mlsanityData to 14 Oct 2026

TransDreamerV3: Implanting Transformer In DreamerV3

arXiv 2506.17103 ↗First posted 20 Jun 2025cs.LG cs.AIcited by 2

On the map: Deep reinforcement learning methods → Deep RL algorithms and representations

Abstract (arXiv)

This paper introduces TransDreamerV3, a reinforcement learning model that enhances the DreamerV3 architecture by integrating a transformer encoder. The model is designed to improve memory and decision-making capabilities in complex environments. We conducted experiments on Atari-Boxing, Atari-Freeway, Atari-Pong, and Crafter tasks, where TransDreamerV3 demonstrated improved performance over DreamerV3, particularly in the Atari-Freeway and Crafter tasks. While issues in the Minecraft task and limited training across all tasks were noted, TransDreamerV3 displays advancement in world model-based reinforcement learning, leveraging transformer architectures.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in Deep RL algorithms and representations, one of 15 directions in Deep reinforcement learning methods. Builds on 14 of its 16 references that are in the map. First posted on arXiv 20 Jun 2025.

Builds on

14 of 16 references.

References · 14

  1. 2017Attention Is All You Needcited by 60,361
  2. 2019Dream to Control: Learning Behaviors by Latent Imaginationcited by 1,653
  3. 2021Decision Transformer: Reinforcement Learning via Sequence Modelingcited by 1,546
  4. 2018World Modelscited by 1,513
  5. 2018Learning Latent Dynamics for Planning from Pixelscited by 1,264
  6. 2023Mastering Diverse Domains through World Modelscited by 1,253
  7. 2020Mastering Atari with Discrete World Modelscited by 1,007
  8. 2021Offline Reinforcement Learning as One Big Sequence Modeling Problemcited by 644
  9. 2022Transformers are Sample-Efficient World Modelscited by 328
  10. 2019Stabilizing Transformers for Reinforcement Learningcited by 270
  11. 2022TransDreamer: Reinforcement Learning with Transformer World Modelscited by 143
  12. 2021Going Beyond Linear Transformers with Recurrent Fast Weight Programmerscited by 89
2 more
  1. 2020Rapid Task-Solving in Novel Environmentscited by 23
  2. 2020MEMO: A Deep Network for Flexible Combination of Episodic Memoriescited by 21

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026PH-Dreamer: A Physics-Driven World Model via Port-Hamiltonian Generative Dynamicscited by 3
  2. 2026World Models: A Comprehensive Survey of Architectures, Methodologies, Reasoning Paradigms, and Applicationscited by 3

Similar, not cited

Close in wording, no citation either way

  1. 2024Learning to Play Atari in a World of Tokens
  2. 2022Multi-Game Decision Transformers
  3. 2025Learning Transformer-based World Models with Contrastive Predictive Coding
  4. 2023Transformer-based World Models Are Happy With 100k Interactions
  5. 2023Transformers in Reinforcement Learning: A Survey
  6. 2023Recurrent Action Transformer with Memory
  7. 2025Memo: Training Memory-Efficient Embodied Agents with Reinforcement Learning
  8. 2023Emergent Agentic Transformer from Chain of Hindsight Experience