collaborators

7 papers

cs.CV2026

MotionCraft: Latent World Modeling with Sparse Attention for Visual Upscaling

Rong Fu, Chunlei Meng, Yangchen Zeng +9

Video super-resolution (VSR) aims to recover high-fidelity high-resolution videos from low-resolution inputs and is central to applications ranging from mobile capture to streaming…

cs.LG2026

DynImmune-BERT: Dynamic Immune Repertoire Modeling with Neural ODE Driven Continuous Transformers

Rong Fu, Yongtai Liu, Xiaowen Ma +5

Longitudinal T cell receptor repertoires contain signals of clonal expansion, contraction, disappearance, and reappearance after immune perturbation. Static repertoire language mod…

cs.LG2026

AdvSynGNN: Structure-Adaptive Graph Neural Nets via Adversarial Synthesis and Self-Corrective Propagation

Rong Fu, Chunlei Meng, Shuo Yin +2

Graph neural networks frequently encounter significant performance degradation when confronted with structural noise or non-homophilous topologies. To address these systemic vulner…

cs.MM2026

Emotion Collider: Dual Hyperbolic Mirror Manifolds for Sentiment Recovery via Anti Emotion Reflection

Rong Fu, Ziming Wang, Shuo Yin +3

Emotional expression underpins natural communication and effective human-computer interaction. We present Emotion Collider (EC-Net), a hyperbolic hypergraph framework for multimoda…

cs.IR2026

GaiaFlow: Semantic-Guided Diffusion Tuning for Carbon-Frugal Search

Rong Fu, Jia Yee Tan, Chunlei Meng +4

As the burgeoning power requirements of sophisticated neural architectures escalate, the information retrieval community has recognized ecological sustainability as a pivotal prior…

cs.CV2025

Codebook-Centric Deep Hashing: End-to-End Joint Learning of Semantic Hash Centers and Neural Hash Function

Shuo Yin, Zhiyuan Yin, Yuqing Hou +3

Hash center-based deep hashing methods improve upon pairwise or triplet-based approaches by assigning fixed hash centers to each class as learning targets, thereby avoiding the ine…

cs.LG2025

Meta-Learning Reinforcement Learning for Crypto-Return Prediction

Junqiao Wang, Zhaoyang Guan, Guanyu Liu +7

Predicting cryptocurrency returns is notoriously difficult: price movements are driven by a fast-shifting blend of on-chain activity, news flow, and social sentiment, while labeled…