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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 3
Selective Retrieval Routing for Multi-Violation Knowledge Graph Repair
Knowledge graphs often contain missing or inconsistent facts that undermine the applications built on them.Slide to Report: Continuous Reporting Symptom-Specific Cybersickness in VR
Cybersickness is often assessed during VR exposure through discrete overall sickness, which cannot capture specific symptoms or their changes over time.GreedTok is a Constant-Factor Approximation for Partition-Cover Tokenization
GreedTok (Lim, Tan, Choo and Lauw, NeurIPS 2025) builds a tokenizer vocabulary greedily for the partition-cover objective: choose $k$ tokens so as to maximize the number of adjacent character pairs…AtlasULP: Domain-aware Universal Link Prediction via Relation Atlas
Link prediction (LP) is a widely applied task in graph learning.Constant-Factor Approximations for the Biased Traveling Salesman Problem and Its Path Variant
The metric traveling salesman problem (TSP) is a fundamental problem in combinatorial optimization that asks for a minimum-cost Hamiltonian cycle in a complete undirected graph with $N$ vertices…From What Is Used to What Is Missing: Rethinking Dynamic Rank in LoRA
Parameter-efficient fine-tuning with LoRA is governed by rank, which controls parameter budget and locally accessible task updates.MIKU: Material Invariance and Knowledge Unification for PBR Generation
High-quality material generation for physically based rendering (PBR) remains challenging because datasets and synthesis pipelines lack standardized representations.Constant-Factor Approximation Algorithms for Weighted Budgeted Multisensor Sweep Coverage
Sweep coverage requires each point of interest (PoI) to be revisited by some mobile sensor at least once during every sweep period, and it underlies persistent patrolling, environmental monitoring…Acoustic Anomaly Detection for Early Identification of Drill Jamming
In the context of Industry 4.0, predictive maintenance is essential to minimize unplanned downtime and ensure operational safety.Design of a Speech Enhancement-Based Deep Semantic Autoencoder for Wireless Communications
Speech communication plays a crucial role in the Internet of Things and autonomous networks.Asymptotic-Preserving Tensor Neural Networks for 3D High-Field Kinetic Equations with Applications to Uncertainty Quantification
Kinetic equations in the high-field regime describe particle transport dominated by electric-field acceleration and collisional relaxation.Test-Time Self-Play: Scaling without a Verifier
Test-time scaling methods spend additional compute at deployment to improve a large language model's performance on a hard target problem.A Simple Discrete Newton Method for the Quickest Transshipment Problem
The quickest transshipment problem is a problem defined in a dynamic network with multiple sources and multiple sinks.EnvOpt: Automated Optimization for Agent Environments
An LLM agent's cost and success depend on its model, its harness, and its environment.Design of Multi-UAV Cooperative Deep Semantic Autoencoders for Communication Networks
Driven by the rapid development of the low-altitude economy, Uncrewed Aerial Vehicle (UAV) networks have become increasingly important for executing tasks such as search, rescue, and monitoring.When Scores Conflict with Preferences: Pre-Alignment Diagnosis and Adaptive Correction of Constraint Drift in DPO
Direct Preference Optimization (DPO) is increasingly used in settings where pairwise preferences coexist with pointwise criteria such as response length, answer correctness, or safety scores.Designing with Cinematic Language: An Intent-Driven Approach to Human-AI Video Clip Co-Creation
Generative video models have made video creation more accessible, yet creators still struggle to translate high-level narrative intentions into coherent cinematic expressions.Adversarial Multiplicity: Cherry-Picked Models and the Limits of Disclosure
Predictive multiplicity -- where similarly accurate models disagree on individual predictions -- can be leveraged to optimize secondary metrics (e.g., fairness) without loss in predictive performance.FFMT: Frequency-Factorized Multi-Rate Tokenization for Music-to-Dance Generation
Dance motion combines slowly varying body configurations with rapid local movements.Breaking the Modality Barrier: Multimodal Fusion With Missing Modalities for Cybersickness Prediction
Cybersickness is a major barrier to comfortable VR use, and reliable prediction often requires multiple physiological and behavioral sensors.
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