Prioritized Experience Replay

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6 papers in the last four weeks, against 2 the four weeks before. 0.1% of all new papers.

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ALER: Adaptive Learnable Experience Rewriting for Reinforcement Learning
Sep 30, 2026Oleg Shchendrigin, Egor Cherepanov, Aleksandr I. Panov +1Prioritized Experience Replay Offline Reinforcement Learning
Innopolis University, Innopolis, Russia · MIRIAI, Moscow, Russia · Cognitive AI Systems Lab, Moscow, Russia
Experimental Experience Modeling for Autonomous Research
Sep 30, 2026Wenda Wei, Yingchen Zhang, Ruqing Zhang +3Bayesian Experimental Design Prioritized Experience Replay
State Key Laboratory of AI Safety · Institute of Computing Technology, Chinese Academy of Sciences · University of Chinese Academy of Sciences +1
Reliable Replay through Spatial Coherence in Online Continual Learning
Sep 27, 2026Haixiang Sun, Jiefu Zhang, Yinghao He +4Prioritized Experience Replay Replay-Based Continual Learning
Purdue University West Lafayette, IN 47907, USA
Correcting Within-Group Self-Selection Bias in Prioritized Replay
Sep 21, 2026Oscar Miró López-Feliu, Herke van HoofPrioritized Experience Replay Group-Based Reinforcement Learning
University of Amsterdam
ReDIL-GNN: Resynthesis Domain Incremental Learning for Circuit Graph Neural Networks
Sep 16, 2026Rupesh Raj Karn, Johann Knechtel, Ozgur SinanogluDifferentiable Logic Gate Networks Gnn-Based Detectors
Center for Cyber Security, New York University, Abu Dhabi, UAE.
Anchoring What Matters: A Dual-Level Learning Framework for Visually-Grounded Multimodal Reasoning
Sep 16, 2026Xinxin Song, Siyuan Li, Tingxiong Xiao +1Recent Vision-Language Models Reinforcement Learning With Verifiable Reward
Department of Automation, Tsinghua University · Institute for Brain and Cognitive Science, Tsinghua University
Recurrent Dynamic Range Extension
Sep 14, 2026Sebastian Dille, Keru Fu, S. Mahdi H. Miangoleh +1High Dynamic Range Deterministic Reconstruction
Computational Photography Lab., Simon Fraser University, Canada
One Adapter, Many Tasks: Task-Conditioned Feature Transformations for Continual Learning
Aug 31, 2026Yunxiang Fu, Meng Lou, Yizhou YuClass-Incremental Learning Continual Learning
School of Computing and Data Science The University of Hong Kong
Uncertainty-Driven Replay Memory for Reinforcement Learning
Aug 30, 2026Sheeraja Rajakrishnan, Alexander G. Ororbia, Travis Desell +1Prioritized Experience Replay Transitions
Rochester Institute of Technology
Toward Integrating Adaptive Experience Replay and Online Uncertainty Estimation in Safe Actor-Critic Optimal Control
Aug 5, 2026Mahshad Rastegarmoghaddam, Davoud Nikkhouy, Shima SamadzadehControl Barrier Functions Soft Actor-Critic
Department of Mechanical Engineering, Politecnico di Milano, Milan, Italy
UniMem: Complementary Episodic-to-Parametric Memory for Boundary-Agnostic Task Streams
Jul 28, 2026Siyu Xia, Chenheng Zhang, Yanting Wu +8Parametric Memory Episodic Memory
Institute of Automation, Chinese Academy of Sciences, Beijing, China · School of Artificial Intelligence, University of Chinese Academy of Sciences, China · State Key Lab of General Artificial Intelligence, School of Intelligence Science and Technology, Peking University +3
Revocable Learned State via Process Sidecars
Jun 29, 2026John SweeneyCounterfactual Learning Prioritized Experience Replay
Sideplane AI
Optimizer Memory Makes Shuffle Order a First-Order Source of Fine-Tuning Noise
Jun 28, 2026John SweeneyRandom Rotations Prioritized Experience Replay
The Gentle Collapse: Distributional Metrics for Continual Learning
Jun 23, 2026Ahmed Anwar, Andreas Wagner, Federico Raue +2Catastrophic Forgetting Prioritized Experience Replay
1German Research Center for Artificial Intelligence (DFKI) · 2RPTU University Kaiserslautern-Landau, Kaiserslautern, Germany · 3Hochschule Karlsruhe University of Applied Sciences, Karlsruhe, Germany
Workflow-to-Skill: Skill Creation via Routing-Workflow-Semantics-Attachments Decomposition
Jun 5, 2026Yuyang Zhang, Xinyuan Han, Xudong Jiang +1Skills Agentic Workflow Design
Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University · Nanchang University
BBR-Net: Boundary-Balanced Replay for Continual Medical Image Segmentation
Jun 2, 2026Zahid Ullah, Sieun Choi, Jihie KimSemi-Supervised Medical Image Segmentation Echocardiography
Department of Computer Science and Artificial Intelligence, Dongguk University, Seoul, 04620, Republic of Korea
Continual Learning in Modern Hopfield Networks with an Application to Diffusion Models
May 27, 2026Ken Takeda, Masafumi Oizumi, Ryo KarakidaCatastrophic Forgetting Hopfield Networks
Graduate School of Arts and Science, The University of Tokyo, Tokyo, Japan · Artificial Intelligence Research Center, AIST, Tokyo, Japan
Automated Reformulation of Robust Optimization via Memory-Augmented Large Language Models
May 12, 2026Jinbiao Chen, Shuang Jin, Guoyun Zhang +3Robust Optimization Memory-Augmented Framework
Department of Industrial Systems Engineering and Management, National University of Singapore · Department of Data and Systems Engineering, The University of Hong Kong · Institute of Operations Research and Analytics, National University of Singapore +1
From Passive Reuse to Active Reasoning: Grounding Large Language Models for Neuro-Symbolic Experience Replay
May 10, 2026Yanan Xiao, Yixiang Tang, Zechen Feng +3Prioritized Experience Replay Hierarchical Reinforcement Learning
1Affiliation 1 · 2Affiliation 2 · 3Affiliation 3
Freshness-Aware Prioritized Experience Replay for LLM/VLM Reinforcement Learning
Apr 18, 2026Weiyu Ma, Yongcheng Zeng, Yan Song +4Large Language Model Reinforcement Learning Prioritized Experience Replay
King Abdullah University of Science and Technology (KAUST) · Chinese Academy of Sciences, Institute of Automation (CASIA) · AI Centre, Department of Computer Science, University College London +1
Continual Hand-Eye Calibration for Open-world Robotic Manipulation
Apr 17, 2026Fazeng Li, Gan Sun, Chenxi Liu +3Robotic Manipulation Prioritized Experience Replay
School of Automation Science and Engineering, South China University of Technology, Guangzhou 510641, China · State Key Laboratory of Robotics, the Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China · University of Chinese Academy of Sciences, Beijing 100049, China
VLM-Guided Experience Replay
Feb 2, 2026Elad Sharony, Tom Jurgenson, Orr Krupnik +2Large Language Model Reinforcement Learning Prioritized Experience Replay
Technion · ForSight Robotics · Nvidia Research
Knowledge-Aware Evolution for Task-Free Streaming Federated Continual Learning with Arbitrary Class Overlap
Jan 27, 2026Sixing Tan, Xianmin LiuFederated Learning Replay-Based Continual Learning
Faculty of Computing Harbin Institute of Technology
AIR: Analytic Imbalance Rectifier for Continual Learning
Aug 19, 2024Di Fang, Yinan Zhu, Zhiping Lin +3Class-Incremental Learning Imbalanced Classification
School of Future Technology, South China University of Technology, Guangzhou, China · Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, China

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ALER: Adaptive Learnable Experience Rewriting for Reinforcement Learning

Oleg Shchendrigin, Egor Cherepanov, Aleksandr I. Panov, Alexey K. Kovalev

Innopolis University, Innopolis, Russia · MIRIAI, Moscow, Russia · Cognitive AI Systems Lab, Moscow, Russia

Prioritized Experience Replay Offline Reinforcement Learning Maze Task Recurrent State

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In partially observable reinforcement learning (RL), a later observation can make stored information obsolete or change what it implies for the next decision. Memory architectures and benchmarks for RL mostly test retention, the ability to keep information unchanged until it is needed. We formalize two further requirements. Rewriting sets the decision-relevant content to a value independent of the old one, and experience fusion transforms the old content by a rule that a later observation specifies. For tasks built from such updates, we count the memory states that a solution needs, and several baselines reach their lowest success rates on compositions that need more states. We introduce ALER (Adaptive Learnable Experience Rewriting), an agent that pairs an LSTM with a slot memory. An independently addressed Gumbel-Softmax write that concentrates its weight on one slot overwrites that slot, and a learned gate fuses the retrieved content with the recurrent state before the policy and value heads. We also introduce Rune-Mazes, three environments in which rune observations invert, cancel, reset, or repeat updates of a hidden cue under vector and pixel observations. Against seven baselines, ALER reaches a success rate of at least

0.82

in all sixteen Endless T-Maze configurations and at least

0.99

on all five Rune T-Maze compositions, and it has the highest mean success rate on four-branch Rune Multi-Corridor with an Invert rune. On pixel-based Rune MiniGrid Memory, it has a higher mean success rate than PPO-LSTM in eight of ten configurations. Project page: https://quartz-admirer.github.io/ALER-Adaptive-Learnable-Experience-Rewriting/.

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