Zongzhang Zhang

papers

178

total citations

papers (11)

Language Model Self-improvement by Reinforcement Learning Contemplation

ICLR 2024arXiv

citations

Multi-agent Dynamic Algorithm Configuration

NEURIPS 2022arXiv

citations

ACT: Empowering Decision Transformer with Dynamic Programming via Advantage Conditioning

AAAI 2024arXiv

citations

Generalizable Task Representation Learning for Offline Meta-Reinforcement Learning with Data Limitations

AAAI 2024arXiv

citations

EvaLearn: Quantifying the Learning Capability and Efficiency of LLMs via Sequential Problem Solving

NEURIPS 2025arXiv

citations

Debiased Offline Representation Learning for Fast Online Adaptation in Non-stationary Dynamics

ICML 2024arXiv

citations

Bayesian Optimistic Optimization: Optimistic Exploration for Model-based Reinforcement Learning

NEURIPS 2022

citations

Deep Demonstration Tracing: Learning Generalizable Imitator Policy for Runtime Imitation from a Single Demonstration

ICML 2024

citations

Zongzhang Zhang

papers (11)

Language Model Self-improvement by Reinforcement Learning Contemplation

Multi-agent Dynamic Algorithm Configuration

ACT: Empowering Decision Transformer with Dynamic Programming via Advantage Conditioning

Generalizable Task Representation Learning for Offline Meta-Reinforcement Learning with Data Limitations

EvaLearn: Quantifying the Learning Capability and Efficiency of LLMs via Sequential Problem Solving

Debiased Offline Representation Learning for Fast Online Adaptation in Non-stationary Dynamics

Bayesian Optimistic Optimization: Optimistic Exploration for Model-based Reinforcement Learning

Cross-modal Domain Adaptation for Cost-Efficient Visual Reinforcement Learning

Adaptive Online Packing-guided Search for POMDPs

Efficient Multi-agent Communication via Self-supervised Information Aggregation

Deep Demonstration Tracing: Learning Generalizable Imitator Policy for Runtime Imitation from a Single Demonstration

papers (11)

Language Model Self-improvement by Reinforcement Learning Contemplation

Multi-agent Dynamic Algorithm Configuration

ACT: Empowering Decision Transformer with Dynamic Programming via Advantage Conditioning

Generalizable Task Representation Learning for Offline Meta-Reinforcement Learning with Data Limitations

EvaLearn: Quantifying the Learning Capability and Efficiency of LLMs via Sequential Problem Solving

Debiased Offline Representation Learning for Fast Online Adaptation in Non-stationary Dynamics

Bayesian Optimistic Optimization: Optimistic Exploration for Model-based Reinforcement Learning

Cross-modal Domain Adaptation for Cost-Efficient Visual Reinforcement Learning

Adaptive Online Packing-guided Search for POMDPs

Efficient Multi-agent Communication via Self-supervised Information Aggregation

Deep Demonstration Tracing: Learning Generalizable Imitator Policy for Runtime Imitation from a Single Demonstration