collaborators

6 papers

cs.AI2026

BizFinBench.v2: Towards Reliable LLMs in Finance via Real-User Data and Offline/Online Bilingual Evaluation

Xin Guo, Rongjunchen Zhang, Guilong Lu +4

Large language models are becoming increasingly significant in financial applications. Nevertheless, prevailing benchmarks are largely dependent on simulated or generic data, which…

q-fin.ST2026

QuantaAlpha: An Evolutionary Framework for LLM-Driven Alpha Mining

Jun Han, Shuo Zhang, Wei Li +14

Financial markets are noisy and non-stationary, making alpha mining highly sensitive to backtest noise and regime shifts. While recent agentic frameworks improve automation, they o…

cs.CR2026

Spider-Sense: Intrinsic Risk Sensing for Efficient Agent Defense with Hierarchical Adaptive Screening

Zhenxiong Yu, Zhi Yang, Zhiheng Jin +19

As large language models (LLMs) evolve into autonomous agents, their real-world applicability has expanded significantly, accompanied by new security challenges. Most existing agen…

cs.AI2026

EvoFSM: Controllable Self-Evolution for Deep Research with Finite State Machines

Shuo Zhang, Chaofa Yuan, Ryan Guo +11

While LLM-based agents have shown promise for deep research, most existing approaches rely on fixed workflows that struggle to adapt to real-world, open-ended queries. Recent work…

q-fin.GN2026

UniFinEval: Towards Unified Evaluation of Financial Multimodal Models across Text, Images and Videos

Zhi Yang, Lingfeng Zeng, Fangqi Lou +16

Multimodal large language models are playing an increasingly significant role in empowering the financial domain, however, the challenges they face, such as multimodal and high-den…

cs.CR2026

FinVault: Benchmarking Financial Agent Safety in Execution-Grounded Environments

Zhi Yang, Runguo Li, Qiqi Qiang +15

Financial agents powered by large language models (LLMs) are increasingly deployed for investment analysis, risk assessment, and automated decision-making, where their abilities to…