6 papers
PINA: Prompt Injection Attack against Navigation Agents
Jiani Liu, Yixin He, Lanlan Fan +5
Navigation agents powered by large language models (LLMs) convert natural language instructions into executable plans and actions. Compared to text-based applications, their securi…
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…
Red Teaming Program Repair Agents: When Correct Patches can Hide Vulnerabilities
Simin Chen, Yixin He, Suman Jana +1
LLM-based agents are increasingly deployed for software maintenance tasks such as automated program repair (APR). APR agents automatically fetch GitHub issues and use backend LLMs…
Learning to Ponder: Adaptive Reasoning in Latent Space
Yixin He, Lumingyuan Tang
Test-time compute has emerged as a key paradigm for enhancing LLM reasoning, yet prevailing approaches like Best-of-N and majority voting apply uniform depth across inputs, wasting…
Recent Advances in Large Langauge Model Benchmarks against Data Contamination: From Static to Dynamic Evaluation
Simin Chen, Yiming Chen, Zexin Li +8
Data contamination has received increasing attention in the era of large language models (LLMs) due to their reliance on vast Internet-derived training corpora. To mitigate the ris…
Diagnosing Memorization in Chain-of-Thought Reasoning, One Token at a Time
Huihan Li, You Chen, Siyuan Wang +4
Large Language Models (LLMs) perform well on reasoning benchmarks but often fail when inputs alter slightly, raising concerns about the extent to which their success relies on memo…