collaborators

10 papers

cs.CL2026

SG-OPD: Sign-Gated On-Policy Distillation via Sign-Consistency Gating and Phased Teacher Sampling

Haoran Xu, Hongyu Wang, Yifei Gao +3

On-policy distillation (OPD) trains a student on its own trajectories with dense per-token supervision from a stronger teacher, and often outperforms off-policy distillation and st…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

ImagebindDC: Compressing Multi-modal Data with Imagebind-based Condensation

Yue Min, Shaobo Wang, Jiaze Li +5

Data condensation techniques aim to synthesize a compact dataset from a larger one to enable efficient model training, yet while successful in unimodal settings, they often fail in…