most citedGrounding Computer Use Agents on Human Demonstrations

1 citations · 1 across the 13 of their papers we have counts for

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cs.AI2026

Dual Exam: Controlled Evaluation of Multimodal Agents and World Models

Zhefan Rao, Meng Chu, Xuan Zhang +80

World Models (WMs) can support Multimodal Agents (MAs) through simulated experience, while Agent trajectories can inform World Model refinement. Evaluating this interaction require…

cs.AI2026

A Survey on Foundations and Frontiers of Multimodal Agentic Frameworks: Techniques and Applications

Neel Mokaria, Rishie Raj, Dheeraj Baiju +13

Advances in large language models (LLMs) have fueled a wave of research into agency: the ability to reason, plan, and act. This effort has produced agentic frameworks that orchestr…

cs.AI2026

SceneCode: Executable World Programs for Editable Indoor Scenes with Articulated Objects

Puyi Wang, Yuhao Wang, Linjie Li +4

Indoor scene synthesis underpins embodied AI, robotic manipulation, and simulation-based policy evaluation, where a useful scene must specify not only what the environment looks li…

cs.AI2026

AI for Auto-Research: Roadmap & User Guide

Lingdong Kong, Xian Sun, Wei Chow +17

AI-assisted research is crossing a threshold: fully automated systems can now generate research papers for as little as $15, while long-horizon agents can execute experiments, draf…

cs.AI2026

Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond

Meng Chu, Xuan Billy Zhang, Kevin Qinghong Lin +47

As AI systems move from generating text to accomplishing goals through sustained interaction, the ability to model environment dynamics becomes a central bottleneck. Agents that ma…