AI & Machine Learning · Computer Science & AI
Machine Learning
The newest papers in Machine Learning that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
The newest 5,000 papers, from 12 October 2026 to 5 November 2026: 5,000 arXiv preprints.
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Newest papers, page 75
Continuous-Action World Models: Learning Cross-Embodiment Spatiotemporal Dynamics Priors
We introduce Continuous-Action World Models (CoAWM), a framework for learning cross-embodiment spatiotemporal dynamics priors that support robot action generation across embodiments and execution…SCARL: Sequence Confidence-Aligned Reinforcement Learning
Reinforcement learning with verifiable rewards (RLVR) improves language-model reasoning by scoring sampled responses with a rule-based verifier and reinforcing those that pass.OCCAMS: A Multi-Task Learning-Based Investigation of the CMB Power Spectra
How many latent variables are needed to fit the cosmic microwave background (CMB) temperature and polarisation power spectra when a neural network is given no cosmological model, and to what extent…IMPACT: Inverter-Informed Multimodal Learning for Photovoltaic Generation Forecasting
This work develops a physics-informed multimodal deep learning framework for 10- to 110-minute-ahead probabilistic photovoltaic power forecasting.NECA: Neighbor Event Curve Augmentation for Multi-Horizon ICU Deterioration Prediction
Early prediction of ICU organ dysfunction events supports timely clinical monitoring and intervention, but estimating short-term organ-specific risk from early ICU records remains challenging due to…Uncertainty-aware Feedback Loop Diagnosis: integrating reinforcement learning and conformal prediction for reliable wafer defect classification
Semiconductor manufacturing is a complex, multi-step process that requires both high precision and low operating costs.Adaptive search with path-constrained mobile sensors using multi-arm bandits
We study a constrained sequential decision problem for detecting regions of interest from noisy online measurements collected by a team of energy-constrained mobile sensors.Soil Moisture Estimation in Precision Agriculture: A Knowledge Distillation Approach
Accurate soil moisture estimation is critical for precision agriculture, influencing irrigation, fertilization, and harvesting strategies.A Pretrained Model for Bayesian Filtering in Heterogeneous Dynamical Systems
Filtering has not yet had its foundation-model moment: state estimation is still dominated either by online Bayesian filtering algorithms that require known dy- namics as inputs, or by…Framework-Conditional Open Materials Generation
Theoretical predictions of novel materials rely on a variety of techniques, from data-mining-based ion substitution methods to fully de novo generative models.Learning developmental dynamics from lineage context
A central goal of biology is to predict the dynamics of multicellular systems.Reinforcement learning for control of partial differential equations
Controlling dynamical systems governed by partial differential equations (PDEs) remains a challenging task in scientific computing, owing to high-dimensional state spaces, distributed actuation…Rural Readiness: Domain Generalization with Adversarially Chosen Domains
Predictive models trained at well-resourced data-rich institutions often fail when deployed in new populations.Preserving Utility in Continual LLM Unlearning via Orthogonal Projections
Unlearning concerns the task of removing the influence of a sensitive portion of the training data, such as protected, copyrighted or private text, from a model without retraining it from scratch.The Precision Wall: An Optimizer-Dependent Boundary for Optimization under Power-Law Measurement Spectra
In low-rank matrix sensing of a rank-$D$ factor $U^\ast \in \mathbb{R}^{V \times D}$, replacing isotropic Gaussian designs with power-law measurement covariance $Σ= \mathrm{diag}(j^{-s})_{j=1}^V$…Fast and accurate neural triage decoding of ultra-high-rate quantum LDPC codes
Quantum error correction is essential for fault-tolerant quantum computing.Numerical Integration on Bounded Domains via Learned Reflected Diffusions
We study high-dimensional integration on bounded convex domains.Discovering Interpretable Acoustic Features in Autoregressive Voice-Cloning TTS Models
Voice-cloning TTS models synthesize an unseen speaker's voice from brief speech prompts, but it remains unclear which acoustic properties they represent and use.How I Aligned Your Model: Scaling Up Multilingual Safety Training with Templates
Safety alignment for Large Language Models is heavily focused on English with limited multilingual representation, particularly damaging low-resource language performance.NEOPIC: A Neural Operator Framework for Particle-based Kinetic Plasma Simulations
We introduce NEOPIC, a framework for learning the field operator in particle-based methods applied to kinetic plasma simulations.