1 citations · 1 across the 1 of their papers we have counts for
9 papers
RedCoder: Automated Multi-Turn Red Teaming for Code LLMs
Wenjie Jacky Mo, Qin Liu, Xiaofei Wen +5
Large Language Models (LLMs) for code generation (i.e., Code LLMs) have demonstrated impressive capabilities in AI-assisted software development and testing. However, recent studie…
Triaging Threats to Specialized Guardrails
Wenjie Jacky Mo, Xiaofei Wen, Rui Cai +6
Building robust safety guardrails is essential for deploying Large Language Models across diverse real-world applications. However, this goal remains challenging because safety ris…
Learning Efficient Guardrails for Compliance
Xiaofei Wen, Wenjie Jacky Mo, Yanan Xie +2
Autonomous web agents are increasingly deployed for long-horizon tasks, yet their ability to adhere to real-world policies remains critically underexplored compared to standard saf…
When Vision Speaks for Sound
Xiaofei Wen, Wenjie Jacky Mo, Xingyu Fu +6
Despite rapid progress in video-capable MLLMs, we find that their apparent audio understanding in videos is often vision-driven: models rely on visual cues to infer or hallucinate…
DebugLM: Learning Traceable Training Data Provenance for LLMs
Wenjie Jacky Mo, Qin Liu, Xiaofei Wen +3
Large language models (LLMs) are trained through multi-stage pipelines over heterogeneous data sources, yet developers lack a principled way to pinpoint the specific data responsib…
OmniGuard: Unified Omni-Modal Guardrails with Deliberate Reasoning
Boyu Zhu, Xiaofei Wen, Wenjie Jacky Mo +4
Omni-modal Large Language Models (OLLMs) that process text, images, videos, and audio introduce new challenges for safety and value guardrails in human-AI interaction. Prior guardr…