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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 28
ME^2FDiff: Multiscale Expert Enhancing Feature Diffusion in Residual Network for Brain Tumor Segmentation
Automated segmentation of post-treatment glioma from MRI is essential for accurate diagnosis and treatment planning, yet remains difficult.Noncrossing is All You Need: Beyond Identical Delay Functions in Online Matching with Delays on General Metrics
Online optimization with delays has emerged as a powerful paradigm with numerous applica- tions, including matching, caching, server management, network design, and set cover.How Well Can Large Language Models Impersonate Individual Authors? A Comparative Evaluation
This study investigates the authorship impersonation capacity of six widely used large language models (LLMs): Gemini 3 Pro, Claude Opus, GPT 5.2, GPT 5.2 Pro, DeepSeek 3.2, and Grok 4.1 Fast.Hotplug Coded Caching: Embedding the YMA and Interference Elimination Schemes via Reed--Muller Codes
In the hotplug coded caching model, $K$ users fill their caches of size $M$ as a function of $N$ files, but only an unknown subset of $A<K$ users is active in the delivery phase.Optimizing Recourse Under Predictive Multiplicity
Algorithmic recourse identifies modifications that can change an unfavorable model prediction into a favorable one.Closed-Loop Adaptive Sampling on a Generative Ocean Model
Adaptive sampling can substantially improve the value of sparse ocean observations by directing mobile robots toward measurements that are most informative for an evolving environment.Sublinear Metric Distortion for Matching
We study metric distortion in one-sided matching.Discovering like a scientist: Literature-informed dimensionless learning for physical closure of data-driven equations
Data-driven methods can recover compact equations, yet the physical dependence of their coefficients across operating conditions often remains unresolved.Timing is Everything: Inferring Temporal Membership in Continually Updated Models
Continual model updating has become a common practice in the deployment of machine learning systems.Unsupervised Neural Operators for Rotating Relativistic Stars: High-Fidelity Equation of State Inference and Pulsar Spin Evolution at Scale
Observed populations of rotating neutron stars~(NSs) with millisecond-order periods are powerful probes of fundamental physics.FlyHash for LLM Agent Memory: An Empirical Validation and a New Application
Large language model (LLM) agents increasingly rely on external memory stores to retain information across conversations, typically via dense vector embeddings searched with approximate…ZipDrift: Generating Multimodal Short-Horizon MPC Costs with One-Step Drifting Models
Short-horizon model predictive control (MPC) is fast but myopic.Near linear mixing of random-cluster Glauber dynamics on random regular graphs
We study the random-cluster model on locally treelike graphs at low temperatures.DARE: Difficulty Analysis for Repair Enhancement
LLM-based coding agents are primarily evaluated by their solve rates.Consistency Is Not Understanding: Orbit Audits for Neural Field Weight Readers
Recognizing visual content from neural-network weights requires separating functional information from arbitrary parameter coordinates.Item Representations Matter: Bridging Hard Semantic IDs and Soft Prototype Mixtures for Generative Retrieval
Modern recommender systems rely on generative retrieval techniques to predict the next item either as discrete codes or as a continuous vector.WayPOP: A Panoramic Open-Set Panoptic Tracking Benchmark
Holistic perception for autonomous agents requires reliably segmenting and associating scene elements across time and camera views, including objects outside a fixed semantic taxonomy.GREP: Grounding Generated Room Evaluation in Principles
Recent LLM-centric advances can generate attractive furnished rooms by selecting and arranging assets.Phonological Knowledge of Chinese Characters in Language Models
How much phonological knowledge do language models (LMs) possess about Chinese characters, and how is this knowledge represented and used?Matching the Training-Time Weight Rule in Inference-Time Expert Deactivation
Expert deactivation at inference time changes both token routing and expert weights, and its effect on performance depends on how these changes are implemented.
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