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20242026
most citedDROID: A Large-Scale In-The-Wild Robot Manipulation Dataset

3 citations · 7 across the 7 of their papers we have counts for

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cs.RO2026

Rho: A Foundation for Efficiently Adaptable VLA Models

Rho Team, Simran Bagaria, Daphne Chen +11

General-purpose physical AI models must combine broad visual and linguistic capabilities with precise control across robot embodiments and efficient adaptation to downstream tasks.…

cs.RO2026

A Few Words Go a Long Way: Language Guided Robot Policy Synthesis

Daphne Chen, Archit Ritesh Jain, Eric Goossen +4

While vision-language-action models have demonstrated impressive zero-shot manipulation capabilities, they remain fundamentally black box policies that are difficult to interpret,…

cs.RO2026

FlowDAgger: Human-in-the-Loop Adaptation of Generative Robot Policies in Latent Space

Michael Murray, Daphne Chen, Simran Bagaria +7

Pretrained generative robot policies based on flow matching and diffusion have achieved impressive results across a wide range of manipulation tasks. Yet real-world deployments rou…

cs.RO2025

Towards Embodiment Scaling Laws in Robot Locomotion

Bo Ai, Liu Dai, Nico Bohlinger +7

Cross-embodiment generalization underpins the vision of building generalist embodied agents for any robot, yet its enabling factors remain poorly understood. We investigate embodim…

cs.RO2024★ 3 cited

DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset

Alexander Khazatsky, Karl Pertsch, Suraj Nair +98

The creation of large, diverse, high-quality robot manipulation datasets is an important stepping stone on the path toward more capable and robust robotic manipulation policies. Ho…