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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 9
Data-driven discovery of intrinsic Lie point symmetries of differential equation systems
Discovering continuous symmetries directly from differential-equation data can reveal geometric structure for model reduction and scientific machine learning without symbolic determining equations…Understanding AI from the Inside: The State of Mechanistic Interpretability for AI Safety
Neural networks are likely to be among the most consequential artefacts in human history.Label-Wording Augmentation in a Typed-Decision Encoder: Gains on Unfamiliar Words, Not on Abbreviations or Codes
Typed-decision models score options that the caller supplies at request time, so their accuracy depends on label wording that the model's developer does not control.A Hidden Markov Preference Model for Online Prediction of Adversary Actions
A defender anticipating an attacker needs a probability distribution over the attacker's next action from information available before that action occurs.Unpacking the Compute Efficiency of Strong-to-Weak OPD against GRPO
On-policy distillation (OPD) trains a student on its own rollouts under a frozen teacher's per-token supervision.Adversarial Training with Large Step Sizes: Implicit Bias, Optimization, and Sharpness
Adversarial Training (AT) is an important method for improving model robustness.Towards interpreting any residual stream direction by scaling activation inversion
To interpret a direction in a language model's residual stream, we can look for text that strongly activates it.Same Behavior, Different Mechanism: What Finite Experiments Can Certify About Integrated Information
Interpretability, AI auditing and assessments of machine consciousness increasingly rest on mechanism-level quantities: functionals of a system's causal transition law that describe how it computes…XStack: A Benchmark for ML Repo Migration
ML code should run where researchers choose, not where it was first written.Scientist World: Grow a Research World for AI-Scientists
AI-Scientists arrived, but a world for them to grow in did not.User Embeddings are Superpositions of Interpretable Behavioral Modes
User embeddings are central components of modern recommendation, personalization, and behavioral modeling systems.Optimizing Recourse Under Predictive Multiplicity
Algorithmic recourse identifies modifications that can change an unfavorable model prediction into a favorable one.Timing is Everything: Inferring Temporal Membership in Continually Updated Models
Continual model updating has become a common practice in the deployment of machine learning systems.Unsupervised Neural Operators for Rotating Relativistic Stars: High-Fidelity Equation of State Inference and Pulsar Spin Evolution at Scale
Observed populations of rotating neutron stars~(NSs) with millisecond-order periods are powerful probes of fundamental physics.FlyHash for LLM Agent Memory: An Empirical Validation and a New Application
Large language model (LLM) agents increasingly rely on external memory stores to retain information across conversations, typically via dense vector embeddings searched with approximate…ZipDrift: Generating Multimodal Short-Horizon MPC Costs with One-Step Drifting Models
Short-horizon model predictive control (MPC) is fast but myopic.Item Representations Matter: Bridging Hard Semantic IDs and Soft Prototype Mixtures for Generative Retrieval
Modern recommender systems rely on generative retrieval techniques to predict the next item either as discrete codes or as a continuous vector.WayPOP: A Panoramic Open-Set Panoptic Tracking Benchmark
Holistic perception for autonomous agents requires reliably segmenting and associating scene elements across time and camera views, including objects outside a fixed semantic taxonomy.Autonomy and Coordination in Intelligent Manufacturing: A Recursive Autonomous Agent Framework
Intelligent production requires systems to make decisions and organize work according to production goals and operating conditions.Pathwise-Budgeted LLM Routing: Online Allocation with K-Bit Tail-Cost Learning
Firms using large language models under fixed budgets must decide which model to call and whether to retry a failed task.