1 citations · 1 across the 11 of their papers we have counts for
13 papers
Information-Theoretic Decoupled Prompt Tuning for Continual Learning
Yunfei Zhang, Wen Wen, Tieliang Gong +1
Continual learning (CL) aims to incrementally acquire knowledge from sequential data while avoiding catastrophic forgetting. Recently, prompt tuning has attracted increasing attent…
Sustaining Plasticity via Learnable Wavelet Activations in Continual Learning
Zeyang Zhang, Tieliang Gong, Junyan Lu +1
Plasticity loss has emerged as a critical challenge in continual learning that significantly hinders the acquisition of sequential tasks. While optimizing activation designs offers…
Mitigating Entangled Steering in Large Vision-Language Models for Hallucination Reduction
Yuanhong Zhang, Zhaoyang Wang, Xin Zhang +2
Large Vision-Language Models (LVLMs) have achieved remarkable success across cross-modal tasks but remain hindered by hallucinations, producing textual outputs inconsistent with vi…
MotionWeaver: Holistic 4D-Anchored Framework for Multi-Humanoid Image Animation
Xirui Hu, Yanbo Ding, Jiahao Wang +4
Character image animation, which synthesizes videos of reference characters driven by pose sequences, has advanced rapidly but remains largely limited to single-human settings. Exi…
Information-Theoretic Generalization Bounds of Replay-based Continual Learning
Wen Wen, Tieliang Gong, Zeyu Gao +3
Continual learning (CL) has emerged as a dominant paradigm for acquiring knowledge from sequential tasks while avoiding catastrophic forgetting. Although many CL methods have been…
EchoShot: Multi-Shot Portrait Video Generation
Jiahao Wang, Hualian Sheng, Sijia Cai +5
Video diffusion models substantially boost the productivity of artistic workflows with high-quality portrait video generative capacity. However, prevailing pipelines are primarily…
InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective
Yuanhong Zhang, Muyao Yuan, Weizhan Zhang +4
The Segment Anything Model (SAM), a vision foundation model, exhibits impressive zero-shot capabilities in general tasks but struggles in specialized domains. Parameter-efficient f…
DynamicID: Zero-Shot Multi-ID Image Personalization with Flexible Facial Editability
Xirui Hu, Jiahao Wang, Hao Chen +4
Recent advances in text-to-image generation have driven interest in generating personalized human images that depict specific identities from reference images. Although existing me…
Towards the Generalization of Multi-view Learning: An Information-theoretical Analysis
Wen Wen, Tieliang Gong, Yuxin Dong +2
Multiview learning has drawn widespread attention for its efficacy in leveraging cross-view consensus and complementarity information to achieve a comprehensive representation of d…
SpotActor: Training-Free Layout-Controlled Consistent Image Generation
Jiahao Wang, Caixia Yan, Weizhan Zhang +6
Text-to-image diffusion models significantly enhance the efficiency of artistic creation with high-fidelity image generation. However, in typical application scenarios like comic b…
Accelerating Non-Maximum Suppression: A Graph Theory Perspective
King-Siong Si, Lu Sun, Weizhan Zhang +4
Non-maximum suppression (NMS) is an indispensable post-processing step in object detection. With the continuous optimization of network models, NMS has become the ``last mile'' to…
How Does Distribution Matching Help Domain Generalization: An Information-theoretic Analysis
Yuxin Dong, Tieliang Gong, Hong Chen +3
Domain generalization aims to learn invariance across multiple training domains, thereby enhancing generalization against out-of-distribution data. While gradient or representation…
OneActor: Consistent Character Generation via Cluster-Conditioned Guidance
Jiahao Wang, Caixia Yan, Haonan Lin +5
Text-to-image diffusion models benefit artists with high-quality image generation. Yet their stochastic nature hinders artists from creating consistent images of the same subject.…