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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 85
Self-Supervised Doppler-Guided RF Odometry
Radio-frequency (RF) sensing enables robot ego-motion estimation in darkness, smoke, and fog, yet RF odometry remains challenging because multipath and moving reflectors make cross-frame matching…Blind Spots: Where Small Language Models Fall Behind Frontier Models on Terminal Tasks
Small language models (SLMs) offer an attractive alternative to frontier models (FMs) because they can be deployed with lower cost and latency.Formal Specifications with Data-Driven Signal Analysis
Developing analog and hybrid systems requires substantial domain knowledge that is hard to articulate in a formal specification; without additional effort, this domain knowledge is also inaccessible…Fed-IGTD: A federated learning-based framework for tabular-to-image encoding
Tabular-to-image encoding methods, which transform tabular data into image-like representations, have shown promising results in predictive tasks.Assessing feature scorer results on high-dimensional datasets with t-SNE
While vast literature on high-dimensional data visualization is available, there are not many works regarding the visualization of feature scorers and their results.The Search for Statistical Indistinguishability Between Real and Fake Images
Images produced by generative models appear strikingly similar to real ones.Representation Complexity Along Learning Trajectories: Trading Width for Precision and Time
What computational role does overparameterisation play during learning?MCCL: Training Pytorch models across a fleet of Macs at Skywalker Sound
Skywalker Sound, a premier audio post-production facility, operates more than 200 M4 Max Mac Studios on a 10Gb Ethernet network.FairSplit: Decomposing the Embedding Space for Fair Classification
Fair classification faces a twofold challenge: maintaining high classification accuracy while limiting reliance on sensitive information.Exponential-Nemytskii Neural Operators: Learning Field Evolution Across Step Sizes
In variable-step operator learning, agreement at observed step sizes does not by itself determine predictions at other temporal resolutions.Modular Bayesian Foundation Models: Bayesian time series encoders for OOD detection, routing and forecasting
Industrial systems continuously generate time series that vary in sampling frequency, scale, dynamics, and operating regime.Reinforcement Learning for the Game of Balatro: A Fast Simulator and Two-Policy Training Approach
Balatro, a 2024 roguelike deckbuilder, presents three difficulties that have historically derailed reinforcement learning methods: a 3,000-action state-dependent action space, horizons of several…BASILISC: Bayesian Alignment of Siamese-Integrated Latents for Inferring Single-cell Correspondence
Single-cell assays study the genome one cell at a time.When Does Closed-Loop Curriculum Adaptation Help GRPO? An Analysis on Countdown
Reinforcement fine-tuning has become an effective post-training paradigm for improving the reasoning ability of large language models, but it remains sample-inefficient when the training…Tabular foundation models are not a shortcut to calibrated clinical risk prediction: a pre-registered simulation against the true risk
Tabular foundation models are pretrained networks that predict risk from a table without fitting a model.Closed Gates Leak: Decomposing Adjacent-Layer Cancellation in Gated Language Models
In transformer language models with gated multilayer perceptrons (MLPs), adjacent layers write partly against each other into the residual stream.CausalGrade: Evidence-Guided Causal Graph Scoring with Jev
Evaluating the structural quality of candidate causal graphs when the true causal structure is unknown is an important problem in applying causal discovery results.CalibCause: A Quality-Gated, Interpretable and Calibrated Deep Learning Framework for Diabetic Retinopathy Grading
Most deep learning systems for diabetic retinopathy (DR) grading are evaluated on a single data source, with limited evidence of cross-site generalisation, uncertainty calibration, and…Automatic Construction of Strong Simple Baselines
To rigorously establish the value of a novel deep learning method, it must be compared against appropriate baselines.FGSM Attack Transferability from Simulation to Quantum Hardware in Network Intrusion Detection
Quantum computers are now available through cloud platforms, and recent work has proposed using them to detect network intrusions.