{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/the-finben-an-holistic-financial-benchmark","title":"FinBen: A Holistic Financial Benchmark for Large Language Models","arxiv_id":"2402.12659","date":"2024-02-20","proceeding":null,"authors":["Qianqian Xie","Weiguang Han","Zhengyu Chen","Ruoyu Xiang","Xiao Zhang","Yueru He","Mengxi Xiao","Dong Li","Yongfu Dai","Duanyu Feng","Yijing Xu","Haoqiang Kang","Ziyan Kuang","Chenhan Yuan","Kailai Yang","Zheheng Luo","Tianlin Zhang","Zhiwei Liu","Guojun Xiong","Zhiyang Deng","Yuechen Jiang","Zhiyuan Yao","Haohang Li","Yangyang Yu","Gang Hu","Jiajia Huang","Xiao-Yang Liu","Alejandro Lopez-Lira","Benyou Wang","Yanzhao Lai","Hao Wang","Min Peng","Sophia Ananiadou","Jimin Huang"],"abstract":"LLMs have transformed NLP and shown promise in various fields, yet their potential in finance is underexplored due to a lack of comprehensive evaluation benchmarks, the rapid development of LLMs, and the complexity of financial tasks. In this paper, we introduce FinBen, the first extensive open-source evaluation benchmark, including 36 datasets spanning 24 financial tasks, covering seven critical aspects: information extraction (IE), textual analysis, question answering (QA), text generation, risk management, forecasting, and decision-making. FinBen offers several key innovations: a broader range of tasks and datasets, the first evaluation of stock trading, novel agent and Retrieval-Augmented Generation (RAG) evaluation, and three novel open-source evaluation datasets for text summarization, question answering, and stock trading. Our evaluation of 15 representative LLMs, including GPT-4, ChatGPT, and the latest Gemini, reveals several key findings: While LLMs excel in IE and textual analysis, they struggle with advanced reasoning and complex tasks like text generation and forecasting. GPT-4 excels in IE and stock trading, while Gemini is better at text generation and forecasting. Instruction-tuned LLMs improve textual analysis but offer limited benefits for complex tasks such as QA. FinBen has been used to host the first financial LLMs shared task at the FinNLP-AgentScen workshop during IJCAI-2024, attracting 12 teams. Their novel solutions outperformed GPT-4, showcasing FinBen's potential to drive innovation in financial LLMs. All datasets, results, and codes are released for the research community: https://github.com/The-FinAI/PIXIU.","url_abs":"https://arxiv.org/abs/2402.12659v2","url_pdf":"https://arxiv.org/pdf/2402.12659v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"the-finben-an-holistic-financial-benchmark","repo_url":"https://github.com/the-finai/pixiu","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"the-finben-an-holistic-financial-benchmark","repo_url":"https://github.com/chancefocus/pixiu","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"question-answering","task_name":"Question Answering"},{"task_slug":"rag","task_name":"RAG"},{"task_slug":"retrieval-augmented-generation","task_name":"Retrieval-augmented Generation"},{"task_slug":"text-generation","task_name":"Text Generation"},{"task_slug":"text-summarization","task_name":"Text Summarization"}],"methods":[{"method_slug":"absolute-position-encodings","method_name":"Absolute Position Encodings"},{"method_slug":"adam","method_name":"Adam"},{"method_slug":"attention","method_name":"Attention"},{"method_slug":"bpe","method_name":"BPE"},{"method_slug":"dense-connections","method_name":"Dense Connections"},{"method_slug":"dropout","method_name":"Dropout"},{"method_slug":"gpt-4","method_name":"GPT-4"},{"method_slug":"label-smoothing","method_name":"Label Smoothing"},{"method_slug":"layer-normalization","method_name":"Layer Normalization"},{"method_slug":"linear-layer","method_name":"Linear Layer"},{"method_slug":"multi-head-attention","method_name":"Multi-Head Attention"},{"method_slug":"position-wise-feed-forward-layer","method_name":"Position-Wise Feed-Forward Layer"},{"method_slug":"residual-connection","method_name":"Residual Connection"},{"method_slug":"softmax","method_name":"Softmax"},{"method_slug":"transformer","method_name":"Transformer"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2402.12659","atlas_url":"https://app.syntology.ai/?focus=2402.12659","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2402.12659"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/chancefocus/pixiu","reach":{"status":"ok","spdx":"MIT"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/the-finai/pixiu","reach":null}],"summary":{"ran":6,"ran_draft_wrong":2,"unverified":4},"by_repo_kind":{"listed":{"samples":12,"ran":8,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"510528f4db1006bc","entry":"best_demos","repo":"chancefocus/pixiu","repo_kind":"listed","path":"src/factscore_package/atomic_facts.py","file_url":"https://github.com/chancefocus/pixiu/blob/HEAD/src/factscore_package/atomic_facts.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"510528f4db1006bc"}},{"code_sha256_prefix":"8eb846a8e76a79b8","entry":"is_invalid_paragraph_ppl","repo":"chancefocus/pixiu","repo_kind":"listed","path":"src/factscore_package/abstain_detection.py","file_url":"https://github.com/chancefocus/pixiu/blob/HEAD/src/factscore_package/abstain_detection.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"8eb846a8e76a79b8"}},{"code_sha256_prefix":"672bd38d830be48d","entry":"is_invalid_ppl","repo":"chancefocus/pixiu","repo_kind":"listed","path":"src/factscore_package/abstain_detection.py","file_url":"https://github.com/chancefocus/pixiu/blob/HEAD/src/factscore_package/abstain_detection.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"672bd38d830be48d"}},{"code_sha256_prefix":"6a96435eba311b08","entry":"normalize_answer","repo":"chancefocus/pixiu","repo_kind":"listed","path":"src/factscore_package/atomic_facts.py","file_url":"https://github.com/chancefocus/pixiu/blob/HEAD/src/factscore_package/atomic_facts.py","link_basis":"harvester_set","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"6a96435eba311b08"}},{"code_sha256_prefix":"3635046105ae0fce","entry":"remove_citation","repo":"chancefocus/pixiu","repo_kind":"listed","path":"src/factscore_package/abstain_detection.py","file_url":"https://github.com/chancefocus/pixiu/blob/HEAD/src/factscore_package/abstain_detection.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"3635046105ae0fce"}},{"code_sha256_prefix":"371e5c4f5d2d78ca","entry":"single_chat","repo":"chancefocus/pixiu","repo_kind":"listed","path":"src/chatlm.py","file_url":"https://github.com/chancefocus/pixiu/blob/HEAD/src/chatlm.py","link_basis":"plan_row","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"371e5c4f5d2d78ca"}},{"code_sha256_prefix":"925c59b7e44138ab","entry":"softmax","repo":"chancefocus/pixiu","repo_kind":"listed","path":"src/factscore_package/npm.py","file_url":"https://github.com/chancefocus/pixiu/blob/HEAD/src/factscore_package/npm.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"925c59b7e44138ab"}},{"code_sha256_prefix":"13867f872a481bd3","entry":"text_to_sentences","repo":"chancefocus/pixiu","repo_kind":"listed","path":"src/factscore_package/atomic_facts.py","file_url":"https://github.com/chancefocus/pixiu/blob/HEAD/src/factscore_package/atomic_facts.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"13867f872a481bd3"}},{"code_sha256_prefix":"5a6e0b41ccbd8a98","entry":"evaluate","repo":"chancefocus/pixiu","repo_kind":"listed","path":"src/interface.py","file_url":"https://github.com/chancefocus/pixiu/blob/HEAD/src/interface.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"5a6e0b41ccbd8a98"}},{"code_sha256_prefix":"d8c48497dd9cc819","entry":"generate_prompt","repo":"chancefocus/pixiu","repo_kind":"listed","path":"src/interface.py","file_url":"https://github.com/chancefocus/pixiu/blob/HEAD/src/interface.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"d8c48497dd9cc819"}},{"code_sha256_prefix":"9d95c14130837ee4","entry":"make_table","repo":"chancefocus/pixiu","repo_kind":"listed","path":"src/evaluator.py","file_url":"https://github.com/chancefocus/pixiu/blob/HEAD/src/evaluator.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"9d95c14130837ee4"}},{"code_sha256_prefix":"a643d9a7436e58c2","entry":"recover_instruct_llama","repo":"chancefocus/pixiu","repo_kind":"listed","path":"src/factscore_package/download_data.py","file_url":"https://github.com/chancefocus/pixiu/blob/HEAD/src/factscore_package/download_data.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"a643d9a7436e58c2"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}