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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 41
CoRTeC: A Differentially Private Release for Synthetic Tabular Data, Decodable by Any Generator
The records that could train the most useful models, such as a hospital's patient files, are often the ones an institution cannot share.Prism: Bidirectional Self-Teaching for Unified Multimodal Models
Unified Multimodal Models (UMMs) aim to support visual understanding and generation within a single model.Today's Work, Tomorrow's Workforce: Incentivizing Learning in AI-Assisted Work
At work, people develop skills through experience: novices acquire skills by completing tasks, while experts retain theirs through continued practice.Flexible Intensities Matter: A Comprehensive Re-evaluation of Hawkes Processes and Neural Temporal Point Processes
Temporal point processes (TPPs) are the canonical framework for event sequence data, with applications spanning seismology, social media, and electronic health records.PMRecBench: A Benchmark for Personalization in Recommendation Agents under Multimodal Queries
On Web platforms for shopping and entertainment, recommendation agents under multimodal queries aim to deliver personalized recommendations that satisfy users' visually specified requirements and…Traffic-VL: Reinforced Vision-Language Models for Generalizable End-to-End Traffic Signal Control
Existing traffic signal control methods typically rely on structured traffic states produced by dedicated perception pipelines.FlashRelight: Portrait Video Relighting with Dynamic Lighting
Portrait video relighting aims to modify the illumination of a portrait video while preserving photorealism and temporal stability.EEGDash Corpus: A Training-Ready Public Corpus for EEG Foundation Models
Foundation models for electroencephalography (EEG) are pretrained on tens of thousands of hours of recordings, and their accuracy grows with that amount.Keeping Fuzzers on Duty: Repairing Fuzzing Build Breakages in Continuous Open-Source Fuzzing
Continuous fuzzing platforms such as OSS-Fuzz provide sustained security testing for open-source projects, but long-term build breakages reduce security coverage and waste infrastructure resources.Vortex-Induced Torque in Grasping Soft Objects: Influence of Geometry and Pneumatic Parameters
Vortex grippers are commonly integrated into automated systems for handling objects with complex geometries in packaging, sorting, and assembling.Estimating the Volume of a Union of Convex Bodies
The \textit{Union Volume Estimation problem}, i.e. yielding an $(\varepsilon, δ)$-approximation of the volume of the union of convex bodies, is a classical problem in computational geometry and…Training-Free Character-Length Control in Summarization with Diffusion Language Models
Summarization with a fixed character length is important for tasks such as headline and article preview generation, where text must fit an exact space.Give Up to Get More: Priors, Not Policies, Govern Test-Time Compute Allocation
When many inputs share a budget of repeated attempts by a large language model (LLM), a common rule gives harder inputs more.Reassessing Dataset Quality and Fine-Tuning Practices for Vulnerability Detection on PrimeVul dataset
Recent studies report promising results from supervised fine-tuning of pre-trained code language models for automated vulnerability detection on benchmarks such as PrimeVul.Corralling AI Risks with Grassroots Contracts
AI's inflection point is a fountain of alarming risks.NanoKV: High-Ratio KV Cache Compression for Autoregressive Video Generation
Autoregressive video models rely on historical key-value (KV) caches to preserve scene consistency over extended rollouts, making KV storage and repeated attention over history a growing memory and…UniLoop: Unified Loop Closure Detection from Retrieval to Geometric Verification and Relative Pose Estimation
Loop closure detection conventionally cascades separate models for global retrieval, geometric verification, and relative pose estimation, leading to redundant computation and disconnected visual…Does Context Compression Preserve Refusal Alignment?
Context compression reduces inference cost by encoding inputs into compact representations while preserving semantic content.LegalEvolver: Agentic Legal Judgment Prediction via Rubric-Guided Self-Evolution
As LLM-based agents develop, they have been increasingly applied in the legal domain.From hydrological laws to catchment models: A process-based model matches deep-learning accuracy on three continents
Dooge asked whether hydrology has laws at the catchment scale.
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