When Does Non-Uniform Replay Matter in Reinforcement Learning?
arXiv:2605.10236v3 Announce Type: replace-cross Abstract: Modern off-policy reinforcement learning algorithms often rely on simple uniform replay sampling and it remains…
Bridging Silicon and the Hippocampus: Algebro-Deterministic Memory “VaCoAl” as a Substrate for Vector-HaSH and TEM
arXiv:2605.15652v2 Announce Type: replace-cross Abstract: Vector-HaSH and the Tolman-Eichenbaum Machine propose the hippocampal-entorhinal circuit factorizes content from a grid-cell scaffold,…
WriteSAE: Sparse Autoencoders for Recurrent State
arXiv:2605.12770v3 Announce Type: replace-cross Abstract: We introduce WriteSAE, the first sparse autoencoder that decomposes and edits the matrix cache write…
Overcoming the Intrinsic Performance Limitations of MEMS IMU via Diffusion-Based Generative Learning
arXiv:2605.16391v1 Announce Type: cross Abstract: Inertial measurement units (IMUs) are fundamental sensing components in multi-source integrated navigation systems, and their…
$boldsymbol{f}$-OPD: Stabilizing Long-Horizon On-Policy Distillation with Freshness-Aware Control
arXiv:2605.17862v1 Announce Type: cross Abstract: Scaling on-policy distillation (OPD) for large language models (LLMs) confronts a fundamental tension: asynchronous execution…
Vision Transformer-Conditioned UNet for Domain-Adaptive Semantic Segmentation
arXiv:2605.16393v1 Announce Type: cross Abstract: Semantic segmentation is essential for analysing anatomical features in biomedical research, yet a performance gap…
DeepSlide: From Artifacts to Presentation Delivery
arXiv:2605.15202v1 Announce Type: new Abstract: Presentations are a primary medium for scholarly communication, yet most AI slide generators optimize the…
TFGN: Task-Free, Replay-Free Continual Pre-Training Without Catastrophic Forgetting at LLM Scale
arXiv:2605.15053v2 Announce Type: replace-cross Abstract: Continually pre-training a large language model on heterogeneous text domains, without replay or task labels,…
CLOVER: Closed-Loop Value Estimation and Ranking for End-to-End Autonomous Driving Planning
arXiv:2605.15120v2 Announce Type: replace-cross Abstract: End-to-end autonomous driving planners are commonly trained by imitating a single logged trajectory, yet evaluated…
Looped SSMs: Depth-Recurrence and Input Reshaping for Time Series Classification
arXiv:2605.16048v1 Announce Type: cross Abstract: State Space Models (SSMs) are inherently recurrent along the sequence dimension, yet depth-recurrence – reusing…