activity
20232026
most citedDiffusion Models for Reinforcement Learning: A Survey

12 citations · 13 across the 14 of their papers we have counts for

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9 papers · 1 filter

cs.LG2026

Brain-Inspired Hierarchical Modularity for General Continual Learning

Hongwei Yan, Kanglei Zhou, Qi Cheng +7

Continual learning, the ability to learn from sequential experience while retaining and adapting prior knowledge, is central to intelligent systems operating in changing environmen…

cs.CV2026

CEL: Continual Ego, Exo, and Ego-Exo Learning

Hongwei Yan, Kanglei Zhou, Yuchen Liu +3

Perception for embodied agents is video-based, often multi-view (ego, exo, or both), and inherently continual, with simultaneous task and viewpoint shifts. Yet continual learning (…

cs.AI2026

MePo++: Unifying Representation Refinement and Reconciliation for General Continual Learning

Guanglong Sun, Kanglei Zhou, Liyuan Wang +6

General continual learning (GCL) aims to learn from evolving data streams without task identities, explicit boundaries, or repeated access to previous data, making it a realistic y…

cs.AI2026

ComMem: Complementary Memory Systems for Test-Time Adaptation of Vision-Language Models

Guanglong Sun, Shuang Cui, Bo Lei +6

Test-time adaptation (TTA) of vision-language models (VLMs) is essential for their robust deployment in dynamic, real-world environments. However, existing TTA methods often adapt…

cs.LG2026

FlyPrompt: Brain-Inspired Random-Expanded Routing with Temporal-Ensemble Experts for General Continual Learning

Hongwei Yan, Guanglong Sun, Kanglei Zhou +3

General continual learning (GCL) challenges intelligent systems to learn from single-pass, non-stationary data streams without clear task boundaries. While recent advances in conti…

cs.CV2026

TP-Blend: Textual-Prompt Attention Pairing for Precise Object-Style Blending in Diffusion Models

Xin Jin, Yichuan Zhong, Yapeng Tian

Current text-conditioned diffusion editors handle single object replacement well but struggle when a new object and a new style must be introduced simultaneously. We present Twin-P…

cs.CV2026

Sparse Video Generation Propels Real-World Beyond-the-View Vision-Language Navigation

Hai Zhang, Siqi Liang, Li Chen +5

Why must vision-language navigation be bound to detailed and verbose language instructions? While such details ease decision-making, they fundamentally contradict the goal for navi…

cs.AI2026

MePo: Meta Post-Refinement for Rehearsal-Free General Continual Learning

Guanglong Sun, Hongwei Yan, Liyuan Wang +5

To cope with uncertain changes of the external world, intelligent systems must continually learn from complex, evolving environments and respond in real time. This ability, collect…

cs.LG2026

Safety Alignment as Continual Learning: Mitigating the Alignment Tax via Orthogonal Gradient Projection

Guanglong Sun, Siyuan Zhang, Liyuan Wang +3

Safety post-training can improve the harmfulness and policy compliance of Large Language Models (LLMs), but it may also reduce general utility, a phenomenon often described as the…