Progress Reward Modeling for Robotic Learning: A Comprehensive Survey Paper • 2607.21655 • Published 11 days ago • 192
KnowAct-GUIClaw: Know Deeply, Act Perfectly, Personal GUI Assistant with Self-Evolving Memory and Skill Paper • 2607.12625 • Published 18 days ago • 80
ABot-World-0: Infinite Interactive World Rollout on a Single Desktop GPU Paper • 2607.19191 • Published 11 days ago • 306
RynnBrain 1.1: Towards More Capable and Generalizable Embodied Foundation Model Paper • 2607.17977 • Published 13 days ago • 198
X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Paper • 2607.12993 • Published 19 days ago • 131
Harness Handbook: Making Evolving Agent Harnesses Readable,Navigable, and Editable Paper • 2607.13285 • Published 19 days ago • 231
RynnWorld-Teleop: An Action-Conditioned World Model for Digital Teleoperation Paper • 2607.06558 • Published 26 days ago • 79
The Mirage of Optimizing Training Policies: Monotonic Inference Policies as the Real Objective for LLM Reinforcement Learning Paper • 2606.29526 • Published Jun 28 • 170
Graph-Native Reinforcement Learning Enables Traceable Scientific Hypothesis Generation through Conceptual Recombination Paper • 2607.00924 • Published Jul 1 • 11
MemSlides: A Hierarchical Memory Driven Agent Framework for Personalized Slide Generation with Multi-turn Local Revision Paper • 2606.17162 • Published Jun 15 • 177
On the Scaling of PEFT: Towards Million Personal Models of Trillion Parameters Paper • 2606.02437 • Published Jun 1 • 241
Learn from Weaknesses: Automated Domain Specialization for Small Computer-Use Agents Paper • 2605.28775 • Published May 27 • 38