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20242026
most citedReinforcement Learning from Reflective Feedback (RLRF): Aligning and Improving LLMs via Fine-Grained Self-Reflection

1 citations · 2 across the 5 of their papers we have counts for

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cs.RO2026

Adapting Vision-Language-Action Models to Unknown Visual Disruptions During Execution

Ahin Lee, Jinwoo Seo, Youngsoo Jang +1

Visual disruptions can arise while a robot is executing a task, leaving a vision-language-action (VLA) policy to respond without knowing the disruption type or timing. We introduce…

cs.RO2025

SpeedAug: Policy Acceleration via Tempo-Enriched Policy and RL Fine-Tuning

Taewook Nam, Junmo Cho, Youngsoo Jang +1

Robotic policy learning for complex real-world manipulation tasks has seen rapid recent progress, enabled in large part by the ability to collect demonstrations through human opera…