collaborators

8 papers

cs.SE2026

MineValiCoder: Reliable Code Generation with Test Case Quality Mining and Bipartite Graph-Based Mutual Validation

Zhen Zhao, Qihang Yang, Feifei Dai +2

Large Language Model (LLM)-based Test-Driven Development (TDD) has advanced automated code generation. However, existing approaches depend heavily on human-crafted test cases and c…

cs.SE2026

SkillOpt-Lite: Better and Faster Agent Self-evolution via One Line of Vibe

Yifei Shen, Bo Li, Xinjie Zhang

While skill optimization for autonomous agents has gained traction, existing methods rely on complex pipelines. This leaves a fundamental question unaddressed: What constitutes a m…

cs.CR2026

Unsafer in Many Turns: Benchmarking and Defending Multi-Turn Safety Risks in Tool-Using Agents

Xu Li, Simon Yu, Minzhou Pan +5

LLM-based agents are becoming increasingly capable, yet their safety lags behind. This creates a gap between what agents can do and should do. This gap widens as agents engage in m…

cs.CL2026

Reasoning over Boundaries: Enhancing Specification Alignment via Test-time Deliberation

Haoran Zhang, Yafu Li, Xuyang Hu +4

Large language models (LLMs) are increasingly applied in diverse real-world scenarios, each governed by bespoke behavioral and safety specifications (spec) custom-tailored by users…

cs.SE2026

GUI Agents for Continual Game Generation

Yixu Huang, Bo Li, Na Li +8

Generating a game is not the same as making one that can be played. Despite advances in code generation, existing approaches treat game generation as one-shot translation from prom…

cs.SE2026

The Limits of Long-Context Reasoning in Automated Bug Fixing

Ravi Raju, Mengmeng Ji, Shubhangi Upasani +2

Rapidly increasing context lengths have led to the assumption that large language models (LLMs) can directly reason over entire codebases. Concurrently, recent advances in LLMs hav…