3 citations · 4 across the 10 of their papers we have counts for
11 papers
CodeMechanic: Bug-Property-Guided Program Mitigation
Han Zheng, Rafaila Galanopoulou, Ilia Shumailov +4
Automated testing discovers vulnerabilities faster than developers can investigate and repair them, leaving an interval in which known memory corruptions remain exploitable. End- t…
SoK: Taxonomizing the Low-Level Attack Surface of Modern Web Browsers
Han Zheng, Qinying Wang, Qiang Liu +1
The web browser remains one of the most exposed remote attack surfaces on end-user systems, and memory-corruption flaws continue to play a central role in real-world browser exploi…
Beyond Jailbreak: Unveiling Risks in LLM Applications Arising from Blurred Capability Boundaries
Yunyi Zhang, Shibo Cui, Baojun Liu +4
LLM applications (i.e., LLM apps) leverage the powerful capabilities of LLMs to provide users with customized services, revolutionizing traditional application development. While t…
AlphaOPT: Formulating Optimization Programs with Self-Improving LLM Experience Library
Minwei Kong, Ao Qu, Xiaotong Guo +12
Optimization modeling underlies critical decision-making across industries, yet remains difficult to automate: natural-language problem descriptions must be translated into precise…
Cuckoo Attack: Stealthy and Persistent Attacks Against AI-IDE
Xinpeng Liu, Junming Liu, Peiyu Liu +5
Modern AI-powered Integrated Development Environments (AI-IDEs) are increasingly defined by an Agent-centric architecture, where an LLM-powered Agent is deeply integrated to autono…
Safe-SAIL: Towards a Fine-grained Safety Landscape of Large Language Models via Sparse Autoencoder Interpretation Framework
Jiaqi Weng, Han Zheng, Hanyu Zhang +6
Sparse autoencoders (SAEs) enable interpretability research by decomposing entangled model activations into monosemantic features. However, under what circumstances SAEs derive mos…
SAFEFLOW: A Principled Protocol for Trustworthy and Transactional Autonomous Agent Systems
Peiran Li, Xinkai Zou, Zhuohang Wu +9
Recent advances in large language models (LLMs) and vision-language models (VLMs) have enabled powerful autonomous agents capable of complex reasoning and multi-modal tool use. Des…
CP-Router: An Uncertainty-Aware Router Between LLM and LRM
Jiayuan Su, Fulin Lin, Zhaopeng Feng +7
Recent advances in Large Reasoning Models (LRMs) have significantly improved long-chain reasoning capabilities over Large Language Models (LLMs). However, LRMs often produce unnece…
Fixing 7,400 Bugs for 1$: Cheap Crash-Site Program Repair
Han Zheng, Ilia Shumailov, Tianqi Fan +2
The rapid advancement of bug-finding techniques has led to the discovery of more vulnerabilities than developers can reasonably fix, creating an urgent need for effective Automated…
CCoE: A Compact and Efficient LLM Framework with Multi-Expert Collaboration for Resource-Limited Settings
Shaomang Huang, Jianfeng Pan, Min Peng +1
Large Language Models (LLMs) have achieved exceptional performance across diverse domains through training on massive datasets. However, scaling LLMs to support multiple downstream…
FishFuzz: Throwing Larger Nets to Catch Deeper Bugs
Han Zheng, Jiayuan Zhang, Yuhang Huang +6
Greybox fuzzing is the de-facto standard to discover bugs during development. Fuzzers execute many inputs to maximize the amount of reached code. Recently, Directed Greybox Fuzzers…