3 papers
cs.CV2026
IVR-R1: Refining Trajectories through Iterative Visual-Grounded Reasoning in Reinforcement Learning
Chenghao Li, Fusheng Hao, Xikai Zhang +5
Multimodal large language models via reinforcement learning (RL) have demonstrated remarkable capabilities in complex visual reasoning tasks, yet they remain limited in long-horizo…
cs.LG2025
Gradient-based Fine-Tuning through Pre-trained Model Regularization
Xuanbo Liu, Liu Liu, Fuxiang Wu +2
Large pre-trained models have demonstrated extensive applications across various fields. However, fine-tuning these models for specific downstream tasks demands significant computa…
cs.AI2025
SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation
Yanwei Ren, Haotian Zhang, Fuxiang Wu +4
Enhancing large language models by simply scaling up datasets has begun to yield diminishing returns, shifting the spotlight to data quality. Monte Carlo Tree Search (MCTS) has eme…