AI & Machine Learning · Computer Science & AI
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 93
QD-PINN:A Physics-Informed Neural Network Approach to Bayesian Quickest Detection in High-Dimensional Diffusions
Quickest detection problems (QDPs) arise in a wide range of applications.Keeping Inference in the Radio: Design and Measurement of a Spiking Accelerator for mmWave ISAC Activity Recognition
Integrated sensing and communication allows wireless networks to recognize human activity from the channel estimates that the receiver computes anyway.Follow the Gradient: Tracing Safety Degradation Back to Training Data
Fine-tuning Large Language Models (LLMs) on instruction data can quietly erode their safety, even when no training example looks harmful.Regression Functions as Fields on Covariate Space: Evolution Equations, the Hessian, and Identification
For each time $t$, the regression function $m_t(x)=E[Y_t\mid X_t=x]$ of an outcome on contemporaneous covariates can be regarded as a field on covariate space.A note on data-efficient finetuning of vision foundation models
Adapting foundation models to a new task within or beyond the training domain is the de facto standard for building specialized machine learning models.Orthogonal and Parametrized Multi-Attribute Steering of LLMs
Activation steering offers an effective and efficient way to modify an LLM's behavior at inference time.The Structure Gap: When More Data Cannot Replace Structured Reasoning
A persistent belief in modern AI is that sufficiently large learners trained on sufficiently much data can make explicit domain knowledge optional.GTFormer: A Syntax-Free Graph Network Alternative to Transformers for 8192$\times$ Length Extrapolation in Linear Time
Self-attention mechanisms have established the Transformer as the dominant backbone across natural language processing, source code intelligence, and automated theorem proving.GroundControl: Satellite-Conditioned Multi-View Diffusion for Reconstruction-Free Novel View Synthesis
Multi-view or video diffusion models have recently emerged as state-of-the-art approaches for novel-view synthesis from sparse image collections.Collective Dynamics of Self-Reinforcement: How Cross-Task Coupling Drives Policy Collapse in Unsupervised RLVR
Label-free reinforcement learning with verifiable rewards (RLVR) rewards a language model for agreeing with its own majority vote.When uncertainty quantification fails: structural vulnerabilities and corrections for selective prediction under clinical class imbalance
Selective prediction systems improve the safety of clinical artificial intelligence by deferring ambiguous cases to human experts while automating high-confidence decisions.Pneuma: A Large-Scale Real-World Time Series Benchmark for Commercial Aircraft Predictive Maintenance
Predictive maintenance is vital for commercial aviation, yet progress remains hindered by the lack of public, large-scale real-world datasets.Gym-Anything-RT: Scaling Real-Time Environments for Vision-Language Agents
AI agents have made substantial progress in domains where they have a non-trivial amount of time to deliberate between actions, such as mathematics, software engineering, and performing tasks on…LCM-Promo: An LLM-Based Uplift Model for Promotion Allocation
We present LCM-Promo, an LLM-based uplift model for promotion allocation.Spectral Braids: A Topological Descriptor for Dynamic Directed Networks
Eigenvalues are a workhorse of graph machine learning: spectral clustering, spectral graph neural networks, and graph kernels all summarize a network by the eigenvalues of a matrix.Zero-Shot Multimodal Event Spotting in Soccer Broadcasts
Automatic soccer event spotting supports highlight generation, video indexing, and sports analytics, but existing methods depend on large annotated datasets and soccer-specific training.Understanding the limits of latent world models
World models are widely proposed as core components for enabling agents to reason over long temporal and spatial horizons.GAS-PFN: Graph-Aware Spatiotemporal Prior-Data Fitted Networks for Zero-Shot Traffic Forecasting
Traffic forecasting requires modeling complex temporal dynamics and the spatial dependencies imposed by road topology.EnvSched: Environment-Aware Scheduling for Rollout-Efficient Agent Reinforcement Learning
As executable environments for language agents scale, generating and verifying their rollouts becomes increasingly expensive.MuonGS: Pretraining LLMs with Relaxed Weight-Norm Control
Weight decay and explicit weight-norm constraints improve optimizer performance in language model pretraining, yet a unified understanding of why such control helps and how much is needed remains…