6 papers · 1 filter
Visual Para-Thinker++: A Single-Policy Multi-Agent Framework for Visual Reasoning
Haoran Xu, Hongyu Wang, Yifei Gao +4
Visual reasoning requires integrating evidence distributed across regions, attributes, and relations, making single-chain reasoning prone to early perceptual commitment and halluci…
Federated Balanced Learning
Jiaze Li, Haoran Xu, Wanyi Wu +9
Federated learning is a paradigm of joint learning in which clients collaborate by sharing model parameters instead of data. However, in the non-iid setting, the global model exper…
Visual Para-Thinker: Divide-and-Conquer Reasoning for Visual Comprehension
Haoran Xu, Hongyu Wang, Jiaze Li +5
Existing LLM test-time scaling laws emphasize the emergence of self-reflective behaviors through extended reasoning length. Nevertheless, this vertical scaling strategy often encou…
Video-OPD: Efficient Post-Training of Multimodal Large Language Models for Temporal Video Grounding via On-Policy Distillation
Jiaze Li, Hao Yin, Haoran Xu +6
Reinforcement learning has emerged as a principled post-training paradigm for Temporal Video Grounding (TVG) due to its on-policy optimization, yet existing GRPO-based methods rema…
Federated Joint Learning for Domain and Class Generalization
Haoran Xu, Jiaze Li, Jianzhong Ju +1
Efficient fine-tuning of visual-language models like CLIP has become crucial due to their large-scale parameter size and extensive pretraining requirements. Existing methods typica…
Vision Also You Need: Navigating Out-of-Distribution Detection with Multimodal Large Language Model
Haoran Xu, Yanlin Liu, Zizhao Tong +8
Out-of-Distribution (OOD) detection is a critical task that has garnered significant attention. The emergence of CLIP has spurred extensive research into zero-shot OOD detection, o…