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arXivSim-to-real

Skill2Real: Agentic Skill Learning for Zero-Shot Sim-to-Real Robot Manipulation

Skill2Real learns simulation skills via a shared robot API with a Proposer-Verifier-Governor loop, transferring frozen skill hierarchies to real robots without fine-tuning to reach 78.75% real-world manipulation success.

Xincheng He, Siyu Ma, Chang Yu, Yunuo Chen and 4 more

Published Oct 2, 2026 · 0 citations · ▲ 16 on Hugging Face

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AI panel: 13 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 1/5
67%Highly rated
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NeurIPS 2026PekingInstitute of automation, ChineseU the Chinese Academy of ScienceLightwheel AIU California, BerkeleySim-to-real

WorldComposer: Generative High-Fidelity Simulation with Digital Cousins for Generalizable Robot Learning and Evaluation

Jasper Lu, Zhenhao Shen, Yuanfei Wang, Shugao Liu and 7 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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lenient 2/5
medium 0/10
strict 0/5
67%Highly rated
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NeurIPS 2026Qualcomm AI ResearchGhentQualcomm Technologies Inc.U AmsterdamSim-to-real

Efficient Test-Time Adaptation For Robot Policies

Motasem Alfarra, Pietro Mazzaglia, Markus Peschl, Daniel Dijkman and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 2 of 20 reviewers recommend it
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medium 0/10
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67%Highly rated
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NeurIPS 2026TsinghuaTsinghua University, TsinghuaIIIS, TsinghuaShanghai Qi Zhi InstituteSim-to-real

DexMirror: Real-to-Sim Scene Mirroring for Sim-to-Real Dexterous Manipulation

Pu Hua, Zhecheng Yuan, Meng Chu, Peiqi Duan and 1 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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lenient 2/5
medium 0/10
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45%Niche pick
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NeurIPS 2026U OxfordMeta and University of OxfordSim-to-real

PhysFormer: Learning to Simulate Mechanics in World Space

Yiming Chen, Yushi LAN, Andrea Vedaldi

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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57%Worth a look
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NeurIPS 2026Micro-IntelligenceInstitute of Computing TechnologLanzhouU science and technology of ChinSim-to-real

Bridging Simulation and Reality: Geometry and Decision Alignment for Autonomous Driving

Dapeng Zhang, Zhenlong Yuan, Chenyang Li, Hongtao Nie and 4 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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45%Niche pick
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NeurIPS 2026George MasonAVA LabsOverLabSim-to-real

CLAMP: A Sim-to-Real Benchmark for Closed-Loop Kinematic Pose Estimation and Assembly Reasoning

Kevin Murray, Randolph B Robert, Petar Z Duric, Zoran Duric

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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71%Highly rated
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NeurIPS 2026The Chinese University of Hong KDexForce Co. Ltd., ShenzhenSouth China University of TechnoSim-to-real

Embracing Evolution: A Call for Body-Control Co-Design in Embodied Humanoid Robot

Humanoid robot co-design evolves control and morphology together via strategic exploration and meta-policy learning to enable true embodied intelligence.

Guiliang Liu, Bo Yue, Yi J Kim, Kui Jia

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 7 of 20 reviewers recommend it
lenient 5/5
medium 2/10
strict 0/5
76%Highly rated
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NeurIPS 2026OralU Massachusetts at AmherstShanghaiTechUMassGoogle Deepmind / HarvardIBMSim-to-real

SyncWorld: Visual Calibration Enables World Models as Zero-Shot Simulators

SyncWorld learns action-visual mappings via visual calibration episodes to serve as zero-shot simulators across unseen robot settings without retraining.

Yuncong Yang, Zhengtao Han, Furkan Ozyurt, Zeyuan Yang and 5 more

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026 · ▲ 16 on Hugging Face · Code ★ 21

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AI panel: 10 of 20 reviewers recommend it
lenient 5/5
medium 5/10
strict 0/5
74%Highly rated
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NeurIPS 2026Technische Universität DarmstadtChaser RoboticsKarlsruhe Institute of TechnologTechnische Universität DarmstadtTU Darmstadt, MITSim-to-real

Nautilus: From One Prompt to Plug-and-Play Robot Learning

NAUTILUS converts a single prompt into robot learning workflows via plug-and-play agent skills, typed contracts, and automated validation, reducing cross-family engineering overhead.

Yufeng Jin, Jianfei Guo, Xiaogang Jia, Yu Deng and 7 more

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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9/20 AI panelreviewers recommend it

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AI panel: 9 of 20 reviewers recommend it
lenient 5/5
medium 4/10
strict 0/5