Sotabase

Career

· PhD Student, Stanford University2024–
· MS in Computer Science, Georgia Institute of Technology2021–2023
· B.Tech. in Computer Science & Engineering, Indian Institute of Technology Bombay2016–2020

Publications (17)

OpenEQA: Embodied Question Answering in the Era of Foundation Models
Computer Vision and Pattern Recognition · 2024
230
cited
HomeRobot: Open-Vocabulary Mobile Manipulation
Conference on Robot Learning · 2023
120
cited
GOAT: GO to Any Thing
Robotics: Science and Systems · 2023
116
cited
Housekeep: Tidying Virtual Households using Commonsense Reasoning
European Conference on Computer Vision · 2022
85
cited
GOAT-Bench: A Benchmark for Multi-Modal Lifelong Navigation
Computer Vision and Pattern Recognition · 2024
68
cited
LANCE: Stress-testing Visual Models by Generating Language-guided Counterfactual Images
Neural Information Processing Systems · 2023
52
cited
FACTS: First Amplify Correlations and Then Slice to Discover Bias
IEEE International Conference on Computer Vision · 2023
32
cited
Adapting Self-Supervised Vision Transformers by Probing Attention-Conditioned Masking Consistency
Neural Information Processing Systems · 2022
16
cited
Towards Open-World Mobile Manipulation in Homes: Lessons from the Neurips 2023 HomeRobot Open Vocabulary Mobile Manipulation Challenge
arXiv.org · 2024
9
cited
Learning Image Inpainting from Incomplete Images using Self-Supervision
International Conference on Pattern Recognition · 2021
6
cited
From Thousands to Billions: 3D Visual Language Grounding via Render-Supervised Distillation from 2D VLMs
International Conference on Machine Learning · 2025
5
cited
FaaSter: Accelerated Functions-as-a-Service with Heterogeneous GPUs
International Conference on High Performance Computing · 2021
4
cited
Semi-Supervised Deep Expectation-Maximization for Low-Dose Pet-Ct
IEEE International Symposium on Biomedical Imaging · 2022
4
cited
HomeRobot: An Open Source Software Stack for Mobile Manipulation Research
Proceedings of the AAAI Symposium Series · 2024
1
cited
Supplemental Material for Adapting Self-Supervised Vision Transformers by Probing Attention-Conditioned Masking Consistency
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