1 citations · 1 across the 5 of their papers we have counts for
5 papers
Automated jailbreak attack targeting multiple defense strategies
Qi Wang, Chengcheng Wan, Weijia He +4
Large language models (LLMs) have demonstrated remarkable capabilities across a wide range of tasks. However, their safety remains a critical concern due to their susceptibility to…
EffiSkill: Agent Skill Based Automated Code Efficiency Optimization
Zimu Wang, Yuling Shi, Mengfan Li +4
Code efficiency is a fundamental aspect of software quality, yet how to harness large language models (LLMs) to optimize programs remains challenging. Prior approaches have sought…
Pruning the Unsurprising: Efficient LLM Reasoning via First-Token Surprisal
Wenhao Zeng, Yaoning Wang, Chao Hu +4
Large Reasoning Models (LRMs) have demonstrated remarkable capabilities by scaling up the length of Chain-of-Thought (CoT). However, excessively long reasoning traces pose substant…
CodeCipher: Learning to Obfuscate Source Code Against LLMs
Yalan Lin, Chengcheng Wan, Yixiong Fang +1
While large code language models have made significant strides in AI-assisted coding tasks, there are growing concerns about privacy challenges. The user code is transparent to the…
From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging
Yuling Shi, Songsong Wang, Chengcheng Wan +2
While large language models have made significant strides in code generation, the pass rate of the generated code is bottlenecked on subtle errors, often requiring human interventi…