18 papers
SCOPE: Evolving Symbolic World for Planning in Open-Ended Environments
Yundaichuan Zhan, Minghe Gao, Zhongqi Yue +7
Recent works have explored integrating Vision-Language Models (VLMs) with classical planners that rely on symbolic representations of planning problems to generate long-horizon pla…
CARE: Competence-Aware Reward Shaping for Adaptive Reasoning Length in Video-MLLMs
Chengwen Liu, Hao Peng, Jisheng Dang +3
In multimodal video reasoning, reinforcement learning-based methods typically rely on simplistic and inflexible reasoning-length control strategies that fail to adapt to the model'…
Reasoning as Intersection: Consensus-Frame Alignment for Visual Focus in Video-MLLMs
Chengwen Liu, Zhe Huang, Jisheng Dang +3
Reinforcement learning has improved the reasoning ability of large language models, but applying outcome-only rewards to video multimodal large language models (Video-MLLMs) provid…
A Robust Point Cloud Analysis Framework Inspired By Primary Visual Cortex
Jisheng Dang, Dengyue Pan, Delin Deng +6
Despite significant advancements in point cloud analysis, reducing energy consumption and improving robustness remain understudied, largely due to the inherent limitations of Convo…
MODF-SIR: A Multi-agent Omni-modal Distilled Framework for Social Intelligence Reasoning
Shang Ma, Jisheng Dang, Wencan Zhang +6
We propose a multi-agent collaborative framework built upon a lightweight Multimodal Large Language Model (MLLM), specifically designed for social intelligence reasoning. A key fea…
On the Implicit Reward Overfitting and the Low-rank Dynamics in RLVR
Hao Ye, Jisheng Dang, Junfeng Fang +7
Recent extensive research has demonstrated that the enhanced reasoning capabilities acquired by models through Reinforcement Learning with Verifiable Rewards (RLVR) are primarily c…