activity
20242026
most citedWhen AI Meets Finance (StockAgent): Large Language Model-based Stock Trading in Simulated Real-world Environments

4 citations · 4 across the 1 of their papers we have counts for

collaborators

5 papers

q-fin.TR20264 cited

When AI Meets Finance (StockAgent): Large Language Model-based Stock Trading in Simulated Real-world Environments

Chong Zhang, Xinyi Liu, Zhongmou Zhang +10

Can AI Agents simulate real-world trading environments to investigate the impact of external factors on stock trading activities (e.g., macroeconomics, policy changes, company fund…

cs.CL2025

Knowledge Graph Large Language Model (KG-LLM) for Link Prediction

Dong Shu, Tianle Chen, Mingyu Jin +3

The task of multi-hop link prediction within knowledge graphs (KGs) stands as a challenge in the field of knowledge graph analysis, as it requires the model to reason through and u…

cs.CL2025

Health-LLM: Personalized Retrieval-Augmented Disease Prediction System

Qinkai Yu, Mingyu Jin, Dong Shu +8

Recent advancements in artificial intelligence (AI), especially large language models (LLMs), have significantly advanced healthcare applications and demonstrated potentials in int…

cs.CL2025

AttackEval: How to Evaluate the Effectiveness of Jailbreak Attacking on Large Language Models

Dong Shu, Chong Zhang, Mingyu Jin +3

Jailbreak attacks represent one of the most sophisticated threats to the security of large language models (LLMs). To deal with such risks, we introduce an innovative framework tha…

cs.CL2024

Target-driven Attack for Large Language Models

Chong Zhang, Mingyu Jin, Dong Shu +3

Current large language models (LLM) provide a strong foundation for large-scale user-oriented natural language tasks. Many users can easily inject adversarial text or instructions…