5 papers
Validity-Aware Jailbreak Evaluation for Large Language Models
Qilong Wu, Sahil Wadhwa, Pranab Mohanty +2
Jailbreak robustness has become central to large language model (LLM) safety evaluation, yet prevailing methodologies rely primarily on refusal behavior, semantic resemblance, and…
Verifiers in the Loop: Decoding Time Verification for Code Translation
Tianyang Zhou, Somesh Jha, Mihai Christodorescu +2
Test-time scaling is an important mechanism for improving large language models, especially on tasks with deterministic verifiers. Code translation is a canonical example: the sour…
Systematic Scaling Analysis of Jailbreak Attacks in Large Language Models
Xiangwen Wang, Ananth Balashankar, Varun Chandrasekaran
Large language models remain vulnerable to jailbreak attacks, yet we still lack a systematic understanding of how jailbreak success scales with attacker effort across methods, mode…
The Erasure Illusion: Stress-Testing the Generalization of LLM Forgetting Evaluation
Hengrui Jia, Taoran Li, Jonas Guan +1
Machine unlearning aims to remove specific data influences from trained models, a capability essential for adhering to copyright laws and ensuring AI safety. Current unlearning met…
SoK: Understanding (New) Security Issues Across AI4Code Use Cases
Qilong Wu, Taoran Li, Tianyang Zhou +1
AI-for-Code (AI4Code) systems are reshaping software engineering, with tools like GitHub Copilot accelerating code generation, translation, and vulnerability detection. Alongside t…