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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 48
Perceived Trust and Transparency in AI-Altered vs. Human-Written LinkedIn Posts
People increasingly draft a social media post themselves and then let an AI model refine it (AI-altered), a common but understudied middle case between fully human-written and fully AI-generated…Fingerprinting the Dispatchers behind Distributed Model Extraction
API distillation campaigns try to hide model-stealing traffic by splitting requests across thousands of load-balanced accounts, which standard content classifiers often miss.Where Search Agents Go Off the Rails: Graph-Grounded Step-Level Verification
Search-augmented reasoning systems can reach correct answers while making errors in intermediate steps.CardioDrift: Automatic Cardiac Motion Tracking on a 3D Atlas Mesh via Shape-aware Coherent Point Drift with Slice Shift Correction
Automatic cardiac motion tracking from cine cardiac magnetic resonance (CMR) imaging is essential for quantifying myocardial motion abnormalities associated with cardiovascular disease.Polynomial-Time Differentially Private Synthetic Graph Release with Nearly-Linear Additive Error
We give a polynomial-time $(\varepsilon, δ)$-edge-differentially private algorithm that releases a synthetic graph approximately preserving all cut values of a nonnegative weighted input graph $G$.Which Physical Tactile Cues Matter for Contact-Rich Imitation Learning? A Controlled Real-Robot Study
Vision-based tactile sensors capture multiple aspects of physical interaction within a single image stream, including contact appearance, geometry, indentation depth, and tangential deformation.AgentTrustCI: Build-Time Policy, Grounding, and Trajectory Tests for Java LLM Agents
Infrastructure security does not establish whether an LLM agent selected an allowed tool, grounded its answer in tool output, or followed a required workflow.Self-Directed Apple Tasting
We study the classical apple-tasting setting, a partial feedback model in which the learner observes the true label only when it predicts $1$.Do unlearning algorithms learn the right features?
Machine unlearning is commonly evaluated with standard post-deletion metrics that compare an unlearned model to one retrained on the remaining data.SecureGARD: Dynamic Ontology-Guided Governance for Secure Tool-Using LLM Agents
Tool-using large language model (LLM) agents translate model outputs into consequential actions, turning indirect prompt injection into an execution-security problem.The Online $k$-Taxi Problem Is Competitive on All Metrics
The online $k$-taxi problem is a natural generalization of the $k$-server problem: $k$ taxis must serve a sequence of requests in a metric space.Sekai: Incremental Event Memory for Generalized Reasoning Video Segmentation
Online reasoning video segmentation (Online RVS) requires a model to segment query-referred objects as a video streams in, using only the frames observed so far.LifeVal: Evaluating AI Model Performance on Personalized Agentic Consumer Tasks
We introduce LifeVal, a benchmark evaluating AI model performance on personalized agentic consumer tasks.Don't Replace, Complement: A Detector-Agnostic Subspace Signal for Near-OOD Detection
Post-hoc out-of-distribution (OOD) detection is mature on far-OOD yet remains weak on near-OOD.Cognitive and Behavioural Effects of Haptic Feedback for ROV Teleoperation in Hazardous Environments
Teleoperating a Remotely Operated Vehicle (ROV) in complex underwater environments presents unique challenges.You Know What You Will Like: People Predict Their Own Ratings Better Than Recommender Systems
Recommender systems usually learn what people want from what they have done.PINR-ESI: Physics-Informed Self-Supervised Implicit Neural Representation Framework for EEG Extended-Source Imaging
EEG extended-source imaging aims to localize active cortical regions and characterize their spatial extent, yet supervised inverse networks typically depend on synthetic EEG-source pairs and may be…Agent-Driven Generative Priors for Pathology Image Synthesis and Segmentation
Deep learning methods for pathology are constrained by the limited availability and high cost of large-scale pixel-level annotations.When to Ask for Help: Uncertainty-Triggered Aerial Refinement for Off-Road Navigation
Heterogeneous air-ground teams can use aerial sensing to address the limited range and viewpoint of ground-vehicle sensors, but deciding when the UGV needs assistance and what information the UAV…Where It Breaks: Diagnosing Perception, Memory, and Decision Failures of a Vision-Language Agent in Pac-Man
Training an agent to play Pac-Man with only up, down, left and right actions raises a basic question: when performance is poor, what should be improved?
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