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Computer Science & AI
Much of the new work in computer science and AI appears first as a preprint on arXiv. ReadSearch reads those listings every day, with papers OpenAlex files under the same subjects, and this page shows the newest it has, from machine learning and language to systems, theory and security.
The newest 1,000 papers, from 4 November 2026 to 5 November 2026: 1,000 arXiv preprints.
Newest papers, page 46
EPISTEME: Trustworthy Coding Agents Through Tool Call Intent
Coding agents change software through tool calls.Playing Soccer Like Humans Do: Learning Versatile and Agile Humanoid Soccer via Latent Motion Priors
Humanoid soccer requires a robot to seamlessly combine agile locomotion, ball manipulation, and impact-rich contact dynamics across a continuous, dynamic behavioral spectrum.One Scale, Four Texts: Gaps, Overlaps and Silent Repairs in Published Grading Schemes
Category systems often reach their users as text, and readers apply them with tacit repairs.Does Personality Persuade? Investigating Personality Trait Prompting and Persuasion in Large Language Models
Large language models (LLMs) can be prompted to express different personality profiles, but it remains unclear how reliably they do so or whether personality affects their persuasiveness.Finite-width shift of the edge of chaos in deep neural networks
Deep neural networks train best when they are initialised at the edge of chaos, the critical line in the plane of weight and bias variances on which the distance between two inputs neither grows nor…PatchCon: Patch-aware Weighted Supervised Contrastive Learning for Vulnerability Detection
Automated vulnerability detection is critical for securing modern software systems, yet existing learning-based approaches often treat functions as independent samples and underuse the supervision…Informing research priorities for distributed acoustic sensing: insights from a citizens' panel
This report presents findings from a Citizens' Panel convened by the SOUNDSCALE project (www.soundscale.ac.uk) to inform research priorities for distributed acoustic sensing (DAS).Signed, Sealed, Leaked: Trust Beyond Signature for MCP Toolchains
AI agents rely on third-party tools, such as Model Context Protocol (MCP) servers, whose publishers can be authenticated and whose execution can be restricted by runtime security policies.FOSCo-Net: Ego-centric Voxel Completion for Forest LiDAR Occlusions
Ground robots operating in temperate forests suffer from systematic LiDAR occlusions caused by tree trunks, creating persistent blind regions that degrade traversability estimation.Thermodynamics-Informed Learning Captures Hierarchical Hydrogen-Bond Networks in Deep Eutectic Solvents
Deep eutectic solvents (DESs) offer a tunable platform for lignocellulose refining, but their solvation behavior depends on multicomponent hydrogen-bond networks rather than individual constituent…BudgetSplat: Budget-Controllable Generalizable Gaussian Splatting
Feed-forward 3D Gaussian Splatting enables efficient generalizable novel view synthesis, but existing pixel-aligned methods often generate highly redundant Gaussian primitives, causing the final…SpikePose: Lightweight Video Human Pose Estimation
Efficient video human pose estimation must balance localisation accuracy, motion quality, and energy cost.A trust layer for fast pedestal-stability surrogates: calibrated error bars, out-of-distribution alarms and few-shot recalibration
Machine-learning surrogates of linear peeling-ballooning stability now run in milliseconds, but they are mostly deployed as point estimators: they do not say how wrong they may be, or when a query…The Behavioral Rate of Fine-Tuning: Compression as a Measure of Useful Information
Low-Rank Adaptation (LoRA) adapts a frozen language model through a compact learned update, making it a natural setting for asking how much information fine-tuning needs to write.Time-Division Multiplexing: The Operational Rhythm and Temporal Organization Layer of Digital Life
Continual agents must handle urgent interaction while retaining alternatives, replaying errors, and committing safe long-term changes.A Sub-$3^n$ Upper Bound on the Number of Stable Matchings
We study the problem of determining the maximum number of stable matchings.Verifier-Guided Self-Consistency: Test-Time Reasoning with Imperfect Generators and Verifiers
Large language models can solve many multi-step reasoning problems, but their reasoning remains brittle: plausible intermediate steps often lead to incorrect answers.Alternatives to Shallow Autoencoders for Collaborative Filtering
Collaborative filtering (CF) is a cornerstone of recommender systems and plays a relevant role in many modern applications.Constant-Time Dynamic Edge Coloring via Dynamic Splitting and LLL
We give a dynamic algorithm that maintains a near-optimal edge coloring in constant expected time per update.From Reconstruction to Imputation: Test-Time Optimization for Missing Time-Series Channels
Complete sensor-channel failures create a difficult form of time-series missingness: local interpolation is unavailable, and deploying a separately trained imputer for every failure pattern may be…
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