Yash Shukla

According to our database1, Yash Shukla authored at least 12 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Agent-Centric Human Demonstrations Train World Models.
RLJ, 2024

Autonomous Robotic Assembly: From Part Singulation to Precise Assembly.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2024

A Framework for Neurosymbolic Goal-Conditioned Continual Learning in Open World Environments.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2024

Logical Specifications-guided Dynamic Task Sampling for Reinforcement Learning Agents.
Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling, 2024

A Multilingual BERT-Based Framework for Robust Online Hate Speech Detection.
Proceedings of the IEEE International Conference on Computer Vision and Machine Intelligence, 2024

LgTS: Dynamic Task Sampling using LLM-generated Sub-Goals for Reinforcement Learning Agents.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

Formal and Natural Language assisted Curriculum Generation for Reinforcement Learning Agents.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

2023
A Framework for Few-Shot Policy Transfer Through Observation Mapping and Behavior Cloning.
IROS, 2023

Automaton-Guided Curriculum Generation for Reinforcement Learning Agents.
Proceedings of the Thirty-Third International Conference on Automated Planning and Scheduling, 2023

2022
RAPid-Learn: A Framework for Learning to Recover for Handling Novelties in Open-World Environments.
Proceedings of the IEEE International Conference on Development and Learning, 2022

ACuTE: Automatic Curriculum Transfer from Simple to Complex Environments.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

2020
Haptic Knowledge Transfer Between Heterogeneous Robots using Kernel Manifold Alignment.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020


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