14 papers
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…
Faithful-MR1: Faithful Multimodal Reasoning via Anchoring and Reinforcing Visual Attention
Changyuan Tian, Zhicong Lu, Huaxing Liu +7
Reinforcement learning with verifiable rewards (RLVR) has emerged as a promising paradigm for advancing complex reasoning in large language models, and recent work extends RLVR to…
Debiased Model-based Representations for Sample-efficient Continuous Control
Jiafei Lyu, Zichuan Lin, Scott Fujimoto +5
Model-based representations recently stand out as a promising framework that embeds latent dynamics information into the representations for downstream off-policy actor-critic lear…
HiRO-Nav: Hybrid ReasOning Enables Efficient Embodied Navigation
He Zhao, Yijun Yang, Zichuan Lin +2
Embodied navigation agents built upon large reasoning models (LRMs) can handle complex, multimodal environmental input and perform grounded reasoning per step to improve sequential…
UI-Voyager: A Self-Evolving GUI Agent Learning via Failed Experience
Zichuan Lin, Feiyu Liu, Yijun Yang +9
Autonomous mobile GUI agents have attracted increasing attention along with the advancement of Multimodal Large Language Models (MLLMs). However, existing methods still suffer from…
AdaptVision: Efficient Vision-Language Models via Adaptive Visual Acquisition
Zichuan Lin, Yicheng Liu, Yang Yang +2
Vision-Language Models (VLMs) have achieved remarkable success in visual question answering tasks, but their reliance on large numbers of visual tokens introduces significant compu…