collaborators

5 papers

cs.LG2026

How to Achieve Prototypical Birth and Death for OOD Detection?

Ningkang Peng, Qianfeng Yu, Xiaoqian Peng +7

Out-of-Distribution (OOD) detection is crucial for the secure deployment of machine learning models, and prototype-based learning methods are among the mainstream strategies for ac…

cs.AI2026

Seeing through the Conflict: Transparent Knowledge Conflict Handling in Retrieval-Augmented Generation

Hua Ye, Siyuan Chen, Ziqi Zhong +4

Large language models (LLMs) equipped with retrieval--the Retrieval-Augmented Generation (RAG) paradigm--should combine their parametric knowledge with external evidence, yet in pr…

cs.CV2025

Affordance-First Decomposition for Continual Learning in Video-Language Understanding

Mengzhu Xu, Hanzhi Liu, Ningkang Peng +2

Continual learning for video--language understanding is increasingly important as models face non-stationary data, domains, and query styles, yet prevailing solutions blur what sho…

cs.CV2025

Where Culture Fades: Revealing the Cultural Gap in Text-to-Image Generation

Chuancheng Shi, Shangze Li, Shiming Guo +9

Multilingual text-to-image (T2I) models have advanced rapidly in terms of visual realism and semantic alignment, and are now widely utilized. Yet outputs vary across cultural conte…

cs.CV2025

C3-OWD: A Curriculum Cross-modal Contrastive Learning Framework for Open-World Detection

Siheng Wang, Zhengdao Li, Yanshu Li +12

Object detection has advanced significantly in the closed-set setting, but real-world deployment remains limited by two challenges: poor generalization to unseen categories and ins…