collaborators

7 papers

cs.CV2026

Separating Angular Alignment from Radial Ordering in Hyperbolic Vision-Language Models

Mingyang Gao, Yuwei Wu, Shiyu Luo +8

Hyperbolic vision-language models are well suited to modeling the hierarchical structure of multimodal data, because hyperbolic volume grows exponentially with radius, enabling low…

cs.CV2026

Facial Expression Generation Aligned with Human Preference for Natural Dyadic Interaction

Xu Chen, Rui Gao, Xinjie Zhang +5

Achieving natural dyadic interaction requires generating facial expressions that are emotionally appropriate and socially aligned with human preference. Human feedback offers a com…

cs.RO2026

Morphology-Independent Facial Expression Imitation for Human-Face Robots

Xu Chen, Rui Gao, Che Sun +4

Accurate facial expression imitation on human-face robots is crucial for achieving natural human-robot interaction. Most existing methods have achieved photorealistic expression im…

cs.CV2026

Fine-Grained 3D Facial Reconstruction for Micro-Expressions

Che Sun, Xinjie Zhang, Rui Gao +3

Recent advances in 3D facial expression reconstruction have demonstrated remarkable performance in capturing macro-expressions, yet the reconstruction of micro-expressions remains…

cs.CV2026

Bridging Modality Disconnect in Self-Reflection via Closed-Loop Visually Grounded Verification

Haoyu Zhang, Yuwei Wu, Pengxiang Li +6

In the era of Vision-Language Models (VLMs), enhancing multimodal reasoning capabilities remains a critical challenge, particularly in handling ambiguous or complex visual inputs,…

cs.RO2025

Long-Horizon Visual Imitation Learning via Plan and Code Reflection

Quan Chen, Chenrui Shi, Qi Chen +6

Learning from long-horizon demonstrations with complex action sequences presents significant challenges for visual imitation learning, particularly in understanding temporal relati…

cs.CL2025

M3PO: Multimodal-Model-Guided Preference Optimization for Visual Instruction Following

Ruirui Gao, Emily Johnson, Bowen Tan +1

Large Vision-Language Models (LVLMs) hold immense potential for complex multimodal instruction following, yet their development is often hindered by the high cost and inconsistency…