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 45
Sweep Less, Steer More: Using Activation Steering Geometry for Reduced Hyperparameter Search
Representation steering methods like difference-in-means (DIM) offer a lightweight approach to controlling LLM behavior, but their effectiveness varies widely across concepts, datasets, and layers…FedUDG: Federated Domain Generalization with Unlabeled Clients
Federated domain generalization (FDG) aims to learn models that generalize reliably to out-of-distribution (OOD) environments without centralizing client's data.Improved Sample Complexity Analysis For First Order Bilevel Reinforcement Learning
Bilevel reinforcement learning optimizes an upper-level objective through the policy response to a lower-level reinforcement learning problem.Abstention Spends Its Budget on Local Label Variance More Than on Novelty: Auditing Conformal Calibration and Selective Prediction under Molecular Scaffold Shift
Selective prediction with split conformal calibration promises a post-hoc fix for molecular property prediction: abstain on the least reliable compounds, ideally out-of-distribution chemistry, and…Write Facts the Way Models Read Them: Lifting the Two-Hop Curse
A language model that learns a new fact by fine-tuning can repeat it but cannot reason with it: taught that a person is a citizen of a new country, it still cannot say, without chain-of-thought, who…InformedXRD: Reproducible Benchmarks and Physics-Informed Evaluation for Powder Diffraction Symmetry Classification
Machine learning for powder diffraction (PXRD) symmetry classification is being trained at scale, yet the field lacks a common evaluation standard: papers report results on different subsets of…From Tool State to Scientific Action: Auditing Decision Provenance in Biomedical Research Agents
A scientific agent can give the same verdict while reading and citing different evidence.Learning Gradients of Homogeneous Functions
Homogeneous gradient functions have widespread significance, including applications in maximum energy subspace selection and retrieval problems.Generative Modeling with Continuous Flows: Sample Complexity of Flow Matching
Flow matching has emerged as a promising alternative to diffusion-based generative modeling, offering a continuous-time ordinary differential equation formulation with fast sampling and a simple…Finite-Time Online Sample Complexity for Conditional Diffusion Models
We study the finite-time training and sampling error of conditional diffusion models trained by online stochastic-gradient denoising score matching.Meta-memorization and memorization scaling laws in transformers
Larger transformers can memorize more data, with a capacity (in bits) that scales roughly linearly with the number of parameters.Beyond Validation Loss: Coverage and Reliability Dynamics in Robot Policy Pretraining
In modern robot learning, generative robot policies are first pretrained through supervised learning from demonstrations, then refined through reinforcement learning, supervised finetuning, or other…Principled Human-AI Collaboration in Agentic Workflows
Organizations adopting AI face the challenge of deciding which outputs can be released without human review while meeting the quality standards of human experts.Search-Aware On-Policy Self-Distillation with Sibling Alignment for Generative Recommendation
Generative recommendation retrieves items by autoregressively generating semantic IDs, typically via beam search.Autoencoder Based Deep Clustering of Point Clouds
Motivated by a problem in Generative Specification-Producing AIs (SPAIs), we focus on a problem of deep clustering of three-dimensional shapes specified by point clouds.When Does Sparse Routing Help? The Geometry of Expert Separation in Mixture of Experts
Sparse mixtures of experts combine multiple prediction models while evaluating only a small subset for each input.DyRadio: Spatiotemporal Diffusion for Dynamic Radio Map Reconstruction
Accurate radio map (RM) reconstruction is essential for environment-aware wireless networks.Halal-NeSyNet: Clause-Scoped Neuro-Symbolic Cross-Attention for Automated Food Ingredient Auditing and Risk-Aware Halal Logistics Triage
Verifying that a packaged food is Halal requires reading ingredient declarations and E-number additives before goods enter certified warehouses.Surrogate Losses for Fairness-Aware Classification: Fisher Consistency and Calibration
Fairness-aware classification seeks to balance predictive accuracy and fairness across demographic groups.Sonny-ENS: demystifying machine-learning ensemble weather forecasting
Every weather forecast is uncertain, and decisions from flood warnings to energy trading depend on how well that uncertainty is quantified.