10 papers
Humans are Missing from AI Coding Agent Research
Zora Z. Wang, John Yang, Kilian Lieret +10
Recent progress in AI coding agent research has led to rapid improvements in agents' ability to autonomously perform complex software engineering tasks, from editing large codebase…
SkillHarm: Lifecycle-Aware Skill-Based Attacks via Automated Construction
Yuting Ning, Zhehao Zhang, Yash Kumar Lal +8
Agent skills occupy a privileged position in the agent workflow, as agents are expected to implicitly follow and execute them, rendering third-party skills a vulnerable attack surf…
CodeClash: Benchmarking Goal-Oriented Software Engineering
John Yang, Kilian Lieret, Joyce Yang +6
Current benchmarks for coding evaluate language models (LMs) on concrete, well-specified tasks such as fixing specific bugs or writing targeted tests. However, human programmers do…
SecureForge: Finding and Preventing Vulnerabilities in LLM-Generated Code via Prompt Optimization
Houjun Liu, Lisa Einstein, John Yang +5
LLM coding agents now generate code at an unprecedented scale, yet LLM-generated code introduces cybersecurity vulnerabilities into codebases without human involvement. Even when f…
ProgramBench: Can Language Models Rebuild Programs From Scratch?
John Yang, Kilian Lieret, Jeffrey Ma +9
Turning ideas into full software projects from scratch has become a popular use case for language models. Agents are being deployed to seed, maintain, and grow codebases over exten…
The Rise of AI Companions: Interaction with AI Companions and Psychological Well-being
Yutong Zhang, Dora Zhao, Jeffrey T. Hancock +2
As large language model (LLM)-enhanced chatbots become increasingly expressive and socially responsive, many users begin forming companionship-like bonds with them. This study inve…