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.
Get the few papers worth your time in Machine Learning every morning.
Follow Machine Learning and ReadSearch reads its new papers each day, then brings you the few worth reading, each with its key finding in a sentence.
Newest papers, page 54
Personalized Rollout Allocation for Federated LQR Policy Optimization under Heterogeneous Process Noise
We study federated model-free learning of a common linear quadratic regulator (LQR) gain under a limited uplink communication budget, with clients that share dynamics and costs but experience…Adversarial Robustness Is Not Zero-Day Generalization: A Controlled Evaluation of Flow-Based Intrusion Detectors on Corrected CIC-IDS2017
Synthetic variants of known attacks, including feature-space adversarial perturbations, are sometimes used as stand-ins for unseen ("zero-day") attacks when evaluating machine-learning network…Adversarial robustness does not entail human-aligned categorization
Adversarial training can improve some forms of correspondence between artificial and biological vision, but whether robust classifiers acquire human-aligned classification behavior remains unclear.Uncertainty Aware Quality-Diversity Optimization For Offline Biological Sequence Design
Designing sequences such as nucleic acids and proteins with desired properties is a fundamental challenge in biology.Pricing Today, Shaping Tomorrow: Contextual Dynamic Pricing in Purchase-Driven Evolving Systems
Across diverse markets, it is important for firms to balance attracting customers with managing operational conditions, such as workloads and delivery times.Beyond Synthesis Conditions: Linking In-situ Growth Dynamics to Carbon Nanotube Forest Properties through Multimodal Machine Learning
Machine learning for chemical vapor deposition (CVD) of carbon nanotubes (CNTs) has largely mapped static synthesis conditions to final properties, implicitly treating these conditions as a complete…Learning hidden-state dynamics from unpaired snapshots with lift-project SDEs
Many systems are observed only through unpaired snapshots, with population samples available at each time point but no correspondence between samples at different times.PeptSol: A Translational Benchmark for Protected-Peptide Solubility in Drug Manufacturing
Liquid-phase peptide synthesis (LPPS) offers a scalable route to peptide manufacturing, but route development still depends on empirical solvent screens because each protected intermediate must be…Old Is Not False: Valid-Time Memory for Interactive Video World Models
Interactive video world models draw each frame from a memory bank of earlier frames stamped with their capture times.Model-Based Learning of Latent Euclidean Embedding from Relational Data
Visualizing and interpreting the dependence structure in relational data often benefits from geometric representations via low-dimensional Euclidean embeddings.Sampling Design and Confidence Tubes for Integral Curves on Riemannian Manifolds
We estimate the integral curve of an unknown vector field from noisy tangent vector field on a known compact Riemannian manifold.The Tangled Web They Weave: Exploring Neural Representations with Directed Simplicial Complexes
Understanding how artificial neural networks (ANNs) represent and combine features internally is a central challenge in mechanistic interpretability.Unbiased Low-Rank Approximation for Repeated Matrix-Vector Multiplication: Stability and Optimal Sampling
Replacing the matrix in an iteration with random low-rank matrices can reduce the cost of matrix-vector multiplication.Tight Stochastic Sequential Covers for General VC Classes with Unknown i.i.d. Features
We study hybrid online learning with stochastic features and adversarial labels when the feature distribution is unknown.Crop Mapping Evaluation under Sampling Bias
Government agencies use crop maps to estimate production, monitor food security, and set agricultural policy.Private Uniform Language Generation
We study uniform language generation under approximate differential privacy.Streaming Virtual Metrology via Lightweight Adaptation under Temporal Distribution Shifts
Virtual metrology (VM) aims to estimate costly or delayed metrology variables from heterogeneous sensor signals and in-line measurements, and it acts as a critical component of semiconductor…ODC: Orthogonal Drift Correction for Improved Text-to-Image Semantic Alignment at Inference
Text-to-image models have achieved remarkable success in generating high-quality images from textual descriptions.AdKnob: Ad Intensity Control and Labeling for LLM-Native Advertising
Large language model (LLM)-native advertising has emerged as a viable monetization channel as LLM service providers seek sustainable revenue streams.Answer Correction with Verifiable Rewards: A Gemma-Family Study of Multi-View Driving QA
Multi-camera driving question answering provides a discrete test of vision-language models, but post-training gains can reflect changed selected answers or improved answer extraction.