Cover Image

PADiff: Predictive and Adaptive Diffusion Policies for Ad Hoc Teamwork

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chan, Hohei, Zhang, Xinzhi, Xiang, Antao, Zhang, Weinan, Zhao, Mengchen
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Symmetry-Breaking Augmentations for Ad Hoc Teamwork
by: Hammond, Ravi, et al.
Published: (2024)

RecBayes: Recurrent Bayesian Ad Hoc Teamwork in Large Partially Observable Domains
by: Ribeiro, João G., et al.
Published: (2025)

A Minimax Approach to Ad Hoc Teamwork
by: Villin, Victor, et al.
Published: (2025)

Score-Based Diffusion Policy Compatible with Reinforcement Learning via Optimal Transport
by: Sun, Mingyang, et al.
Published: (2025)

Seldonian Reinforcement Learning for Ad Hoc Teamwork
by: Zorzi, Edoardo, et al.
Published: (2025)

Open Ad Hoc Teamwork with Cooperative Game Theory
by: Wang, Jianhong, et al.
Published: (2024)

Diffusion-DICE: In-Sample Diffusion Guidance for Offline Reinforcement Learning
by: Mao, Liyuan, et al.
Published: (2024)

Multi-party Agent Relation Sampling for Multi-party Ad Hoc Teamwork
by: Zhang, Beiwen, et al.
Published: (2025)

Unsupervised Partner Design Enables Robust Ad-hoc Teamwork
by: Ruhdorfer, Constantin, et al.
Published: (2025)

Minimum Coverage Sets for Training Robust Ad Hoc Teamwork Agents
by: Rahman, Arrasy, et al.
Published: (2023)

N-Agent Ad Hoc Teamwork
by: Wang, Caroline, et al.
Published: (2024)

Reinforcing Language Agents via Policy Optimization with Action Decomposition
by: Wen, Muning, et al.
Published: (2024)

Diffusion Models for Reinforcement Learning: A Survey
by: Zhu, Zhengbang, et al.
Published: (2023)

LRT-Diffusion: Calibrated Risk-Aware Guidance for Diffusion Policies
by: Sun, Ximan, et al.
Published: (2025)

Generic-to-Specific Reasoning and Learning for Scalable Ad Hoc Teamwork
by: Dodampegama, Hasra, et al.
Published: (2025)

DepCap: Adaptive Block-Wise Parallel Decoding for Efficient Diffusion LM Inference
by: Xia, Xiang, et al.
Published: (2026)

Benchmarking the Limits of In-Context Reinforcement Learning for Ad-Hoc Teamwork
by: Jing, Yuheng, et al.
Published: (2026)

DiffStitch: Boosting Offline Reinforcement Learning with Diffusion-based Trajectory Stitching
by: Li, Guanghe, et al.
Published: (2024)

Entropy-Regularized Token-Level Policy Optimization for Language Agent Reinforcement
by: Wen, Muning, et al.
Published: (2024)

Adaptive Diffusion Policy Optimization for Robotic Manipulation
by: Jiang, Huiyun, et al.
Published: (2025)

PFedDST: Personalized Federated Learning with Decentralized Selection Training
by: Fan, Mengchen, et al.
Published: (2025)

Beyond State-Wise Mirror Descent: Offline Policy Optimization with Parametric Policies
by: Li, Xiang, et al.
Published: (2026)

Refined Edge Usage of Graph Neural Networks for Edge Prediction
by: Jin, Jiarui, et al.
Published: (2022)

Prompt Tuning with Diffusion for Few-Shot Pre-trained Policy Generalization
by: Hu, Shengchao, et al.
Published: (2024)

Predict-then-Diffuse: Adaptive Response Length for Compute-Budgeted Inference in Diffusion LLMs
by: Rottoli, Michael, et al.
Published: (2026)

Maximum Entropy Reinforcement Learning with Diffusion Policy
by: Dong, Xiaoyi, et al.
Published: (2025)

Offline Policy Evaluation for Reinforcement Learning with Adaptively Collected Data
by: Madhow, Sunil, et al.
Published: (2023)

Holder Policy Optimisation
by: Chen, Yuxiang, et al.
Published: (2026)

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air
by: Yang, Shiyi, et al.
Published: (2025)

MADiff: Offline Multi-agent Learning with Diffusion Models
by: Zhu, Zhengbang, et al.
Published: (2023)

TS-DP: Reinforcement Speculative Decoding For Temporal Adaptive Diffusion Policy Acceleration
by: Li, Ye, et al.
Published: (2025)

Adaptive Layerwise Perturbation: Unifying Off-Policy Corrections for LLM RL
by: Ye, Chenlu, et al.
Published: (2026)

LLM-Driven Policy Diffusion: Enhancing Generalization in Offline Reinforcement Learning
by: Zhang, Hanping, et al.
Published: (2025)

Pre-Hoc Predictions in AutoML: Leveraging LLMs to Enhance Model Selection and Benchmarking for Tabular datasets
by: Belkhiter, Yannis, et al.
Published: (2025)

Policy Gradient with Adaptive Entropy Annealing for Continual Fine-Tuning
by: Zhang, Yaqian, et al.
Published: (2026)

From Noise to Control: Parameterized Diffusion Policies
by: Zhang, Renhao, et al.
Published: (2026)

Preferred-Action-Optimized Diffusion Policies for Offline Reinforcement Learning
by: Zhang, Tianle, et al.
Published: (2024)

Active Tabular Augmentation via Policy-Guided Diffusion Inpainting
by: Zhang, Zheyu, et al.
Published: (2026)

Ada-Diffuser: Latent-Aware Adaptive Diffusion for Decision-Making
by: Feng, Fan, et al.
Published: (2026)

Model-agnostic Selective Labeling with Provable Statistical Guarantees
by: Huang, Huipeng, et al.
Published: (2025)