21 citations · 33 across the 9 of their papers we have counts for
10 papers
NTDH: Complex Reasoning for Comprehensive Affective Analysis
Tianlei Zhu, Zhiwei Liu, Yuyan Wang +2
Comprehensive affective analysis is challenging for two reasons: it spans heterogeneous prediction tasks with continuous, ordinal, and multi-label outputs, and affective meaning is…
Herculean: An Agentic Benchmark for Financial Intelligence
Xueqing Peng, Zhuohan Xie, Yupeng Cao +60
As AI agents advance, the central question is no longer whether they can solve isolated financial tasks, but whether their capabilities generalize across complete professional work…
FinAuditing: A Financial Taxonomy-Structured Multi-Document Benchmark for Evaluating LLMs
Yan Wang, Keyi Wang, Shanshan Yang +12
Going beyond simple text processing, financial auditing requires detecting semantic, structural, and numerical inconsistencies across large-scale disclosures. As financial reports…
MultiFinBen: Benchmarking Large Language Models for Multilingual and Multimodal Financial Application
Xueqing Peng, Lingfei Qian, Yan Wang +44
Real-world financial analysis involves information across multiple languages and modalities, from reports and news to scanned filings and meeting recordings. Yet most existing eval…
FinTagging: Benchmarking LLMs for Extracting and Structuring Financial Information
Yan Wang, Lingfei Qian, Xueqing Peng +18
Accurate interpretation of numerical data in financial reports is critical for markets and regulators. Although XBRL (eXtensible Business Reporting Language) provides a standard fo…
FLAG-Trader: Fusion LLM-Agent with Gradient-based Reinforcement Learning for Financial Trading
Guojun Xiong, Zhiyang Deng, Keyi Wang +10
Large language models (LLMs) fine-tuned on multimodal financial data have demonstrated impressive reasoning capabilities in various financial tasks. However, they often struggle wi…
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications
Jimin Huang, Mengxi Xiao, Dong Li +41
Financial LLMs hold promise for advancing financial tasks and domain-specific applications. However, they are limited by scarce corpora, weak multimodal capabilities, and narrow ev…
Dólares or Dollars? Unraveling the Bilingual Prowess of Financial LLMs Between Spanish and English
Xiao Zhang, Ruoyu Xiang, Chenhan Yuan +8
Despite Spanish's pivotal role in the global finance industry, a pronounced gap exists in Spanish financial natural language processing (NLP) and application studies compared to En…
FinBen: A Holistic Financial Benchmark for Large Language Models
Qianqian Xie, Weiguang Han, Zhengyu Chen +31
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 devel…
Deficiency of Large Language Models in Finance: An Empirical Examination of Hallucination
Haoqiang Kang, Xiao-Yang Liu
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. Despite th…