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 220
A Two-Level Clinical Novelty Prioritization Framework for Disease Trajectories Discovered from Longitudinal Electronic Health Records
Graph-based analysis of electronic health records (EHRs) yields disease-trajectory catalogs, but structural support does not establish semantic novelty.Bayesian Learning to Select Fair Classifiers
Evaluations of classifiers (AI or human or agents) often assume a batch setting in which every agent produces labels on every example in a test set, which can be expensive or impractical in many…VASPO: Self-Distillation with Privileged Value Estimation
On-policy self-distillation provides dense supervision for reasoning models via a privileged self-teacher.The Physics Is the Network: Fast, Training-Free Neural Emulation
Neural emulation need not require learning a substitute for known physics.ActiveEvidence: Decision-Focused Evidence Graphs with Verifiable Acquisition Gaps
A multimodal agent must decide whether visual evidence is worth acquiring, which candidate or resolution to query, and when further interaction can no longer change its decision.Generative Representation Learning for Scalable Latent Tokenization
We introduce an approach for self-supervised representation learning designed to be used as a tokenizer for generative modeling.Revisiting Simple Baselines for Relational Deep Learning
Relational deep learning has emerged as a powerful paradigm for learning end-to-end predictive models over relational databases by representing them as temporal heterogeneous graphs.PrismaCoder: Pushing the Boundaries of Open Multimodal Code Intelligence through Decomposed Rubric Synthesis
Multimodal code intelligence connects the symbolic world of programs with the visual world their execution creates.Detection of Potato Plant Leaf Diseases using Convolutional Neural Networks
Potato is an important food-security crop in Ethiopia, but its production is affected by foliar diseases, particularly early blight and late blight.Recovering Reliable Supervision via Critique-Guided On-Policy Distillation
On-policy distillation (OPD) trains a student model on its own rollouts with token-level supervision from a teacher, assuming that the teacher can reach a correct answer from any prefix the student…One Task, Many Interfaces: Simple Cross-Interface Consistency Training Improves LLM Agent Robustness
Post-training binds the competence of an LLM agent to the interface it was trained on.Latent Compaction with Test-Time Training
Long contexts enlarge key--value (KV) caches, increasing memory use and attention costs during generation.Learnable Hodge-Laplacian Driven Mixture of Experts for Steady-PDE Surrogates on Coarse Unstructured Meshes
Current approaches for steady partial differential equations surrogate models on unstructured meshes apply a single mixing mechanism to the whole solution.Continuum Attention
We introduce Continuum Attention (CA), a causal Transformer attention operator that replaces discrete key and value lookup with integration over a continuous, piecewise linear memory curve.Price of Anarchy of First-Price Auctions in Agentic Markets
An agentic market is a decentralized serving-time market where AI agents bid to claim each user prompt.Your Transformer Is Secretly Elastic
Scaling up transformers has produced models with broad capabilities, deployed across heterogeneous hardware and fluctuating workloads.Co-Evolving Acting and Forecasting for Language Agents
Training language agents is bottlenecked by the high cost of long-horizon rollouts, yet standard agentic reinforcement learning (RL) learns only from a terminal scalar reward, leaving the…Modeling and Understanding Neural Weights of Humanoid Policies with Diffusion
Recent advances in robot learning have driven rapid progress in humanoid control, enabling increasingly agile behaviors in the real world.Hierarchical Residual Policy Learning for Real-World Mobile Manipulation with Sparse Human Guidance
Mobile Manipulation (MoMa) is a cornerstone of autonomous robotic systems, yet real-world fine-tuning remains a formidable challenge because of high-dimensional action spaces and intricate coupling…A polylogarithmic bound for list replicability
Zhang [Zha26] recently posted a manuscript announcing that the list-replicability number of every class of $M\ge 2$ binary concepts on $N\ge 2$ domain points is $O(\log^2 M\log N)$, which would be…