Chaplot, Devendra Singh

On evaluation of embodied navigation agents

Anderson, P., Chang, A., Chaplot, D. S., Dosovitskiy, A., Gupta, S., Koltun, V., Kosecka, J., Malik, J., Mottaghi, R., Savva, M., et al. (2018) · arXiv

Reinforcement Learning in RoboticsRobotic Path Planning Algorithms

Cited by 622

Mistral 7B

Jiang, A. Q., Sablayrolles, A., Mensch, A., Bamford, C., Chaplot, D. S., Casas, D. D. L., Bressand, F., Lengyel, G., Lample, G., Saulnier, L., et al. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 340

Object Goal Navigation using Goal-Oriented Semantic Exploration

Chaplot, D. S., Gandhi, D., Gupta, A., & Salakhutdinov, R. (2020) · arXiv

Reinforcement Learning in RoboticsRobotics and Sensor-Based Localization

Cited by 321

Learning to explore using active neural SLAM

Chaplot, D. S., Gandhi, D., Gupta, S., Gupta, A., & Salakhutdinov, R. (2020) · arXiv

Reinforcement Learning in RoboticsRobotics and Sensor-Based Localization

Cited by 318

PONI: Potential Functions for ObjectGoal Navigation with Interaction-free Learning

Ramakrishnan, S. K., Chaplot, D. S., Al-Halah, Z., Malik, J., & Grauman, K. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Reinforcement Learning in RoboticsRobotics and Sensor-Based Localization

Cited by 154

Habitat 2.0: Training home assistants to rearrange their habitat

Szot, A., Clegg, A., Undersander, E., Wijmans, E., Zhao, Y., Turner, J., Maestre, N., Mukadam, M., Chaplot, D., Maksymets, O., et al. (2021) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 143

Mixtral of Experts

Jiang, A. Q., Sablayrolles, A., Roux, A., Mensch, A., Savary, B., Bamford, C., Chaplot, D. S., Casas, D. D. L., Hanna, E. B., Bressand, F., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 143

Navigating to objects in the real world

Gervet, T., Chintala, S., Batra, D., Malik, J., & Chaplot, D. S. (2023) · Science Robotics

Reinforcement Learning in RoboticsRobotics and Sensor-Based Localization

Cited by 125

Habitat-Matterport 3D Semantics Dataset

Yadav, K., Ramrakhya, R., Ramakrishnan, S. K., Gervet, T., Turner, J., Gokaslan, A., Maestre, N., Chang, A. X., Batra, D., Savva, M., et al. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

3D Shape Modeling and AnalysisReinforcement Learning in Robotics

Cited by 92

Global Pose Estimation with an Attention-Based Recurrent Network

Parisotto, E., Chaplot, D. S., Zhang, J., & Salakhutdinov, R. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Robotics and Sensor-Based LocalizationReinforcement Learning in Robotics

Cited by 88

Gated-Attention Architectures for Task-Oriented Language Grounding

Chaplot, D. S., Sathyendra, K. M., Pasumarthi, R. K., Rajagopal, D., & Salakhutdinov, R. (2017) · arXiv

Multimodal Machine Learning ApplicationsReinforcement Learning in Robotics

Cited by 82

FILM: Following Instructions in Language with Modular Methods

Min, S. Y., Chaplot, D. S., Ravikumar, P., Bisk, Y., & Salakhutdinov, R. (2021) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 81

Semantic Curiosity for Active Visual Learning

Chaplot, D. S., Jiang, H., Gupta, S., & Gupta, A. (2020) · Lecture Notes in Computer Science

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 64

GOAT: GO to Any Thing

Chang, M., Gervet, T., Khanna, M., Yenamandra, S., Shah, D., Min, S., Shah, K., Paxton, C., Gupta, S., Batra, D., et al. (2024) · Robotics: Science and Systems XX

Robot Manipulation and LearningRobotics and Sensor-Based Localization

Cited by 53

GOAT-Bench: A Benchmark for Multi-Modal Lifelong Navigation

Khanna, M., Ramrakhya, R., Chhablani, G., Yenamandra, S., Gervet, T., Chang, M., Kira, Z., Chaplot, D. S., Batra, D., & Mottaghi, R. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 23

SEAL: Self-supervised embodied active learning using exploration and 3D consistency

Chaplot, D. S., Dalal, M., Gupta, S., Malik, J., & Salakhutdinov, R. (2021) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 22

Habitat 3.0: A Co-Habitat for Humans, Avatars, and Robots

Puig, X., Undersander, E., Szot, A., Cote, M. D., Yang, T.-Y., Partsey, R., Desai, R., Clegg, A. W., Hlavac, M., Min, S. Y., et al. (2023) · arXiv

Robot Manipulation and LearningSocial Robot Interaction and HRI

Cited by 15

Learning Cognitive Models Using Neural Networks

Chaplot, D. S., MacLellan, C., Salakhutdinov, R., & Koedinger, K. (2018) · Lecture Notes in Computer Science

Intelligent Tutoring Systems and Adaptive LearningOnline Learning and Analytics

Cited by 11

Pixtral 12B

Agrawal, P., Antoniak, S., Hanna, E. B., Bout, B., Chaplot, D., Chudnovsky, J., Costa, D., De Monicault, B., Garg, S., Gervet, T., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 8

Instance-Specific Image Goal Navigation: Training Embodied Agents to Find Object Instances

Krantz, J., Lee, S., Malik, J., Batra, D., & Chaplot, D. S. (2022) · arXiv

Reinforcement Learning in RoboticsSpatial Cognition and Navigation

Cited by 7