8 papers
TRIM: Reducing AI-Generated CodeSlop via Agent Trajectory Minimization
Alex Mathai, Shobini Iyer, Aleksandr Nogikh +4
Coding agents are increasingly used to accelerate code generation in many downstream tasks, such as fixing bugs, building applications, and prototyping. However, despite their valu…
kAgent: An execution-guided crash resolution agent for the Linux kernel
Alex Mathai, Chenxi Huang, Suwei Ma +7
Fuzzing frameworks like syzkaller have uncovered thousands of Linux kernel crashes, many of which are critical and security-sensitive. However, the ability to rapidly repair these…
Outrunning LLM Cutoffs: A Live Kernel Crash Resolution Benchmark for All
Chenxi Huang, Alex Mathai, Feiyang Yu +7
Repairing system crashes discovered by kernel fuzzers like Syzkaller is a critical yet underexplored challenge in software engineering. While recent works have introduced Large Lan…
Proactive defense against LLM Jailbreak
Weiliang Zhao, Jinjun Peng, Daniel Ben-Levi +2
The proliferation of powerful large language models (LLMs) has necessitated robust safety alignment, yet these models remain vulnerable to evolving adversarial attacks, including m…
SWE-Spot: Building Small Repo-Experts with Repository-Centric Learning
Jinjun Peng, Magnus Saebo, Tianjun Zhong +5
The deployment of coding agents in privacy-sensitive and resource-constrained environments drives the demand for capable open-weight Small Language Models (SLMs). However, they suf…
Your Compiler is Backdooring Your Model: Understanding and Exploiting Compilation Inconsistency Vulnerabilities in Deep Learning Compilers
Simin Chen, Jinjun Peng, Yixin He +2
Deep learning (DL) compilers are core infrastructure in modern DL systems, offering flexibility and scalability beyond vendor-specific libraries. This work uncovers a fundamental v…