Scholar
Patrick Yin
Google Scholar ID: AMVmM84AAAAJ
University of Washington
artificial intelligence
machine learning
robotics
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Citations & Impact
All-time
Citations
1,196
H-index
7
i10-index
7
Publications
8
Co-authors
0
Contact
Email
patyin@cs.washington.edu
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Publications
5 items
Emergent Dexterity via Diverse Resets and Large-Scale Reinforcement Learning
2026
Cited
0
Simulation Distillation: Pretraining World Models in Simulation for Rapid Real-World Adaptation
2026
Cited
0
Rapidly Adapting Policies to the Real World via Simulation-Guided Fine-Tuning
2025
Cited
0
DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset
Robotics: Science and Systems · 2024
Cited
151
Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data
International Conference on Learning Representations · 2023
Cited
4
Resume (English only)
Academic Achievements
ICLR 2025: Proposed Simulation-Guided Fine-Tuning (SGFT), a sim2real framework for accelerating real-world RL (first author, equal contribution)
RSS 2024: Contributed to DROID, a large-scale in-the-wild robot manipulation dataset with 76k trajectories
ICLR 2024 Oral: Developed ASID, a system that refines simulation models using minimal real-world data for sim-to-real transfer
ICLR 2024 Spotlight: Investigated architectural choices to stabilize contrastive RL for robotic goal reaching
ICRA 2024 Best Paper: Contributed to Open X-Embodiment, an open-source dataset with 1M+ real robot trajectories across 22 robot embodiments
CoRL 2022 Oral: Proposed FLAP, a framework leveraging diverse offline data for rapid fine-tuning to new visuomotor tasks
IROS 2022: Introduced Planning to Practice (PTP) for efficient online fine-tuning of long-horizon goal-conditioned policies (equal contribution)
ICML 2022: Contributed to work on bisimulation-based state abstraction for goal-conditioned reinforcement learning
Co-authors
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Co-authors: 0 (list not available)
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