Decision Transformer

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3 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

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Decision Titan: Test-Time Training for Long-Term Memory in Offline Reinforcement Learning
Oct 1, 2026Jude Waide, Robert LieckReinforcement Learning Transformer-Based RL
Department of Computer Science, University of Durham, Durham, United Kingdom.
Trust Guided Decision Transformer
Sep 25, 2026Chainesh Gautam, Raghuram Bharadwaj Diddigi, Chandramouli Kamanchi +3Transformer-Based RL Decision Transformer
International Institute of Information Technology Bangalore · IBM Research Bangalore
The Operable Pareto Front: Distilling Offline Search into Run-Time Control for Multi-Objective UAV Edge-Computing Scheduling
Sep 16, 2026Qiao Liao, Zhiyong Feng, Bin Wu +1Trajectory Optimization Edge Computing
School of Computer Science and Technology, Tianjin University, Tianjin, China · School of Computer Software, Tianjin University, Tianjin, China · School of Information Science and Engineering, Shandong Agriculture and Engineering University, Shandong, China
WiSDoM: Wireless Sparse Decision Transformer with Mixture-of-Experts for Multi-Task Mobile Network Optimization
Aug 31, 2026Fatih Temiz, Shavbo Salehi, Melike Erol-KantarciSparse Mixture-of-Experts Decision Transformer
School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Canada
Towards Scalable Multi-Task Reinforcement Learning with Large Decision Models
Jun 23, 2026Thibaut KulakReinforcement Learning Transformer
NeoInstinct SA
OnDeFog: Online Decision Transformer under Frame Dropping
Jun 18, 2026Daiki Yotsufuji, Kenta Nishihara, Shoma Shimizu +2Reinforcement Learning Transformer
Yokohama National University, Kanagawa, Japan
Generalizable Multi-Task Learning for Wireless Networks Using Prompt Decision Transformers
Jun 3, 2026Fatih Temiz, Shavbo Salehi, Melike Erol-KantarciReinforcement Learning Transformer
School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Canada
Return-to-Go Is More Than a Number: Q-Guided Alignment for Return-Conditioned Supervised Learning
May 27, 2026Yuxiao Yang, Weitong ZhangReinforcement Learning Decision Transformer
University of North Carolina at Chapel Hill
Generative Auto-Bidding with Unified Modeling and Exploration
May 19, 2026Mingming Zhang, Feiqing Zhuang, Na Li +7Automated Bidding Online Advertising
Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University · Taobao & Tmall Group of Alibaba
Beyond Autoregressive RTG: Conditioning via Injection Outside Sequential Modeling in Decision Transformer
May 7, 2026Yongyi Wang, Hanyu Liu, Lingfeng Li +6Efficient Transformer Inference Reinforcement Learning
School of Computer Science Peking University Beijing, China 100871
E $^2$ DT: Efficient and Effective Decision Transformer with Experience-Aware Sampling for Robotic Manipulation
Apr 30, 2026Kaiyan Zhao, Borong Zhang, Yiming Wang +4Long-Horizon Robotic Manipulation Transformer
School of Computer Science, Wuhan University, Wuhan 430072, China · State Key Lab of Internet of Things for Smart City and Department of Computer Information Science, University of Macau, Macao 999078, China
Direct Regret Optimization in Bayesian Optimization
Jul 9, 2025Fengxue Zhang, Yuxin ChenBayesian Optimization Learning to Optimize
Department of Computer Science University of Chicago Chicago, IL 60637

Oct 1, 2026, cs.AIJ/K move · Enter open · S save

Decision Titan: Test-Time Training for Long-Term Memory in Offline Reinforcement Learning

Jude Waide, Robert Lieck

Department of Computer Science, University of Durham, Durham, United Kingdom.

Reinforcement Learning Transformer-Based RL Decision Transformer Offline RL Test-Time Training

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Long-term dependencies remain a major challenge for sequential decision-making in the field of AI: RNNs suffer from vanishing gradients and the limited expressivity of vector-based hidden states, whilst Transformer-based models are limited by the quadratic scaling of attention. Recent work has proposed tackling this problem with the Test-Time Training (TTT) framework, which stores episodic memories in the parameters of a neural network through gradient descent at both train and test-time. This approach has seen success in the domain of Natural Language Processing, however, to the best of our knowledge it has not yet been applied to the domain of Reinforcement Learning (RL), nor has there been a study analysing how this memory practically functions. In this paper, we study the potential of the TTT framework for offline RL by augmenting a Decision Transformer with TTT layers, dubbed the Decision Titan. We analyse performance and properties of the model in the X-Maze environment, an extension of T-Maze designed to test sequential memory, and investigate how the memory mechanism learns by visualising gate values over time. Our key findings are that Decision Titan can learn long-term dependencies with ranges 20x longer than the context window, generalises to lengths 1.7x the training data, but crucially temporal generalisation depends on the time embeddings used, and the ability to learn long-term dependencies depends on how the relevant information is encoded.

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