← Authors

Zongzhang Zhang

51 papers · 2014–2026 · 6 conferences · across top CS/AI conferences

Achievements

πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (11) 🌍 Conference Polyglot (6) 🐝 Cross-Pollinator (5) πŸ—ΊοΈ Taxonomy Completionist (66) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (10) 🏠 Conference Loyalist (22) 🀝 Dynamic Duo (28) πŸ‘‘ Triple Crown πŸ† Keyword Champion (2) πŸ† Grand Slam πŸ”¬ Deep Specialist (19) πŸ’Ž Century Club (47) πŸ—ƒοΈ Keyword Collector (192) πŸ“ˆ Trend Setter ⚑ Prolific Year (5) πŸ”₯ Unstoppable (9)

Conferences

AAAI (22) IJCAI (9) NIPS (8) ICML (6) ICLR (5) ACL (1)

Top co-authors

Yang Yu (30) Lei Yuan (11) Chenyang Wu (8) Yi-Chen Li (7) Fuxiang Zhang (7) Chen-Xiao Gao (6) Rui Kong (5) Jianye Hao (5) Wulong Liu (5) Cong Guan (4)

Keywords

reinforcement learning (10) multi-agent reinforcement learning (6) policy optimization (6) representation learning (5) deep reinforcement learning (5) offline reinforcement learning (5) multi-agent system (4) imitation learning (3) domain adaptation (3) attention mechanism (3) reward model (3) contrastive learning (2) few-shot learning (2) value function (2) online planning (2) value iteration (2) sample efficiency (2) in-context learning (2) policy learning (2) preference alignment (2)

Papers

Reward Model Evaluation via Automatically-Ranked Policy Alignment AAAI 2026
Efficient Preference Alignment via Pareto Exploration (Student Abstract) AAAI 2026
Meta-Normalizing Flow for Data-Limited Offline Meta-Reinforcement Learning (Student Abstract) AAAI 2026
Multi-agent In-context Coordination via Decentralized Memory Retrieval AAAI 2026
Behavior-Regularized Diffusion Policy Optimization for Offline Reinforcement Learning ICML 2025
Reinforced In-Context Black-Box Optimization IJCAI 2025
Q-Adapter: Customizing Pre-trained LLMs to New Preferences with Forgetting Mitigation ICLR 2025
Lost in the Context: Insufficient and Distracted Attention to Contexts in Preference Modeling ACL 2025
Reward Models in Deep Reinforcement Learning: A Survey IJCAI 2025
Efficient and Stable Offline-to-online Reinforcement Learning via Continual Policy Revitalization IJCAI 2024
ODRL: A Benchmark for Off-Dynamics Reinforcement Learning NIPS 2024
Multi-Agent Domain Calibration with a Handful of Offline Data NIPS 2024
Focus-Then-Decide: Segmentation-Assisted Reinforcement Learning AAAI 2024
ACT: Empowering Decision Transformer with Dynamic Programming via Advantage Conditioning AAAI 2024
Generalizable Task Representation Learning for Offline Meta-Reinforcement Learning with Data Limitations AAAI 2024
Generalizable Policy Improvement via Reinforcement Sampling (Student Abstract) AAAI 2024
Multi-Expert Distillation for Few-Shot Coordination (Student Abstract) AAAI 2024
Policy Rehearsing: Training Generalizable Policies for Reinforcement Learning ICLR 2024
Attention-Guided Contrastive Role Representations for Multi-agent Reinforcement Learning ICLR 2024
Language Model Self-improvement by Reinforcement Learning Contemplation ICLR 2024
Deep Demonstration Tracing: Learning Generalizable Imitator Policy for Runtime Imitation from a Single Demonstration ICML 2024
Debiased Offline Representation Learning for Fast Online Adaptation in Non-stationary Dynamics ICML 2024
Deep Anomaly Detection and Search via Reinforcement Learning (Student Abstract) AAAI 2023
Policy-Independent Behavioral Metric-Based Representation for Deep Reinforcement Learning AAAI 2023
Model-Based Offline Weighted Policy Optimization (Student Abstract) AAAI 2023
Learning Generalizable Batch Active Learning Strategies via Deep Q-networks (Student Abstract) AAAI 2023
Retrosynthetic Planning with Dual Value Networks ICML 2023
Policy Regularization with Dataset Constraint for Offline Reinforcement Learning ICML 2023
Anti-drifting Feature Selection via Deep Reinforcement Learning (Student Abstract) AAAI 2023
Expert Data Augmentation in Imitation Learning (Student Abstract) AAAI 2023
Towards Deployment-Efficient and Collision-Free Multi-Agent Path Finding (Student Abstract) AAAI 2023
Discovering Generalizable Multi-agent Coordination Skills from Multi-task Offline Data ICLR 2023
Adapt to Environment Sudden Changes by Learning a Context Sensitive Policy AAAI 2022
Multi-Agent Incentive Communication via Decentralized Teammate Modeling AAAI 2022
Multi-Agent Concentrative Coordination with Decentralized Task Representation IJCAI 2022
Efficient Multi-Agent Communication via Shapley Message Value IJCAI 2022
Multi-agent Dynamic Algorithm Configuration NIPS 2022
Bayesian Optimistic Optimization: Optimistic Exploration for Model-based Reinforcement Learning NIPS 2022
Efficient Multi-agent Communication via Self-supervised Information Aggregation NIPS 2022
Cross-modal Domain Adaptation for Cost-Efficient Visual Reinforcement Learning NIPS 2021
Enhancing Context-Based Meta-Reinforcement Learning Algorithms via An Efficient Task Encoder (Student Abstract) AAAI 2021
LB-DESPOT: Efficient Online POMDP Planning Considering Lower Bound in Action Selection (Student Abstract) AAAI 2021
Adaptive Online Packing-guided Search for POMDPs NIPS 2021
Triple-GAIL: A Multi-Modal Imitation Learning Framework with Generative Adversarial Nets IJCAI 2020
Generative Adversarial Imitation Learning from Failed Experiences (Student Abstract) AAAI 2020
Third-Person Imitation Learning via Image Difference and Variational Discriminator Bottleneck (Student Abstract) AAAI 2020
Efficient Deep Reinforcement Learning via Adaptive Policy Transfer IJCAI 2020
Monte Carlo Tree Search for Policy Optimization IJCAI 2019
A Deep Bayesian Policy Reuse Approach Against Non-Stationary Agents NIPS 2018
Weighted Double Q-learning IJCAI 2017
Covering Number for Efficient Heuristic-based POMDP Planning ICML 2014