Nishanth Kumar

According to our database, Nishanth Kumar authored at least 32 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

From Pixels to Predicates: Learning Symbolic World Models via Pretrained VLMs.

Ashay Athalye, Nishanth Kumar, Tom Silver, Yichao Liang, Jiuguang Wang, Tomás Lozano-Pérez, Leslie Pack Kaelbling

IEEE Robotics Autom. Lett., April, 2026

Open-World Task and Motion Planning via Vision-Language Model Generated Constraints.

Nishanth Kumar, William Shen, Fabio Ramos, Dieter Fox, Tomás Lozano-Pérez, Leslie Pack Kaelbling, Caelan Reed Garrett

IEEE Robotics Autom. Lett., March, 2026

TiPToP: A Modular Open-Vocabulary Planning System for Robotic Manipulation.

William Shen, Nishanth Kumar, Sahit Chintalapudi, Jie Wang, Christopher Watson, Edward Hu, Jing Cao, Dinesh Jayaraman, Leslie Pack Kaelbling, Tomás Lozano-Pérez

CoRR, March, 2026

Follow the Signs: Using Textual Cues and LLMs to Guide Efficient Robot Navigation.

Jing Cao, Nishanth Kumar, Aidan Curtis

CoRR, January, 2026

2025

Seeing is Believing: Belief-Space Planning with Foundation Models as Uncertainty Estimators.

Linfeng Zhao, Willie McClinton, Aidan Curtis, Nishanth Kumar, Tom Silver, Leslie Pack Kaelbling, Lawson L. S. Wong

CoRR, April, 2025

Guided Exploration for Efficient Relational Model Learning.

Annie Feng, Nishanth Kumar, Tomás Lozano-Pérez, Leslie Pack Kaelbling

CoRR, February, 2025

Predicate Invention from Pixels via Pretrained Vision-Language Models.

Ashay Athalye, Nishanth Kumar, Tom Silver, Yichao Liang, Tomás Lozano-Pérez, Leslie Pack Kaelbling

CoRR, January, 2025

VisualPredicator: Learning Abstract World Models with Neuro-Symbolic Predicates for Robot Planning.

Yichao Liang, Nishanth Kumar, Hao Tang, Adrian Weller, Joshua B. Tenenbaum, Tom Silver, João F. Henriques, Kevin Ellis

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

AHA: A Vision-Language-Model for Detecting and Reasoning Over Failures in Robotic Manipulation.

Jiafei Duan, Wilbert Pumacay, Nishanth Kumar, Yi Ru Wang, Shulin Tian, Wentao Yuan, Ranjay Krishna, Dieter Fox, Ajay Mandlekar, Yijie Guo

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

PGMax: Factor Graphs for Discrete Probabilistic Graphical Models and Loopy Belief Propagation in JAX.

Guangyao Zhou, Antoine Dedieu, Nishanth Kumar, Wolfgang Lehrach, Shrinu Kushagra, Dileep George, Miguel Lázaro-Gredilla

J. Mach. Learn. Res., 2024

Open-World Task and Motion Planning via Vision-Language Model Inferred Constraints.

Nishanth Kumar, Fabio Ramos, Dieter Fox, Caelan Reed Garrett

CoRR, 2024

Learning to Bridge the Gap: Efficient Novelty Recovery with Planning and Reinforcement Learning.

Alicia Li, Nishanth Kumar, Tomás Lozano-Pérez, Leslie Pack Kaelbling

CoRR, 2024

Practice Makes Perfect: Planning to Learn Skill Parameter Policies.

Nishanth Kumar, Tom Silver, Willie McClinton, Linfeng Zhao, Stephen Proulx, Tomás Lozano-Pérez, Leslie Pack Kaelbling, Jennifer L. Barry

CoRR, 2024

Practice Makes Perfect: Planning to Learning Skill Parameter Policies.

Nishanth Kumar, Tom Silver, Willie McClinton, Linfeng Zhao, Stephen Proulx, Tomás Lozano-Pérez, Leslie Pack Kaelbling, Jennifer L. Barry

Proceedings of the Robotics: Science and Systems XX, 2024

Preference-Conditioned Language-Guided Abstraction.

Andi Peng, Andreea Bobu, Belinda Z. Li, Theodore R. Sumers, Ilia Sucholutsky, Nishanth Kumar, Thomas L. Griffiths, Julie A. Shah

Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction, 2024

Adaptive Language-Guided Abstraction from Contrastive Explanations.

Andi Peng, Belinda Z. Li, Ilia Sucholutsky, Nishanth Kumar, Julie Shah, Jacob Andreas, Andreea Bobu

Proceedings of the Conference on Robot Learning, 6-9 November 2024, Munich, Germany., 2024

Trust the PRoC3S: Solving Long-Horizon Robotics Problems with LLMs and Constraint Satisfaction.

Aidan Curtis, Nishanth Kumar, Jing Cao, Tomás Lozano-Pérez, Leslie Pack Kaelbling

Proceedings of the Conference on Robot Learning, 6-9 November 2024, Munich, Germany., 2024

2023

Economic Trading Susceptibility: Constructing Networks of Mutual Influence through the Fitness of Countries.

Nishanth Kumar, Henrik Jeldtoft Jensen, Eduardo Viegas

Entropy, January, 2023

Learning Efficient Abstract Planning Models that Choose What to Predict.

Nishanth Kumar, Willie McClinton, Rohan Chitnis, Tom Silver, Tomás Lozano-Pérez, Leslie Pack Kaelbling

Proceedings of the Conference on Robot Learning, 2023

Predicate Invention for Bilevel Planning.

Tom Silver, Rohan Chitnis, Nishanth Kumar, Willie McClinton, Tomás Lozano-Pérez, Leslie Pack Kaelbling, Joshua B. Tenenbaum

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Learning Operators with Ignore Effects for Bilevel Planning in Continuous Domains.

Nishanth Kumar, Willie McClinton, Rohan Chitnis, Tom Silver, Tomás Lozano-Pérez, Leslie Pack Kaelbling

CoRR, 2022

Inventing Relational State and Action Abstractions for Effective and Efficient Bilevel Planning.

Tom Silver, Rohan Chitnis, Nishanth Kumar, Willie McClinton, Tomás Lozano-Pérez, Leslie Pack Kaelbling, Joshua B. Tenenbaum

CoRR, 2022

PGMax: Factor Graphs for Discrete Probabilistic Graphical Models and Loopy Belief Propagation in JAX.

Guangyao Zhou, Nishanth Kumar, Miguel Lázaro-Gredilla, Shrinu Kushagra, Dileep George

CoRR, 2022

2021

Just Label What You Need: Fine-Grained Active Selection for Perception and Prediction through Partially Labeled Scenes.

Sean Segal, Nishanth Kumar, Sergio Casas, Wenyuan Zeng, Mengye Ren, Jingkang Wang, Raquel Urtasun

CoRR, 2021

Just Label What You Need: Fine-Grained Active Selection for P&P through Partially Labeled Scenes.

Sean Segal, Nishanth Kumar, Sergio Casas, Wenyuan Zeng, Mengye Ren, Jingkang Wang, Raquel Urtasun

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020

Rate of change analysis for interestingness measures.

Nandan Sudarsanam, Nishanth Kumar, Abhishek Sharma, Balaraman Ravindran

Knowl. Inf. Syst., 2020

Task Scoping: Building Goal-Specific Abstractions for Planning in Complex Domains.

Nishanth Kumar, Michael Fishman, Natasha Danas, Michael Littman, Stefanie Tellex, George Konidaris

CoRR, 2020

The Past and Present of Imitation Learning: A Citation Chain Study.

Nishanth Kumar

CoRR, 2020

Building Plannable Representations with Mixed Reality.

Eric Rosen, Nishanth Kumar, Nakul Gopalan, Daniel Ullman, George Konidaris, Stefanie Tellex

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Task Scoping for Efficient Planning in Open Worlds (Student Abstract).

Nishanth Kumar, Michael Fishman, Natasha Danas, Stefanie Tellex, Michael Littman, George Konidaris

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Learning Deep Parameterized Skills from Demonstration for Re-targetable Visuomotor Control.

Jonathan Chang, Nishanth Kumar, Sean Hastings, Aaron Gokaslan, Diego Romeres, Devesh K. Jha, Daniel Nikovski, George Dimitri Konidaris, Stefanie Tellex

CoRR, 2019

Multi-Object Search using Object-Oriented POMDPs.

Arthur Wandzel, Yoonseon Oh, Michael Fishman, Nishanth Kumar, Lawson L. S. Wong, Stefanie Tellex

Proceedings of the International Conference on Robotics and Automation, 2019