6 citations · 12 across the 11 of their papers we have counts for
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cs.CV2025
ReEXplore: Improving MLLMs for Embodied Exploration with Contextualized Retrospective Experience Replay
Gengyuan Zhang, Mingcong Ding, Jingpei Wu +2
Embodied exploration is a target-driven process that requires embodied agents to possess fine-grained perception and knowledge-enhanced decision making. While recent attempts lever…
cs.AI2025
GroundedPRM: Tree-Guided and Fidelity-Aware Process Reward Modeling for Step-Level Reasoning
Yao Zhang, Yu Wu, Haowei Zhang +6
Process Reward Models (PRMs) aim to improve multi-step reasoning in Large Language Models (LLMs) by supervising intermediate steps and identifying errors. However, building effecti…
cs.CR2025
Strong but Brittle: Simple Attacks Subvert Reasoning-based Safety Guardrails
Shuo Chen, Zhen Han, Haokun Chen +6
Open-weight Large Reasoning Models (LRMs) are approaching the capabilities of their frontier counterparts but pose significant safety concerns, as they are difficult to patch or mo…