collaborators

10 papers

cs.CV2026

X-Foresight: A Joint Vision-Action Causal Forecasting Network via Predictive World Modeling

Baolu Li, Jingyu Qian, Rui Guo +17

Physical world knowledge resides mainly in videos. Equipping Vision-Language-Action (VLA) models with such knowledge is fundamental for safe and generalizable planning. Predictive…

cs.CV2026

X-Mind: Efficient Visual Chain-of-Thought via Predictive World Model for End-to-End Driving

Bohao Zhao, Chengrui Wei, Guangfeng Jiang +17

Predicting future states is essential for autonomous agents, yet current Vision-Language-Action (VLA) models fundamentally lack this capability, relying instead on reactive percept…

cs.LG2026

MATT-CTR: Unleashing a Model-Agnostic Test-Time Paradigm for CTR Prediction with Confidence-Guided Inference Paths

Moyu Zhang, Yun Chen, Yujun Jin +3

Recently, a growing body of research has focused on either optimizing CTR model architectures to better model feature interactions or refining training objectives to aid parameter…

cs.CV2026

Test-Time Self-Adaptive Conditioning for Stable Audio-Driven Talking-Head Generation

Zhicheng Zhang, Lei Wang, Yu Zhang +1

Audio-driven talking-head generation has achieved remarkable progress with recent models such as AniTalker, FLOAT, and Sonic. Despite their success, most existing approaches rely o…

cs.LG2026

Selective Test-Time Compute Scaling for Click-Through Rate Prediction via Uncertainty-Triggered Feature Path Exploration

Moyu Zhang, Yun Chen, Yujun Jin +3

Scaling test-time compute has proven highly effective for language models, yet this opportunity remains largely unexplored for industrial Click-Through Rate (CTR) prediction. CTR m…

cs.IR2026

Self-Balancing Gradient Allocation for Heterogeneity-Aware Feature Generation in Click-Through Rate Prediction

Moyu Zhang, Yun Chen, Yujun Jin +3

Generative pre-training via discrete diffusion provides dense reconstruction supervision across all feature fields simultaneously, mitigating representation collapse from data spar…