collaborators

8 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…

cs.AI2026

SkillGenBench: Benchmarking Skill Generation Pipelines for LLM Agents

Yifan Zhou, Zhentao Zhang, Ziming Cheng +8

As LLM agents are increasingly built around reusable skills, a central challenge is no longer only whether agents can use provided skills, but whether they can generate correct, re…

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.AI2026

Chain of Mindset: Reasoning with Adaptive Cognitive Modes

Tianyi Jiang, Arctanx An, Hengyi Feng +12

Human problem-solving is never the repetition of a single mindset, by which we mean a distinct mode of cognitive processing. When tackling a specific task, we do not rely on a sing…

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…