Youngchul Sung
25 papers · 2019–2026 · 6 venues · across top CS/AI venues
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πΊοΈ Taxonomy Completionist (39) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Century Club Β· Bronze
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Conference Pioneer
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Keyword Collector
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Top co-authors
Research topics
Reinforcement Learning
(21)
Methods
(20)
Machine Learning
(16)
Learning Types Β· Machine Learning
(13)
Artificial Intelligence
(9)
Core AI
(9)
Deep Learning
(8)
Learning Types Β· Deep Learning
(7)
Application Areas
(4)
Applications
(3)
Architectures
(3)
Optimization & Theory
(3)
Core Methods
(2)
Learning Paradigms
(2)
Mathematics & Optimization
(1)
Keywords
reinforcement learning
(5)
multi-agent reinforcement learning
(4)
policy learning
(2)
sample efficiency
(2)
policy gradient
(2)
offline reinforcement learning
(2)
entropy regularization
(2)
importance sampling
(2)
experience replay
(2)
reward scaling
(2)
multi-objective reinforcement learning
(2)
deep reinforcement learning
(2)
ensemble learning
(1)
domain adaptation
(1)
domain generalization
(1)
policy optimization
(1)
visual observation
(1)
imitation learning
(1)
constrained reinforcement learning
(1)
online learning
(1)
Papers
Align While Search: Belief-Guided Exploratory Inference for World-Grounded Embodied Agents
CVPR 2026
ARS: Adaptive Reward Scaling for Multi-Task Reinforcement Learning
ICML 2025
Online Pre-Training for Offline-to-Online Reinforcement Learning
ICML 2025
Penalizing Infeasible Actions and Reward Scaling in Reinforcement Learning with Offline Data
ICML 2025
ReflAct: World-Grounded Decision Making in LLM Agents via Goal-State Reflection
EMNLP 2025
Reward Dimension Reduction for Scalable Multi-Objective Reinforcement Learning
ICLR 2025
Adaptive Q-Aid for Conditional Supervised Learning in Offline Reinforcement Learning
NeurIPS 2024
Decision ConvFormer: Local Filtering in MetaFormer is Sufficient for Decision Making
ICLR 2024
Hard Tasks First: Multi-Task Reinforcement Learning Through Task Scheduling
ICML 2024
The Max-Min Formulation of Multi-Objective Reinforcement Learning: From Theory to a Model-Free Algorithm
ICML 2024
An Adaptive Entropy-Regularization Framework for Multi-Agent Reinforcement Learning
ICML 2023
Domain Adaptive Imitation Learning with Visual Observation
NeurIPS 2023
LESSON: Learning to Integrate Exploration Strategies for Reinforcement Learning via an Option Framework
ICML 2023
Parameterizing Non-Parametric Meta-Reinforcement Learning Tasks via Subtask Decomposition
NeurIPS 2023
Sample-Efficient and Safe Deep Reinforcement Learning via Reset Deep Ensemble Agents
NeurIPS 2023
Blockwise Sequential Model Learning for Partially Observable Reinforcement Learning
AAAI 2022
MASER: Multi-Agent Reinforcement Learning with Subgoals Generated from Experience Replay Buffer
ICML 2022
Quantile Constrained Reinforcement Learning: A Reinforcement Learning Framework Constraining Outage Probability
NeurIPS 2022
Robust Imitation Learning against Variations in Environment Dynamics
ICML 2022
A Max-Min Entropy Framework for Reinforcement Learning
NeurIPS 2021
Communication in Multi-Agent Reinforcement Learning: Intention Sharing
ICLR 2021
Diversity Actor-Critic: Sample-Aware Entropy Regularization for Sample-Efficient Exploration
ICML 2021
Population-Guided Parallel Policy Search for Reinforcement Learning
ICLR 2020
Dimension-Wise Importance Sampling Weight Clipping for Sample-Efficient Reinforcement Learning
ICML 2019
Message-Dropout: An Efficient Training Method for Multi-Agent Deep Reinforcement Learning
AAAI 2019