5 papers · 1 filter
Informed Masking: Structure-Aware Perturbation for Reinforcement Learning in Diffusion Large Language Models
Xiaoyi Yu, Enver Sangineto, Pei Fu +6
Diffusion Large Language Models (dLLMs) have emerged as an efficient alternative to autoregressive models, yet aligning them via Reinforcement Learning (RL) requires likelihood sur…
Doc-V*:Coarse-to-Fine Interactive Visual Reasoning for Multi-Page Document VQA
Yuanlei Zheng, Pei Fu, Hang Li +9
Multi-page Document Visual Question Answering requires reasoning over semantics, layouts, and visual elements in long, visually dense documents. Existing OCR-free methods face a tr…
CoME: Empowering Channel-of-Mobile-Experts with Informative Hybrid-Capabilities Reasoning
Yuxuan Liu, Weikai Xu, Kun Huang +9
Mobile Agents can autonomously execute user instructions, which requires hybrid-capabilities reasoning, including screen summary, subtask planning, action decision and action funct…
Restoring Exploration after Post-Training: Latent Exploration Decoding for Large Reasoning Models
Wenhui Tan, Fiorenzo Parascandolo, Enver Sangineto +6
Large Reasoning Models (LRMs) have recently achieved strong mathematical and code reasoning performance through Reinforcement Learning (RL) post-training. However, we show that mod…
Think Silently, Think Fast: Dynamic Latent Compression of LLM Reasoning Chains
Wenhui Tan, Jiaze Li, Jianzhong Ju +3
Large Language Models (LLMs) achieve superior performance through Chain-of-Thought (CoT) reasoning, but these token-level reasoning chains are computationally expensive and ineffic…