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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 223
Does Morphological Correctness Matter for Tokenization? A Scrambled Control Study in Tagalog
Typology-aware tokenizers are motivated by the claim that segmentation which respects morpheme boundaries preserves information that frequency-driven segmentation destroys.Time-partitioning Gaussian Process Mixture Model
Nonstationarity and heterogeneous dynamics are common in financial and macroeconomic time series.SNOAR: Self-training with Noise filtering, Observation adding, and Remixing for Speech Denoising Without Clean References
Unsupervised speech denoising methods such as MixIT and noisy-target training can be trained directly on noisy recordings, avoiding the sim-to-real gap of synthetic training data, but remain well…Long-Context Drafting Does Not Require Long-Context Drafters
Speculative decoding pairs a cheap drafter with parallel verification against the target.SHRED: Self-Play for Heterogeneous Road-Users without Expert Demonstrations
Realistic traffic simulation and autonomous planning both depend on modeling interactions among heterogeneous road users whose dynamics, constraints, and behaviors differ fundamentally.Clinically Interpretable Biological Age Estimation Using CatBoost and SHAP with Continuous and Categorical Features from NHANES
Biological age (BA) captures inter-individual variation in physiological aging beyond chronological age (CA).Machine-learning-based neutrino-event generation constrained by experimental measurements
We present a generative surrogate for charged-current \(ν_μ\)-nucleus scattering that can be calibrated to measured differential cross sections without event-level experimental samples.CogDrift-4D: Hierarchical Multimodal Modeling of Temporal Behavioral Decay for MCI Detection
Early detection of mild cognitive impairment remains a critical bottleneck in dementia care, demanding scalable tools capable of capturing subtle behavioral decay.Pixels to Tokens: Token Space Efficient Active Learning for Low-Budget Semantic Segmentation
While foundation models and vision transformers (ViTs) have redefined visual representations, current active learning (AL) strategies for these backbones largely operate at the patch or region…Do Emergent Misalignment Models Share a Circuit?
Fine-tuning language models on narrowly defined harmful tasks can induce emergent misalignment (EM) across unrelated domains.Learning Warm Starts for the Simplex Method from Measured Solver Cost
Learned warm starts for the simplex method build starting bases using predictions of which variables will be basic at optimality.Flexible Doubly Robust Proximal Causal Inference for Censored Outcomes
Estimating causal effects on right-censored time-to-event outcomes is challenging under unmeasured confounding.Stochastic Gradient Descent: A Nonlinear Time Series Perspective
This paper investigates the statistical behavior of Stochastic Gradient Descent (SGD) with constant step size under the framework of iterated random functions.Wrong Votes, Right Gradients: Why Majority-Vote Rewards Track Verifiable RL
Reinforcement learning with self-generated labels, such as majority vote over a model's own samples, often recovers most of the gain of training with verifiable rewards.TGrasp6D: Task-Informed Vision-Language Priors and Pose Refinement enable Zero-Shot Task-Oriented 6DoF Grasping
Task-Oriented Grasping (TOG) has emerged as an important skill for purposeful robotic manipulation.Sign Betting for Misspecified Regression: Variance Adaptivity and Optimal Approximation
We study bounded regression under model misspecification, evaluating a function $f$ by its $L_1(P_X)$ distance to the conditional mean $η(x)=\mathbb{E}[Y\mid X=x]$, rather than the standard…Task-Centric Multimodal Learning for Cognitive Impairment Detection
Dementia affects millions of older adults worldwide, yet early detection remains difficult outside clinical settings.Replicable Dueling Bandits
Dueling bandits choose each comparison based on earlier noisy outcomes, so two runs on the same preferences can compare different pairs.Recursive Offline Distillation via Entropy Gain Sampling and Answer Mixing
Distillation of reasoning chains from Large Language Models (LLMs) into their smaller siblings is a standard training approach.Defining and Generating Compositional Structure
Compositional structure is pervasive in nature and across scales: atoms combine into molecules, molecules into cells, and cells into organisms, while further compositional hierarchies appear within…