Author

Dongyoung Kim

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#artificial intelligence Preprint Feb 2026

RoboCurate: Harnessing Diversity with Action-Verified Synthetic Data for Robot Learning

RoboCurate is introduced, a novel framework for action-verified synthetic robot data that addresses inconsistencies between generated videos and annotated actions and further expands the scene diversity of synthetic data beyond the available dataset through off-the-shelf generative models with structured editing axes.

Seungku Kim, Suhyeok Jang, Byungjun Yoon et al. · 0 citations

#artificial intelligence Jun 2025

Training-free LLM Verification via Recycling Few-shot Examples

This work proposes a novel framework that Recycles Few-shot examples to verify LLM outputs (ReFeri), which combines a forward confidence score with a backward reconstruction penalty to select candidates that follow few-shot guidance while avoiding demonstration-specific overfitting.

Dongseo Lee, Jimyung Hong, Dongyoung Kim et al. · arXiv.org · 6 citations