8 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…
Understanding the Fundamental Design Decisions of Retrieval-Augmented Generation Systems
Shengming Zhao, Yuchen Shao, Yuheng Huang +4
Retrieval-Augmented Generation (RAG) has emerged as a critical technique for enhancing large language model (LLM) capabilities. However, practitioners face significant challenges w…
MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text
Chenjun Li, Cheng Wan, Johannes C. Paetzold
Large language models are now embedded in everyday writing workflows, making reliable AI-generated text detection important for academic integrity, content moderation, and provenan…
Seeing is Coding: On the Effectiveness of Vision Language Models in Code Understanding
Yuling Shi, Chaoxiang Xie, Zhensu Sun +7
Large Language Models (LLMs) have achieved remarkable success in source code understanding, yet as software systems grow in scale, computational efficiency has become a critical bo…
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…