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Machine Learning
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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 97
Finite-step statistical mechanics of scale-invariant learning: spectral equations of state and curvature transport
Stationary learning admits an ideal-gas description under restrictive noise assumptions.Measured or Real? When Model-Derived Measurements Can Be Corrected or Compared
Numbers computed from trained models, such as an example's difficulty or a model's benchmark lead, change with seed and prompt.Detecting Brain Cancer Progression Through Signatures of Wearable Accelerometry Data
Glioblastoma and other high-grade gliomas (HGG) have a poor prognosis and are associated with progressive functional decline.Learning from Relative Action Credit for Escaping Local Minima
Reinforcement learning holds the promise of robots that learn manipulation skills from interaction alone, without pretrained priors or demonstration data.Integral Probability Boundaries
Bounds based on Integral Probability Metrics (IPMs) are ubiquitous in machine learning and statistics, appearing, e.g., in generalization, alignment, fairness, and privacy.Measuring Deep Learning Performance - An Empirical Study of Performance Distributions Across Architectures and Tasks
Non-determinism in deep learning algorithm design and implementation leads to performance variation, meaning model performance is not a single value, but rather a distribution.Efficient Deep Gaussian Process Surrogates via Mini-Batch Latent MAP Estimation
Deep Gaussian processes (DGPs) are flexible surrogate models for computer experiments with nonstationary response surfaces, but inference over their latent representations remains computationally…Conformal Predictive Distributions for Contextual Order Fulfillment Optimization
Ship-to-home fulfillment requires a retailer to select a fulfillment location and carrier before the delivery time is known.Cooperative EV Charging Assignment Using Multi-Agent Reinforcement Learning: A Comparison of QMIX and Independent Q-Learning Under Urban Traffic Uncertainty
The allocation of electric vehicles to public charging stations is increasingly constrained by the fact that several heterogeneous facilities often serve the same stream of requests while observing…Progressive-Observation Physical-Layer Fingerprinting for Efficient Open-Set Ethernet Authentication
Physical-layer fingerprinting (PLF) has emerged as a promising authentication approach for Internet of Things devices.Neural Compression of Long ADMM Trajectory for Multiparametric Quadratic Program
Solving large-scale multiparametric quadratic programs (mpQPs) in real time often requires thousands of iterative optimization updates, creating a major computational bottleneck in model predictive…Interpretable Feature Discovery from Unstructured Data Using LLMs and Statistical Choice Models
Feature extraction from unstructured data typically relies on opaque embeddings unsuited to interpretable decision-making.CADENCE: Distributional Next-Transaction Forecasting for Business Cash-Flow Underwriting
Recurring cash flows are the backbone of cash-flow underwriting: they separate durable revenue from one-off deposits, expose standing obligations, and ultimately determine ability to pay.Dynamic Merging Mutually-Distilled Multi-View Networks for RGB-Event-based Representation Learning
Multi-modal fusion algorithms combining conventional frame-based cameras and event cameras have recently attracted substantial research attention.Inverse modelling of a laser-plasma accelerator
The electron beams of a laser-plasma accelerator depend non-linearly on the laser and gas settings.Dream to Assist: Intent-Conditioned World Models for Shared Vehicle Control
Assistive agents in shared-control settings face a dual challenge: acting proactively to align with the human's intentions while remaining legible enough for the human to comprehend and fluently…AdaTutor: Adaptive Tutoring through Pedagogical Strategy Selection
Effective tutoring requires determining not only what information to provide, but also which form of assistance to deliver.Video World Models Need Predictable Latents
Video world models trained on large-scale robot data promise a safe and scalable approach for learning and evaluating policies that act in the physical world.Exploring perceptual straightness in learned visual representations
Humans have been shown to use a "straightened" encoding to represent the natural visual world as it evolves in time (Hénaff et al. 2019).AT-AT: Automatic Tool Optimization from Agent Traces
Efforts to improve LLM-based agents typically focus on modifying the agent itself, yet success also depends on the environment in which an agent acts.