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Sergey Levine

16 papers hereh-index 141.4k citations18 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author7
  • last author9

Across the 16 of 16 papers where every author was matched, so the position is known.

fields
  • cs.RO13
  • cs.LG2
  • cs.CL1
same name
  • Sergey Levine — 48 papers, h 32
  • Sergey Levine — 21 papers, h 12
  • Sergey Levine — 13 papers, h 10
  • Sergey Levine — 12 papers, h 7
  • Sergey Levine — 11 papers, h 11
  • Sergey Levine — 10 papers, h 7

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232026
most citedNavigation with Large Language Models: Semantic Guesswork as a Heuristic for Planning

14 citations · 52 across the 14 of their papers we have counts for

collaborators
Showing 2025Show all

4 papers · 1 filter

cs.RO2025

Training-Time Action Conditioning for Efficient Real-Time Chunking

Kevin Black, Allen Z. Ren, Michael Equi +1

Real-time chunking (RTC) enables vision-language-action models (VLAs) to generate smooth, reactive robot trajectories by asynchronously predicting action chunks and conditioning on…

cs.LG2025

π0.6∗​: a VLA That Learns From Experience

Physical Intelligence, Ali Amin, Raichelle Aniceto +53

We study how vision-language-action (VLA) models can improve through real-world deployments via reinforcement learning (RL). We present a general-purpose method, RL with Experience…

cs.RO2025

OmniVLA: An Omni-Modal Vision-Language-Action Model for Robot Navigation

Noriaki Hirose, Catherine Glossop, Dhruv Shah +1

Humans can flexibly interpret and compose different goal specifications, such as language instructions, spatial coordinates, or visual references, when navigating to a destination.…

cs.RO2025

CAST: Counterfactual Labels Improve Instruction Following in Vision-Language-Action Models

Catherine Glossop, William Chen, Arjun Bhorkar +2

Generalist robots should be able to understand and follow user instructions. Despite providing a powerful architecture for mapping open-vocabulary language instructions to robot ac…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.