Chenjun Xiao
24 papers · 2019–2026 · 8 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (6) π Interdisciplinary Bridge π§ Keyword Pioneer π Conference Polyglot (7) π Cross-Pollinator (5)
π
Cross-Pollinator
(5)
π
Renaissance Researcher
(5)
πΊοΈ
Taxonomy Completionist
(25)
π
Grand Slam
π€
Dynamic Duo
(12)
π§¬
Topic Evolution
ποΈ
Keyword Collector
(71)
π
Century Club
(22)
π₯
Unstoppable
(7)
β‘
Prolific Year
(5)
Conferences
ICML (7)
NIPS (6)
ICLR (4)
AAAI (2)
UAI (2)
ACL (1)
AISTATS (1)
IJCAI (1)
Top co-authors
Keywords
markov decision process
(3)
convergence rate
(3)
reinforcement learning
(3)
policy optimization
(2)
representation learning
(2)
policy learning
(2)
energy-based model
(2)
regret bound
(2)
tabular setting
(2)
temporal difference learning
(1)
sequential decision making
(1)
function approximation
(1)
in-context learning
(1)
supervised learning
(1)
sample efficiency
(1)
policy gradient
(1)
loss landscape
(1)
maximum entropy
(1)
neural network optimization
(1)
sample complexity
(1)
Papers
Large Language Model-Enhanced Multi-Armed Bandits
ACL 2026
An MRP Formulation for Supervised Learning: Generalized Temporal Difference Learning Models (Abstract Reprint)
AAAI 2026
Behavior-Regularized Diffusion Policy Optimization for Offline Reinforcement Learning
ICML 2025
Rethinking Decision Transformer via Hierarchical Reinforcement Learning
ICML 2024
Diffusion Spectral Representation for Reinforcement Learning
NIPS 2024
Multiagent Gumbel MuZero: Efficient Planning in Combinatorial Action Spaces
AAAI 2024
Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning
ICML 2024
Exploiting the Replay Memory Before Exploring the Environment: Enhancing Reinforcement Learning Through Empirical MDP Iteration
NIPS 2024
Iteratively Refined Behavior Regularization for Offline Reinforcement Learning
NIPS 2024
HarmonyDream: Task Harmonization Inside World Models
ICML 2024
Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation
ICML 2024
Latent Variable Representation for Reinforcement Learning
ICLR 2023
Conditionally optimistic exploration for cooperative deep multi-agent reinforcement learning
UAI 2023
Replay Memory as An Empirical MDP: Combining Conservative Estimation with Experience Replay
ICLR 2023
Energy-based Predictive Representations for Partially Observed Reinforcement Learning
UAI 2023
The In-Sample Softmax for Offline Reinforcement Learning
ICLR 2023
Understanding and Leveraging Overparameterization in Recursive Value Estimation
ICLR 2022
The Curse of Passive Data Collection in Batch Reinforcement Learning
AISTATS 2022
On the Optimality of Batch Policy Optimization Algorithms
ICML 2021
Understanding the Effect of Stochasticity in Policy Optimization
NIPS 2021
On the Global Convergence Rates of Softmax Policy Gradient Methods
ICML 2020
Escaping the Gravitational Pull of Softmax
NIPS 2020
On Principled Entropy Exploration in Policy Optimization
IJCAI 2019
Maximum Entropy Monte-Carlo Planning
NIPS 2019