activity
20242026
collaborators

13 papers

cs.CL2026

Multi-User Large Language Model Agents

Shu Yang, Shenzhe Zhu, Hao Zhu +5

Large language models (LLMs) and LLM-based agents are increasingly deployed as assistants in planning and decision making, yet most existing systems are implicitly optimized for a…

cs.CL2026

On Safety Risks in Experience-Driven Self-Evolving Agents

Weixiang Zhao, Yichen Zhang, Yingshuo Wang +8

Experience-driven self-evolution has emerged as a promising paradigm for improving the autonomy of large language model agents, yet its reliance on self-curated experience introduc…

cs.LG2026

Structural Evaluation Metrics for SVG Generation via Leave-One-Out Analysis

Haonan Zhu, Adrienne Deganutti, Elad Hirsch +1

SVG generation is typically evaluated by comparing rendered outputs to reference images, which captures visual similarity but not the structural properties that make SVG editable,…

cs.LG2026

Do Transformers Have the Ability for Periodicity Generalization?

Huanyu Liu, Ge Li, Yihong Dong +7

Large language models (LLMs) based on the Transformer have demonstrated strong performance across diverse tasks. However, current models still exhibit substantial limitations in ou…

cs.SE2026

KOCO-BENCH: Can Large Language Models Leverage Domain Knowledge in Software Development?

Xue Jiang, Ge Li, Jiaru Qian +12

Large language models (LLMs) excel at general programming but struggle with domain-specific software development, necessitating domain specialization methods for LLMs to learn and…

cs.SE2025

VulInstruct: Teaching LLMs Root-Cause Reasoning for Vulnerability Detection via Security Specifications

Hao Zhu, Jia Li, Cuiyun Gao +7

Large language models (LLMs) have achieved remarkable progress in code understanding tasks. However, they demonstrate limited performance in vulnerability detection and struggle to…