Jianhao Wang
14 papers · 2020–2025 · 6 conferences · across top CS/AI conferences
Achievements
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π Renaissance Researcher (7) π Interdisciplinary Bridge π Conference Polyglot (6) π Academic Marathon (5) πΊοΈ Taxonomy Completionist (21)
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Keyword Pioneer
π£
Hot Topic Early Bird
π
Conference Polyglot
(6)
π
Triple Crown
π
Grand Slam
π€
Dynamic Duo
(13)
β‘
Prolific Year
(6)
π
Century Club
(14)
ποΈ
Keyword Collector
(59)
Conferences
NIPS (4)
ICLR (3)
ICML (3)
AAAI (2)
CVPR (1)
IJCAI (1)
Top co-authors
Keywords
multi-agent reinforcement learning
(5)
value factorization
(2)
intrinsic reward
(2)
offline reinforcement learning
(2)
motion capture
(1)
attention mechanism
(1)
self-supervised learning
(1)
instruction tuning
(1)
uncertainty quantification
(1)
human motion
(1)
video understanding
(1)
continuous control
(1)
model-based reinforcement learning
(1)
distribution shift
(1)
graph topology
(1)
communication efficiency
(1)
exploration policy
(1)
polynomial time
(1)
latent variable model
(1)
data augmentation
(1)
Papers
Human Motion Instruction Tuning
CVPR 2025
Offline Meta Reinforcement Learning with In-Distribution Online Adaptation
ICML 2023
Active Hierarchical Exploration with Stable Subgoal Representation Learning
ICLR 2022
LAPO: Latent-Variable Advantage-Weighted Policy Optimization for Offline Reinforcement Learning
NIPS 2022
Self-Organized Polynomial-Time Coordination Graphs
ICML 2022
Multi-Agent Incentive Communication via Decentralized Teammate Modeling
AAAI 2022
Multi-Agent Concentrative Coordination with Decentralized Task Representation
IJCAI 2022
QPLEX: Duplex Dueling Multi-Agent Q-Learning
ICLR 2021
Towards Understanding Cooperative Multi-Agent Q-Learning with Value Factorization
NIPS 2021
Offline Reinforcement Learning with Reverse Model-based Imagination
NIPS 2021
Episodic Multi-agent Reinforcement Learning with Curiosity-driven Exploration
NIPS 2021
Learning Subgoal Representations with Slow Dynamics
ICLR 2021
MetaCURE: Meta Reinforcement Learning with Empowerment-Driven Exploration
ICML 2021
Object-Oriented Dynamics Learning through Multi-Level Abstraction
AAAI 2020