3 papers
cs.AI2026
vla-eval: A Unified Evaluation Harness for Vision-Language-Action Models
Suhwan Choi, Yunsung Lee, Yubeen Park +4
Vision-Language-Action (VLA) models are increasingly evaluated across multiple simulation benchmarks, yet adding each benchmark to an evaluation pipeline requires resolving incompa…
cs.LG2026
Random Is Hard to Beat: Active Selection in online DPO with Modern LLMs
Giyeong Oh, Junghyun Lee, Jaehyun Park +3
Modern LLMs inherit strong priors from web-scale pretraining, which can limit the headroom of post-training data-selection strategies. While Active Preference Learning (APL) seeks…
cs.AI2025
D2E: Scaling Vision-Action Pretraining on Desktop Data for Transfer to Embodied AI
Suhwan Choi, Jaeyoon Jung, Haebin Seong +7
Large language models leverage internet-scale text data, yet embodied AI remains constrained by the prohibitive costs of physical trajectory collection. Desktop environments -- par…