most citedGLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning

1 citations · 1 across the 4 of their papers we have counts for

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cs.CL2026

CAVE: Competence-Aware Visual Boundary Evidence Alignment for Video Temporal Grounding

Wei Jia, Zhicong Lu, Yu Chen +6

Large vision-language models (LVLMs) have achieved substantial performance gains in Video Temporal Grounding (VTG) through reinforcement learning (RL). However, existing methods pr…

cs.CL2026

CORA: Analyzing and bridging thinking-answer gap in Multimodal RLVR via Consistency-Oriented Reasoning Alignment

Jiayue Cao, Zhicong Lu, Xuehan Sun +6

Reinforcement learning with verifiable rewards (RLVR) has successfully elicited the reasoning capabilities of large language models, motivating its extension to multimodal scenario…