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cs.CV2026

HelloWorld: Enabling Socially Interactive Characters in Video World Models

Liangyang Ouyang, Ruicong Liu, Xuangeng Chu +2

Despite the remarkable recent progress of video world models, social interaction between users and the characters within these worlds remains unsupported. To fill this gap, we pres…

cs.CV2026

SFHand: Learning Embodied Manipulation by Streaming Egocentric 3D Hand Forecasting

Ruicong Liu, Yifei Huang, Liangyang Ouyang +2

Real-time 3D hand forecasting is a critical component for fluid human-computer interaction in applications like AR and assistive robotics. However, existing methods are ill-suited…

cs.CV2026

SocialDirector: Training-Free Social Interaction Control for Multi-Person Video Generation

Liangyang Ouyang, Ruicong Liu, Caixin Kang +2

Video generation has advanced rapidly, producing photorealistic videos from text or image prompts. Meanwhile, film production and social robotics increasingly demand multi-person v…

cs.CV2025

Multi-speaker Attention Alignment for Multimodal Social Interaction

Liangyang Ouyang, Yifei Huang, Mingfang Zhang +3

Understanding social interaction in video requires reasoning over a dynamic interplay of verbal and non-verbal cues: who is speaking, to whom, and with what gaze or gestures. While…

cs.CV2025

Can MLLMs Read the Room? A Multimodal Benchmark for Assessing Deception in Multi-Party Social Interactions

Caixin Kang, Yifei Huang, Liangyang Ouyang +3

Despite their advanced reasoning capabilities, state-of-the-art Multimodal Large Language Models (MLLMs) demonstrably lack a core component of human intelligence: the ability to `r…

cs.CV2025

Can MLLMs Read the Room? A Multimodal Benchmark for Verifying Truthfulness in Multi-Party Social Interactions

Caixin Kang, Yifei Huang, Liangyang Ouyang +2

As AI systems become increasingly integrated into human lives, endowing them with robust social intelligence has emerged as a critical frontier. A key aspect of this intelligence i…