activity
20192026
most citedFrom exploration to control: learning object manipulation skills through novelty search and local adaptation

32 citations · 32 across the 4 of their papers we have counts for

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2 papers · 1 filter

cs.RO2026

ProgVLA: Progress-Aware Robot Manipulation Skill Learning

Seungsu Kim, Jinyoung Choi, Seungmin Baek +1

We present ProgVLA, a compact vision-language-action (VLA) model designed for reliable robot manipulation under tight compute and memory budgets. The model specifically focuses on…

cs.LG2026

Behavioral Mode Discovery for Fine-tuning Multimodal Generative Policies

Alberta Longhini, David Emukpere, Jean-Michel Renders +1

We address the problem of fine-tuning pre-trained generative policies with reinforcement learning (RL) while preserving the multimodality of their action distributions. Existing me…