From the 1 of 12 linked papers with an AI index.
12 papers
Distill What the Student Can See: Fisher-Projected On-Policy Distillation for Vision-Language Models
Leyan Xue, Feng Xiong, Mingjun Ma +1
On-policy distillation (OPD) samples trajectories from the current student policy and minimizes token-level divergence between student and teacher next-token distributions at prefi…
Correcting What You Cannot See: Credit Assignment for Perception Distillation in Multimodal Reasoners
Feng Xiong, Leyan Xue, Hongyu Lin
The paper proposes Perception-Correction Distillation (PCD), a label‑free method that uses downstream failures and teacher‑student disagreement to pinpoint and correct perception e…
Visually-Guided Policy Optimization for Multimodal Reasoning
Zengbin Wang, Feng Xiong, Liang Lin +5
Reinforcement learning with verifiable rewards (RLVR) has significantly advanced the reasoning ability of vision-language models (VLMs). However, the inherent text-dominated nature…
Ace-Skill: Bootstrapping Multimodal Agents with Prioritized and Clustered Evolution
Feng Xiong, Zengbin Wang, Yong Wang +5
Self-evolving agents present a promising path toward continual adaptation by distilling task interactions into reusable knowledge artifacts. In practice, this paradigm remains hind…
MMKG-RDS: Reasoning Data Synthesis via Deep Mining of Multimodal Knowledge Graphs
Lun Zhan, Feng Xiong, Huanyong Liu +2
Synthesizing high-quality training data is crucial for enhancing domain models' reasoning abilities. Existing methods face limitations in long-tail knowledge coverage, effectivenes…
Active Zero: Self-Evolving Vision-Language Models through Active Environment Exploration
Jinghan He, Junfeng Fang, Feng Xiong +5
Self-play has enabled large language models to autonomously improve through self-generated challenges. However, existing self-play methods for vision-language models rely on passiv…