of tabular and textual content in finance

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Ccks2022: Few-shot event extraction for the financial sector

CCKS. 2022 · 2022

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Bloomberggpt: A large language model for finance

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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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C-pack: Packaged resources to advance general chinese embedding

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Shitao Xiao, Zheng Liu, Peitian Zhang, and Niklas Muennighoff. 2023 · 2023

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Fineval: A chinese financial domain knowledge evaluation benchmark for large language models

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Liwen Zhang, Weige Cai, Zhaowei Liu, Zhi Yang, Wei Dai, Yujie Liao, Qianru Qin, Yifei Li, Xingyu Liu, Zhiqiang Liu, et al. 2023 · 2023

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Greenback bears and fiscal hawks: Finance is a jungle and text embeddings must adapt

Peter Anderson, Mano Vikash Janardhanan, Jason He, Wei Cheng, and Charlie Flanagan. 2024 · 2024

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