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The newest 5,000 papers, from 12 October 2026 to 5 November 2026: 5,000 arXiv preprints.
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Newest papers, page 89
Evaluating AlphaEarth Embeddings for Crop Classification: Separability, Temporal Dynamics, and Cross-Regional Transferability
Earth Observation (EO)-based agricultural monitoring is shifting from pixel-level spectral analysis toward representation-driven modeling, yet systematic evaluation of learned representations…HorizON: A Multi-Horizon Deep Operator Network for Property Prediction of Organic Battery Stacks
Transition-metal-based batteries rely on critical elements such as lithium, cobalt, and nickel.Intrinsic Information-Theoretic Analysis of ReLU Nets
Mutual information (MI) is fundamental to representation-learning analysis in deep networks, but in high dimensions MI estimators depend on hyperparameters whose bias often dominates the signal.Sample-and-Score: Surrogate-Guided Coordinated Spatial Reuse in IEEE 802.11 Networks
Coordinated spatial reuse (Co-SR) in IEEE 802.11bn increases area throughput through simultaneous transmissions, yet the combinatorial configuration space makes real-time optimization challenging.Tail Cues, Principal Corrections: Plug-and-Play Rectification for Open-Set Test-Time Adaptation
Open-Set Test-Time Adaptation (OSTTA) operates on non-stationary target streams where covariate and semantic shifts coexist.RAG-CSI: Global Local Retrieval via Joint State and Dynamics Matching for CSI Prediction
Channel state information (CSI) prediction forecasts future channel states from historical observations, supporting transceiver design and resource allocation with reduced measurement overhead.Hyperparameter and Neural Architecture Search via Evolutionary Optimization for Reinforcement Learning: HPNAS-RL
In this study, we propose a dual-branch evolutionary framework that simultaneously performs Neural Architecture Search (NAS) and Hyperparameter Optimization (HPO) for Reinforcement Learning (RL) in…PREEN: Exemplar-Based Color Style Transfer with Smartphone Editor Presets
We present PREEN (Preset Regression via an Exemplar-based Editor Network), which casts color style transfer as regression onto the 29 parameters of a deterministic image editor.HiLo-RD: Cross-Budget Self-Distillation for Masked Diffusion Language Models
We propose HiLo-RD (High-to-Low Budget Representation Distillation) to improve masked diffusion language models (MDLMs) under a limited generation budget.Provenance Signatures for Low Rank Adaptations of Image Diffusion Models
Diffusion models have revolutionized the generation of realistic artificial images.Gaussian Process Bandits for Constraint Black Box Lever Optimization
Optimizing discrete allocation weights across competing segments of a shared budget is a fundamental challenge in resource-constrained, sequential decision-making environments.TDLM: Adaptive Temporal Integration for Diffusion Language Models
Masked diffusion language models repeatedly compute representations for unresolved tokens, but conventional denoisers do not explicitly retain these representations for reuse across steps.Algorithmic Monoculture in Machine Learning-based Site-Specific Fertilizer Recommendation
Machine learning recommendations are often evaluated one model at a time, despite deployment across interconnected decision makers.DCKV: Learned Transform Coding of the Prompt KV Cache in Hybrid Language Models
Hybrid language models keep a key-value (KV) cache only in their few full-attention layers, but this cache is still the part of a prompt's state that grows with the prompt and that must be stored or…Live-OPSD: On-Policy Self-Distillation for Proactive Streaming Large Video Models
Streaming multimodal assistants must make response decisions while events are still unfolding.On the VC Dimension of Autoregressive Linear Threshold Functions
Linear threshold functions (LTFs) are a canonical class of Boolean predictors.GNN-Guided Network Reduction for Centralized Urban Traffic Routing
We consider the centralized traffic routing (CTR) problem, where a central planner assigns routes to origin-destination (OD) vehicle flows to minimize congestion-dependent segment cost.Advancement or Acceleration? How Data Curation Improves LLM Training
While data curation is widely credited with improving large language model training, a basic question remains unresolved: does curation expand what a model can ultimately learn, or merely reach the…Quantum Evolution Kernel for Node-Attributed Graphs
We present a novel approach to embed node-attributed graphs onto neutral-atom quantum computers, and propose an application to digit recognition.CaLLM: Continual Adaptation of LLMs via Non-Parametric Adapter Routing
Continual adaptation of large language models (LLMs) to evolving task distributions while mitigating catastrophic forgetting remains an open problem.