Nakul Gopalan
9 papers · 2017–2024 · 3 venues · across top CS/AI venues
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Achievements
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π£ Hot Topic Early Bird π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Silver πΊοΈ Taxonomy Completionist (25) π Conference Polyglot Β· Bronze
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Topic Evolution
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Trend Setter
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Unstoppable Β· Bronze
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Renaissance Researcher
(5)
Top co-authors
Research topics
Artificial Intelligence
(7)
Machine Learning
(5)
Core AI Β· Artificial Intelligence
(5)
Learning Types
(5)
Natural Language Processing
(3)
Robotics
(3)
Applications Β· Natural Language Processing
(3)
Capabilities
(3)
Learning Paradigms
(3)
Reinforcement Learning
(2)
Computer Vision
(1)
Deep Learning
(1)
Analysis
(1)
Applications Β· Reinforcement Learning
(1)
Core AI Β· Computer Vision
(1)
Keywords
language grounding
(2)
hierarchical abstraction
(2)
sample efficiency
(2)
robotic manipulation
(2)
natural language understanding
(2)
reinforcement learning
(2)
learning from demonstration
(2)
task abstraction
(2)
imitation learning
(1)
few-shot learning
(1)
continual learning
(1)
task generalization
(1)
scene graph
(1)
human-robot interaction
(1)
instruction following
(1)
natural language
(1)
visual language grounding
(1)
demonstration learning
(1)
robot behavior
(1)
markov decision process
(1)
Papers
Interactive Visual Task Learning for Robots
AAAI 2024
Investigating the Impact of Experience on a User's Ability to Perform Hierarchical Abstraction
RSS 2023
Negative Result for Learning from Demonstration: Challenges for End-Users Teaching Robots with Task And Motion Planning Abstractions
RSS 2022
"Good Robot! Now Watch This!": Repurposing Reinforcement Learning for Task-to-Task Transfer
CoRL 2021
Guiding Multi-Step Rearrangement Tasks with Natural Language Instructions
CoRL 2021
Robot Object Retrieval with Contextual Natural Language Queries
RSS 2020
Simultaneously Learning Transferable Symbols and Language Groundings from Perceptual Data for Instruction Following
RSS 2020
Sequence-to-Sequence Language Grounding of Non-Markovian Task Specifications
RSS 2018
Accurately and Efficiently Interpreting Human-Robot Instructions of Varying Granularities
RSS 2017