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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 154
From Code Generator to Engineering Companion: A Plant-aware Agent for PLC Programming
Programmable Logic Controller (PLC) coding remains a manual, IDE-centric task that demands constant context switching between documentation, project files, and code editors.Coincidence-Maximizing Customer Clustering Using Smart Meter Data
Electricity distribution planning depends on peak-demand coincidence within customer groups, yet similarity-based clustering of smart-meter data does not optimize it directly.Foreword: Pre-Generation Prediction and Characterisation of LLM Test Failures using the Jacobian Lens
Testing LLM-based software is expensive: each input needs several sampled responses, each judged by a costly oracle.Offline Makes Online Better: Calibrated Cache Compression for Video Generation
Token merging is an effective approach to reducing KV-cache memory consumption in autoregressive video generation by clustering temporally redundant tokens and retaining only a small set of…Adaptive Pullback: Reweighting Supervision at Penalty Jumps in On-Policy Distillation
On-policy distillation (OPD) supervises student-generated responses using sampled-token student-teacher log-ratios.Attractive Faces Skew Text-to-Image Reward Models and Leaderboards
Human preference is now central to the evaluation, guidance, finetuning, and ranking of text-to-image models.Reframing Object-Centric Reinforcement Learning: From Absolute to Relative Representations
Object-centric reinforcement learning agents typically receive each object's position in a fixed global frame, even though their decisions usually depend on where objects are relative to one another.Parameter-Efficient Adaptation of Time Series Foundation Models for Electrical Load Forecasting
Accurate electrical load forecasting supports power-system operation across countries, regions, cities, and buildings, but repeated development of target-specific models is costly.JAXbounce: A Continuous-Control Pong-Like Benchmark for Active Inference Beyond Low Dimensional Environments
We introduce JAXbounce, a continuous control pong-like benchmark designed to evaluate active inference beyond discrete, low dimensional environments.ExeBench-FHD: Addressing Fidelity Issues in Decompiler Evaluation
ExeBench is one of the most widely used benchmarks for evaluating LLM-based decompilers.Norm-optimal model order reduction in reproducing kernel Hilbert spaces
We consider the problem of model order reduction (MOR) in reproducing kernel Hilbert spaces (RKHSs).TPO: Tri-level Distributionally Robust Learning for OOD Direct Preference Optimization
Direct Preference Optimization (DPO) minimizes empirical risk over observed preference comparisons, implicitly assuming that the training preference distribution matches the deployment preference…Convergent Performance, Divergent Mechanisms in LoRA-Adapted Vision Foundation Models for Brain MRI
Adapting Vision Foundation Models (VFMs) to medical imaging via LoRA has become standard practice, yet model selection is guided almost entirely by downstream task metrics, treating backbones with…Geometry-Aware Block Selection for Sparse Variational Gaussian Processes
Sparse variational Gaussian processes (SVGPs) are a widely used, principled approach to scalable Gaussian process modelling.Local Work, Global Progress: A Convergence Theory of AI Agent Collaboration
Teams of large language model (LLM) agents are increasingly applied to complex tasks, but their collaboration protocols are mostly designed empirically, without convergence guarantees.Adaptive Replay Refinement: Allocating Test-Time Compute Between Revision and Resampling
Test-time scaling allocates additional inference compute to refining existing solutions or generating new ones.Learning Normal Coordinates on Riemannian Manifolds with Flow Charts
Riemannian manifolds are powerful models for problems with non-Euclidean structure.Recommending Bacterial Cultivation Conditions from 16S rRNA
Recommending bacterial cultivation conditions from sequence data is a challenging structured problem characterized by missing standardized benchmarks and limited use of sequence structure.Debiased Prior-Data Fitted Networks for Amortized Bayesian Semi-Parametric Inference
Prior-data fitted networks (PFNs) have recently gained popularity as an end-to-end approach to amortized Bayesian inference.Disclosure Begets Disclosure: A Self-Reinforcing Privacy Loop in LLM Agents with Persistent Memory
Large language model (LLM) agents increasingly use persistent memory to personalize responses, and personal attributes in this memory pose a privacy risk if exposed.