21 citations · 38 across the 15 of their papers we have counts for
18 papers
IF-MAP: Influence-Function-Inspired Agent Prioritization in Multi-Agent Systems
Jie Mao, Pingchen Lu, Zikun Qu +6
Improving every agent in an LLM-based multi-agent system can be prohibitively costly, making it important to identify which agent should be prioritized to achieve the greatest syst…
TimeLitmus: A Diagnostic Benchmark for Cross-Modal Understanding and Explanation Faithfulness in Event-Conditioned Time-Series Prediction
Jie Gong, Maowei Jiang, Zhiwei Liu +6
Large language models (LLMs) are increasingly used to make predictions from numerical time-series histories and textual events. Yet accuracy alone cannot reveal whether correct ans…
ShiJianBench: From Dialogue to Decision for Long-Horizon Evaluation of Investment Advisors
Jie Gong, Maowei Jiang, Zhiwei Liu +14
Conversational investment advisors influence not only what users know, but also how they make subsequent decisions as market conditions evolve. Existing evaluations primarily asses…
Not All Tokens Are Equal: Inflation-Aware Routing for Agentic LLM Systems
Heming Fu, Shan Lin, Qianqian Xie +1
When a language model fails to answer a query on the first attempt, an agentic system retries, consuming additional tokens each time. This retry overhead creates a gap between what…
Concordia: Self-Improving Synthetic Tables for Federated LLMs
Jimin Huang, Duanyu Feng, Nuo Chen +8
Federated learning (FL) enables training large language models (LLMs) without sharing raw data, but adapting LLMs under strict data isolation and non-IID client distributions remai…
MOIRA: Policy Memory and Belief Revision for Language-Model Agents in Non-Stationary Pair Trading
Polydoros Giannouris, Yuechen Jiang, Lingfei Qian +5
Many sequential decision-making problems exhibit hierarchical structure, where high-level semantic choices constrain downstream actions and feedback is delayed and ambiguous. Learn…
MeCaMIL: Causality-Aware Multiple Instance Learning for Fair and Interpretable Whole Slide Image Diagnosis
Yiran Song, Yikai Zhang, Shuang Zhou +6
Multiple instance learning (MIL) has emerged as the dominant paradigm for whole slide image (WSI) analysis in computational pathology, achieving strong diagnostic performance throu…
FinCriticalED: A Visual Benchmark for Financial Fact-Level OCR
Yueru He, Xueqing Peng, Yupeng Cao +13
Recent progress in multimodal large language models (MLLMs) has substantially improved document understanding, yet strong optical character recognition (OCR) performance on surface…
When Agents Trade: Live Multi-Market Trading Benchmark for LLM Agents
Lingfei Qian, Xueqing Peng, Yan Wang +14
Although Large Language Model (LLM)-based agents are increasingly used in financial trading, it remains unclear whether they can reason and adapt in live markets, as most studies t…
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…
MARLIN: Multi-Agent Reinforcement Learning with Murmuration Intelligence and LLM Guidance for Reservoir Management
Heming Fu, Shan Lin, Guojun Xiong
As climate change intensifies extreme weather events, water disasters pose growing threats to global communities, making adaptive reservoir management critical for protecting vulne…
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…
INVESTORBENCH: A Benchmark for Financial Decision-Making Tasks with LLM-based Agent
Haohang Li, Yupeng Cao, Yangyang Yu +12
Recent advancements have underscored the potential of large language model (LLM)-based agents in financial decision-making. Despite this progress, the field currently encounters tw…
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…
FinCon: A Synthesized LLM Multi-Agent System with Conceptual Verbal Reinforcement for Enhanced Financial Decision Making
Yangyang Yu, Zhiyuan Yao, Haohang Li +14
Large language models (LLMs) have demonstrated notable potential in conducting complex tasks and are increasingly utilized in various financial applications. However, high-quality…
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…