Mohit Shridhar

DeepMind research scientist known for ALFWorld, ALFRED, AI2-THOR-based agent benchmarks, and robotic foundation models.

Role: researcher
Currently at: Google DeepMind
Twitter: twitter.com/MohitShridhar
GitHub: github.com/MohitShridhar
Scholar: scholar.google.com/citations
Papers: 4

Cite

Notes

Only stored in your browser.

Attribution

Affiliations & profile: scholar.google.com/citations

Attribution policy →

4papers·1tool contribs

Authored papers

Generative Image as Action Models

arXiv 2024

2024

GenSim: Generating Robotic Simulation Tasks via Large Language Models

arXiv 2023

2023

ALFWorld: Aligning Text and Embodied Environments for Interactive Learning

ICLR

2021

ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks

alfred-a-benchmark-for-interpreting-grounded-1

2019

Tool contributions

ALFWorld

MIT CSAIL

Aligned text-and-3D embodied environment - agents learn household tasks (pick & place, heat, cool, clean) as both TextWorld games and visually-rendered ALFRED scenes.

RL EnvPlanningEmbodiedInstruction FollowingAgentic

Affiliations

Currently at

Google DeepMind

researcher · frontier lab

Previously

Allen Institute for AI (Ai2)non profit University of Washingtonuniversity lab

Frequent co-authors

from 4 papers

Yonatan Bisk

professor

2 shared papers

Adam Trischler

researcher

Bailin Wang

Chen Bao

Daniel Gordon

Dieter Fox

Huazhe Xu

Jesse Thomason

Lirui Wang

Luke Zettlemoyer

professor

1 shared paper