11 papers
Effective LLM Code Refinement via Property-Oriented and Structurally Minimal Feedback
Lehan He, Zeren Chen, Zhe Zhang +2
LLMs excel at code generation, yet ensuring the functional correctness of their outputs remains a persistent challenge. While recent studies have applied Test-Driven Development (T…
HomeGuard: VLM-based Embodied Safeguard for Identifying Contextual Risk in Household Task
Xiaoya Lu, Yijin Zhou, Zeren Chen +6
Vision-Language Models (VLMs) empower embodied agents to execute complex instructions, yet they remain vulnerable to contextual safety risks where benign commands become hazardous…
ProGuard: Towards Proactive Multimodal Safeguard
Shaohan Yu, Lijun Li, Chenyang Si +2
The rapid evolution of generative models has led to a continuous emergence of multimodal safety risks, exposing the limitations of existing defense methods. To address these challe…
IS-Bench: Evaluating Interactive Safety of VLM-Driven Embodied Agents in Daily Household Tasks
Xiaoya Lu, Zeren Chen, Xuhao Hu +5
Flawed planning from VLM-driven embodied agents poses significant safety hazards, hindering their deployment in real-world household tasks. However, existing static, non-interactiv…
Geometrically-Constrained Agent for Spatial Reasoning
Zeren Chen, Xiaoya Lu, Zhijie Zheng +6
Vision Language Models (VLMs) exhibit a fundamental semantic-to-geometric gap in spatial reasoning: they excel at qualitative semantic inference but their reasoning operates within…
Systematic Reward Gap Optimization for Mitigating VLM Hallucinations
Lehan He, Zeren Chen, Zhelun Shi +3
The success of Direct Preference Optimization (DPO) in mitigating hallucinations in Vision Language Models (VLMs) critically hinges on the true reward gaps within preference pairs.…