activity
20242026
most citedOpen-FinLLMs: Open Multimodal Large Language Models for Financial Applications

4 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

eess.AS2026

Listen, Look, Drive: Coupling Audio Instructions for User-aware VLA-based Autonomous Driving

Ziang Guo, Feng Yang, Xuefeng Zhang +6

Vision Language Action (VLA) models promise an open-vocabulary interface that can translate perceptual ambiguity into semantically grounded driving decisions, yet they still treat…

cs.CL2025

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…

cs.CL2025

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…

cs.DB2024★ 1 cited

LR-SQL: A Supervised Fine-Tuning Method for Text2SQL Tasks under Low-Resource Scenarios

Wen Wuzhenghong, Zhang Yongpan, Pan Su +3

Large language models revolutionize Text2SQL through supervised fine-tuning, yet a crucial limitation is overlooked: the complexity of databases leads to an increased context lengt…

cs.CL2024★ 4 cited

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…