Woojun Kim

Orcid: 0000-0001-8886-8848

According to our database¹, Woojun Kim authored at least 34 papers between 2019 and 2026.

Collaborative distances:

Dijkstra number² of three.
Erdős number³ of four.

Timeline

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Links

On csauthors.net:

Bibliography

2026

Overcoming Valid Action Suppression in Unmasked Policy Gradient Algorithms.

[BibT_eX]

[DOI]

CoRR, March, 2026

SCALAR: Learning and Composing Skills through LLM Guided Symbolic Planning and Deep RL Grounding.

[BibT_eX]

[DOI]

CoRR, March, 2026

Generalized Per-Agent Advantage Estimation for Multi-Agent Policy Optimization.

[BibT_eX]

[DOI]

CoRR, March, 2026

Theory of Mind Guided Strategy Adaptation for Zero-Shot Coordination.

[BibT_eX]

[DOI]

CoRR, February, 2026

Disentangled Concept-Residual Models: Bridging the Interpretability-Performance Gap for Incomplete Concept Sets.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2026

2025

Adaptively Coordinating with Novel Partners via Learned Latent Strategies.

[BibT_eX]

[DOI]

CoRR, November, 2025

Fair Cooperation in Mixed-Motive Games via Conflict-Aware Gradient Adjustment.

[BibT_eX]

[DOI]

Woojun Kim

Katia Sycara

CoRR, August, 2025

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration.

[BibT_eX]

[DOI]

CoRR, July, 2025

Enhancing Safety of Foundation Models for Visual Navigation through Collision Avoidance via Repulsive Estimation.

[BibT_eX]

[DOI]

CoRR, June, 2025

Speaking the Language of Teamwork: LLM-Guided Credit Assignment in Multi-Agent Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, February, 2025

B3C: A Minimalist Approach to Offline Multi-Agent Reinforcement Learning.

[BibT_eX]

[DOI]

Woojun Kim

Katia P. Sycara

CoRR, January, 2025

Escaping Local Minima: Hybrid Artificial Potential Field with Wall-Follower for Decentralized Multi-Robot Navigation.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Robotics and Automation, 2025

Integrating Multi-Robot Adaptive Sampling and Informative Path Planning for Spatiotemporal Natural Environment Prediction.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Robotics and Automation, 2025

Distributed Multi-Robot Source Seeking in Unknown Environments with Unknown Number of Sources.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Robotics and Automation, 2025

2024

HiMemFormer: Hierarchical Memory-Aware Transformer for Multi-Agent Action Anticipation.

[BibT_eX]

[DOI]

CoRR, 2024

DyPNIPP: Predicting Environment Dynamics for RL-based Robust Informative Path Planning.

[BibT_eX]

[DOI]

CoRR, 2024

OffRIPP: Offline RL-based Informative Path Planning.

[BibT_eX]

[DOI]

CoRR, 2024

Escaping Local Minima: Hybrid Artificial Potential Field with Wall-Follower for Decentralized Multi-Robot Navigation.

[BibT_eX]

[DOI]

CoRR, 2024

Value-Aided Conditional Supervised Learning for Offline RL.

[BibT_eX]

[DOI]

CoRR, 2024

Adaptive Q-Aid for Conditional Supervised Learning in Offline Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

ShapeGrasp: Zero-Shot Task-Oriented Grasping with Large Language Models through Geometric Decomposition.

[BibT_eX]

[DOI]

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2024

Decision ConvFormer: Local Filtering in MetaFormer is Sufficient for Decision Making.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Enabling technologies for AI empowered 6G massive radio access networks.

[BibT_eX]

[DOI]

ICT Express, 2023

Sample-Efficient and Safe Deep Reinforcement Learning via Reset Deep Ensemble Agents.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Domain Adaptive Imitation Learning with Visual Observation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

An Adaptive Entropy-Regularization Framework for Multi-Agent Reinforcement Learning.

[BibT_eX]

[DOI]

Woojun Kim

Youngchul Sung

Proceedings of the International Conference on Machine Learning, 2023

LESSON: Learning to Integrate Exploration Strategies for Reinforcement Learning via an Option Framework.

[BibT_eX]

[DOI]

Woojun Kim

Jeonghye Kim

Youngchul Sung

Proceedings of the International Conference on Machine Learning, 2023

Parameter Sharing with Network Pruning for Scalable Multi-Agent Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Woojun Kim

Youngchul Sung

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

A Variational Approach to Mutual Information-Based Coordination for Multi-Agent Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022

MASER: Multi-Agent Reinforcement Learning with Subgoals Generated from Experience Replay Buffer.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

2021

χ-separation: Magnetic susceptibility source separation toward iron and myelin mapping in the brain.

[BibT_eX]

[DOI]

NeuroImage, 2021

Communication in Multi-Agent Reinforcement Learning: Intention Sharing.

[BibT_eX]

[DOI]

Woojun Kim

Jongeui Park

Youngchul Sung

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

A Maximum Mutual Information Framework for Multi-Agent Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2020

2019

Message-Dropout: An Efficient Training Method for Multi-Agent Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Woojun Kim

Myungsik Cho

Youngchul Sung

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Woojun Kim

Timeline

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On csauthors.net:

Bibliography

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