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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 86
SpatialVec: A Unified Representation Learning Framework for Geospatial Objects with Boundary-Aware Sampling
Spatial representation learning is essential for Geospatial Artificial Intelligence (GeoAI) applications, enabling machine learning models to capture the geometry, location, and spatial…Repulsive Population Policy Gradients for Behaviorally Diverse Reinforcement Learning
The goal of Quality-Diversity Reinforcement Learning (QD-RL) is to find a population of high-performing policies that solve a decision-making problem in diverse ways.Property-Based Testing for Robust Softmax and Cross-Entropy
A recent paper of Barron et. al. (2026) identified two numerical issues with the softmax and cross-entropy functions in virtually all standard machine learning libraries (e.g., PyTorch and JAX).Simulated petrological labels enable probabilistic mineralogy prediction from whole-rock geochemistry
Modal mineralogy, the mineral identities and abundances in rocks, guides geological studies and industrial resource extraction.Learning atomic interactions for the thermodynamics of liquid mixtures
Predictive models for activity coefficients, which describe the non-ideality of liquid mixtures, are foundational for process design and optimization.High-Fidelity Aerostructural Dataset of Transonic Wings in Cruise Conditions
Recent advances in machine learning (ML) have the potential to substantially accelerate aircraft wing design, a process that has traditionally required extensive high-fidelity simulation and design…Whole-Body Humanoid Control via Stochastic Motion Tokenization
While velocity-commanded RL policies are effective for controlling quadrupeds, they are a limited interface for humanoids that need to perform complex whole-body motions.A Simple Presentation of Robust Membership Inference Attacks
In a membership inference attack, an attacker is given the data of a particular individual, and tries to determine if that individual was included in a particular dataset, given some kind of…Split Federated Unlearning
Split federated learning (SFL) combines partitioned model execution with federated aggregation to support collaborative learning across distributed Web and edge environments.CoHARL: Co-Evolving Agent Policies and Executable Harnesses with Reinforcement Learning
Large language model (LLM) agents interact with their environments through executable harnesses that govern tool use and feedback.Underdamped Anchored Langevin Dynamics
Classical Langevin Monte Carlo algorithms, such as the unadjusted Langevin algorithm (ULA), are based on discretization schemes of the overdamped Langevin dynamics and are widely used for sampling…Proposing Better Rollouts for On-Policy Distillation
On-policy distillation (OPD) improves language-model post-training by letting the student learn from its own sampled trajectories under teacher supervision, aligning the training process with…Second-order Sinkhorn Geometry and $\sqrt{n}$-Inference
The Sinkhorn divergence, a debiased form of entropic optimal transport, has been widely used in various scientific disciplines due to its computational and statistical tractability.Algorithmics for Graphical Separation Criteria
Statistical graphical models are representations of the dependences between the components of a random vector.PRISM: Pathology Reliability In Scarce-label Medicine. A Tile-level Benchmark of Pathology Foundation Models
Pathology foundation models are typically benchmarked on classification performance at full label availability and on in-distribution test sets, while calibration, behavior at low label budgets, and…Folding Attention Biases into Keys Makes Compacted KV Caches Run on Standard Kernels
Attention Matching (AM) compacts a KV cache by keeping some keys per head, refitting their values and adding a bias to each kept key's logit.Causal Localization of Evidence Effects in Transformers
Can controlled symbolic inputs reveal attention heads that influence a language model's decisions from natural language evidence?RoboAuto: Autonomous Robot Program Search through Multi-Level Physical Understanding
Recently, LLM-based autonomous agents have shown strong capabilities in iteratively generating, evaluating, and refining executable solutions.NextEval: An Agent-Based Solver and Benchmark for Derivative-Free Optimization
Derivative-free optimization (DFO) addresses problems where derivatives are unavailable or costly to obtain.Holomorphic Cauchy Networks for Efficient Stationary Tail Computation in High-Dimensional Reflected Brownian Motions
Stationary tail computation for high-dimensional reflected Brownian motions (RBMs) remains computationally challenging.