output
20102026
most citedLINE: Large-scale Information Network Embedding

4.8k citations

331 papers

cs.CV2026

Human-Level Accuracy, Non-Human Strategies: Revealing Model-Human Divergence in Video Physical Reasoning

Fanhong Li, Shurui Zheng, Zi Yin +3

Video foundation models now reach human-level accuracy on physical-reasoning benchmarks, yet such tasks require predicting unobserved physical outcomes. Do these models perform hum…

cs.HC2026★ 1 cited

Toward Natural and Companionable Virtual Agents via Cross-Temporal Emotional Modeling

Feier Qin, Xiao Li, Yi Zheng +5

Recent advances in foundation models have enabled conversational agents that aim for sustained companionship rather than mere task completion. Yet most still remain unable to suppo…

cs.CV2026

CasLayout: Cascaded 3D Layout Diffusion for Indoor Scene Synthesis with Implicit Relation Modeling

Yingrui Wu, Youkang Kong, Mingyang Zhao +3

Synthesizing realistic 3D indoor scenes remains challenging due to data scarcity and the difficulty of simultaneously enforcing global architectural constraints and local semantic…

cs.GR2026

SQuadGen: Generating Simple Quad Layouts via Chart Distance Fields

Youkang Kong, Yang Liu, Yue Dong +2

3D shapes from scanning, reconstruction, or AI-generated content often lack simple quad mesh layouts -- critical for efficient editing and modeling. Existing quad-remeshing techniq…

cs.AI2026

CSPO: Alleviating Reward Ambiguity for Structured Table-to-LaTeX Generation

Yunfan Yang, Cuiling Lan, Jitao Sang +1

Tables contain rich structured information, yet when stored as images their contents remain "locked" within pixels. Converting table images into LaTeX code enables faithful digitiz…

cs.HC2026

From Passive Consumption to Active Interaction: Exploring Interactive LLM Scaffolding to Support Learning Engagement

Zixin Chen, Haotian Li, Zhe Liu +2

Large Language Models (LLMs) are increasingly used as learning companions, providing scaffolded explanations, hints, or step-by-step guidance. However, in current LLM-based learnin…