7 papers
Length-Unbiased Sequence Policy Optimization: Revealing and Controlling Response Length Variation in RLVR
Fanfan Liu, Youyang Yin, Peng Shi +3
Recent applications of Reinforcement Learning with Verifiable Rewards (RLVR) to Large Language Models (LLMs) and Vision-Language Models (VLMs) have demonstrated significant success…
Learning When to Look: A Disentangled Curriculum for Strategic Perception in Multimodal Reasoning
Siqi Yang, Zilve Gao, Haibo Qiu +5
Multimodal Large Language Models (MLLMs) demonstrate significant potential but remain brittle in complex, long-chain visual reasoning tasks. A critical failure mode is "visual forg…
Reading or Reasoning? Format Decoupled Reinforcement Learning for Document OCR
Yufeng Zhong, Lei Chen, Zhixiong Zeng +8
Reading text from images or scanned documents via OCR models has been a longstanding focus of researchers. Intuitively, text reading is perceived as a straightforward perceptual ta…
Metis-HOME: Hybrid Optimized Mixture-of-Experts for Multimodal Reasoning
Xiaohan Lan, Fanfan Liu, Haibo Qiu +4
Inspired by recent advancements in LLM reasoning, the field of multimodal reasoning has seen remarkable progress, achieving significant performance gains on intricate tasks such as…
Perceptual-Evidence Anchored Reinforced Learning for Multimodal Reasoning
Chi Zhang, Haibo Qiu, Qiming Zhang +6
Reinforcement Learning with Verifiable Rewards (RLVR) has significantly advanced the reasoning capabilities of Large Language Models (LLMs) and is now being applied to Vision-Langu…
Metis-SPECS: Decoupling Multimodal Learning via Self-distilled Preference-based Cold Start
Kun Chen, Peng Shi, Haibo Qiu +4
Reinforcement learning (RL) with verifiable rewards has recently catalyzed a wave of "MLLM-r1" approaches that bring RL to vision language models. Most representative paradigms beg…