Author

Lin-Qing Zhong

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Preprint Sep 2026

GE-Act 2.0: Pretraining and Scaling a World-Action Model for Robotic Manipulation

Genie Envisioner Act 2.0 (GE-Act 2.0) is introduced, a world-action model whose trainable generative and action components are all initialized from scratch on manipulation data, and its components are jointly trained with knowledge-aligned selective optimization (KASO), which reduces mismatched supervision.

AgiBot Research Team, Ren-Hang Liu, Wen-Zhi Zhao et al. · 4 citations · ⚡1

Preprint Jul 2026

EVA-Client: A Unified Data Collection, Inference, and Deployment Framework for Embodied Policies on Real Robots

EVA-Client unifies the real-robot stages of the policy iteration loop within a single codebase, and consolidates major real-time inference strategies, synchronous and asynchronous execution, ACT-style temporal ensembling, Real-Time Chunking, and a naive-async ablation baseline, behind a single configuration surface.

He Yang, Yang Yi, Liyao Wang et al. · 0 citations