26 citations · 27 across the 5 of their papers we have counts for
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cs.CV2026
Perceive, Interact, Reason: Building Tool-Augmented Visual Agents for Spatial Reasoning
Changye Li, Meng Lu, Yi Wu +1
While recent vision-language models (VLMs) demonstrate strong multimodal understanding, they remain limited in spatial reasoning tasks that require active evidence acquisition and…
cs.AI2026
Verifiable Process Rewards for Agentic Reasoning
Huining Yuan, Zelai Xu, Huaijie Wang +6
Reinforcement learning from verifiable rewards (RLVR) has improved the reasoning capabilities of large language models (LLMs), yet existing approaches predominantly rely on sparse…
cs.LG2026
HTPO: Towards Exploration-Exploitation Balanced Policy Optimization via Hierarchical Token-level Objective Control
Xincheng Yao, Ruoqi Li, Cheng Chen +4
Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a pivotal technique for enhancing the reasoning capabilities of Large Language Models (LLMs). However, the de f…