Publications
============

This page lists papers and technical reports associated with **RLinf**. Detailed publication pages (with results and quickstart links) are linked below.

Detailed publication pages
--------------------------

.. list-table::
   :header-rows: 1

   * - Publication
     - Focus
     - Preprint
   * - :doc:`STEAM <steam>`
     - Self-supervised temporal ensemble advantage modeling for real-world robot learning.
     - `arXiv:2606.29834 <https://arxiv.org/abs/2606.29834>`__
   * - :doc:`RLinf-USER <rlinf_user>`
     - Unified system for real-world online policy learning.
     - `arXiv:2602.07837 <https://arxiv.org/abs/2602.07837>`__
   * - :doc:`RLinf-VLA <rlinf_vla>`
     - Unified framework for VLA+RL training.
     - `arXiv:2510.06710 <https://arxiv.org/abs/2510.06710>`__
   * - :doc:`RLinf-Co <rlinf_co>`
     - Reinforcement learning-based sim-real co-training for VLA models.
     - `arXiv:2602.12628 <https://arxiv.org/abs/2602.12628>`__
   * - :doc:`RLinf <rlinf_system>`
     - Flexible and efficient RL system.
     - `arXiv:2509.15965 <https://arxiv.org/abs/2509.15965>`__
   * - :doc:`πRL <pi_rl>`
     - Online RL fine-tuning for flow-based VLA models.
     - `arXiv:2510.25889 <https://arxiv.org/abs/2510.25889>`__
   * - :doc:`WoVR <wovr>`
     - World model-based RL fine-tuning for VLA policies.
     - `arXiv:2602.13977 <https://arxiv.org/abs/2602.13977>`__
   * - :doc:`WideSeek-R1 <wideseek_r1>`
     - Exploring width scaling for broad information seeking via multi-agent reinforcement learning.
     - `arXiv:2602.04634 <https://arxiv.org/abs/2602.04634>`__

.. toctree::
   :hidden:
   :maxdepth: 2

   steam
   rlinf_user
   rlinf_vla
   rlinf_co
   rlinf_system
   pi_rl
   wovr
   wideseek_r1
