2 citations · 3 across the 8 of their papers we have counts for
8 papers
Turning Bias into Bugs: Bandit-Guided Style Manipulation Attacks on LLM Judges
Xianglin Yang, Bryan Hooi, Gelei Deng +2
The known stylistic biases in LLM judges, such as a preference for verbosity or specific sentence structures, present an underexplored security vulnerability. In this work, we intr…
Inverting the Shield: Systematically Generating Safety Tests from Policy Specifications
Xiaoyue Lu, Xianglin Yang, Haijun Liu +4
The widespread integration of Large Language Models (LLMs) necessitates rigorous and systematic safety evaluation. Existing paradigms either rely on constructed benchmarks to asses…
From Patches to Trajectories: Privileged Process Supervision for Software-Engineering Agents
Murong Ma, Tianyu Chen, Yun Lin +7
Supervised fine-tuning (SFT) on long teacher trajectories is the dominant way to instill investigation and reasoning in open software-engineering (SWE) agents. Since every retained…
LLM-enabled Applications Require System-Level Threat Monitoring
Yedi Zhang, Haoyu Wang, Xianglin Yang +2
LLM-enabled applications are rapidly reshaping the software ecosystem by using large language models as core reasoning components for complex task execution. This paradigm shift, h…
LLM as an Execution Estimator: Recovering Missing Dependency for Practical Time-travelling Debugging
Yunrui Pei, Hongshu Wang, Wenjie Zhang +3
Determining the dynamic data dependency of a step that reads a variable is challenging. It typically requires either exhaustive instrumentation, which becomes prohibitively exp…
Generating Project-Specific Test Cases with Requirement Validation Intention
Binhang Qi, Yun Lin, Xinyi Weng +5
Test cases are valuable assets for maintaining software quality. State-of-the-art automated test generation techniques typically focus on maximizing program branch coverage or tran…
Towards Large Language Model Aided Program Refinement
Yufan Cai, Zhe Hou, Xiaokun Luan +4
Program refinement involves correctness-preserving transformations from formal high-level specification statements into executable programs. Traditional verification tool support f…
Neural Surveillance: Live-Update Visualization of Latent Training Dynamics
Xianglin Yang, Jin Song Dong
Monitoring the inner state of deep neural networks is essential for auditing the learning process and enabling timely interventions. While conventional metrics like validation loss…