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From the 1 of 14 linked papers with an AI index.

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14 papers

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

Vinci2: Providing Proactive Assistance in Continuous Egocentric Videos

Gong Sitong, Tianyu Yan, Caixin Kang +6

The paper introduces Vinci2, a proactive on‑device assistant for continuous egocentric video that decides when to intervene by using memory‑augmented reasoning, and presents EgoSer…

cs.CV2026

CaST-Bench: Benchmarking Causal Chain-Grounded Spatio-Temporal Reasoning for Video Question Answering

Mingfang Zhang, Jingjing Pan, Ashutosh Kumar +7

Cause-and-effect reasoning in video is a significant challenge for Vision-Language Models (VLMs), as it requires going beyond surface-level perception to a deeper understanding of…

cs.CV2026

HanDyVQA: A Video QA Benchmark for Fine-Grained Hand-Object Interaction Dynamics

Masatoshi Tateno, Gido Kato, Hirokatsu Kataoka +2

Hand-object interaction (HOI) inherently involves dynamics where human manipulations produce distinct spatio-temporal effects on objects. However, existing semantic HOI benchmarks…

cs.CV2026

The N-Body Problem: Parallel Execution from Single-Person Egocentric Video

Zhifan Zhu, Yifei Huang, Yoichi Sato +1

Humans can intuitively parallelise complex activities, but can a model predict this from observing a single person? Given one egocentric video, we introduce the N-Body Problem: pre…

cs.AI2026

Perception or Prejudice: Can MLLMs Go Beyond First Impressions of Personality?

Caixin Kang, Tianyu Yan, Sitong Gong +8

Multimodal Large Language Models (MLLMs) are increasingly deployed in human-facing roles where personality perception is critical, yet existing benchmarks evaluate this capability…