collaborators

7 papers

cs.RO2026

Semantic Evidence Regulation via Relational Bias for Zero-Shot Object Navigation

Weitao An, Chenghao Xu, Xu Yang +1

Object navigation requires an embodied agent to locate a target object in an unknown environment through visual observations. Existing zero-shot methods typically leverage open-voc…

cs.CV2026

Hierarchical Dual-Subspace Decoupling for Continual Learning in Vision-Language Models

Mengxin Qin, Xiang Zhang, Kun Wei +2

Class-incremental learning aims to continuously acquire new knowledge while preserving previously learned information, thereby mitigating catastrophic forgetting. Existing methods…

cs.CV2026

DIMoE-Adapters: Dynamic Expert Evolution for Continual Learning in Vision-Language Models

Mengxin Qin, Xiang Zhang, Xi Wang +3

Continual learning enables vision-language models to accumulate knowledge and adapt to evolving tasks without retraining from scratch. However, in multi-domain task-incremental lea…

cs.CV2026

Perceive, Verify and Understand Long Video: Multi-Granular Perception and Active Verification via Interactive Agents

Jiahua Li, Zhanhe Zhang, Chenghao Xu +4

Long videos, characterized by temporal complexity and sparse task-relevant information, pose significant reasoning challenges for AI systems. Although existing Large Language Model…

cs.AI2026

Compensating Visual Insufficiency with Stratified Language Guidance for Long-Tail Class Incremental Learning

Xi Wang, Xu Yang, Donghao Sun +1

Long-tail class incremental learning (LT CIL) remains highly challenging because the scarcity of samples in tail classes not only hampers their learning but also exacerbates catast…

cs.LG2026

Rotation Control Unlearning: Quantifying and Controlling Continuous Unlearning for LLM with The Cognitive Rotation Space

Xiang Zhang, Kun Wei, Xu Yang +3

As Large Language Models (LLMs) become increasingly prevalent, their security vulnerabilities have already drawn attention. Machine unlearning is introduced to seek to mitigate the…