works on

From the 1 of 18 linked papers with an AI index.

most citedOmniGAIA: Towards Native Omni-Modal AI Agents

1 citations · 1 across the 5 of their papers we have counts for

collaborators

18 papers

cs.CV2026

StreamArena: Toward Continuous, Interactive, and Long-Horizon Agentic Streaming Video Understanding

Xichen Zhang, Guankai Li, Yinghao Zhu +6

Deploying autonomous multimodal agents in continuous, real-world environments requires them to ingest unbounded audio-visual streams and maintain hour-scale memory. However, curren…

cs.AI2026

Harness-R1: Learning to Edit Executable Runtime Harnesses from Agent Failure Trajectories

Shuai Shao, Kangning Zhang, Qingyao Li +7

Agents built around large language models continually accumulate interaction trajectories during deployment, yet their behavior typically remains fixed. Beyond updating model weigh…

cs.CV2026

EgoGenesis: Egocentric World-Action Modeling with Online Anchored Projective Memory and Action-3D RoPE

Zexuan Yan, Yuzhou Wu, Yue Ma +9

The paper introduces EgoGenesis, a simulator that generates controllable egocentric manipulation videos using geometry-aware conditioning mechanisms to augment real robot data and…

cs.AI20261 cited

OmniGAIA: Towards Native Omni-Modal AI Agents

Xiaoxi Li, Wenxiang Jiao, Jiarui Jin +10

Human intelligence naturally intertwines omni-modal perception -- spanning vision, audio, and language -- with complex reasoning and tool usage to interact with the world. However,…

cs.LG2026

Uncertainty-Aware Reward Modeling for Stable RLHF

Licheng Pan, Haocheng Yang, Haoxuan Li +7

Reinforcement learning from human feedback (RLHF) aligns large language models by training reward models on preference data and optimizing policies to maximize predicted rewards. H…

cs.IR2026

AgentDisCo: Towards Disentanglement and Collaboration in Open-ended Deep Research Agents

Jiarui Jin, Zexuan Yan, Shijian Wang +2

In this paper, we present AgentDisCo, a novel Disentangled and Collaborative agentic architecture that formulates deep research as an adversarial optimization problem between infor…