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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 9
Approximate Hamming Convolution via Rectangular Matrix Multiplication
We study $(1 \pm ε)$-approximate text-to-pattern Hamming distance: given a length-$N$ pattern and a length-$2N$ text, compute the Hamming distance at every alignment to relative error $ε$.Beneath the Surface: What We Overlook When We Talk About Agent Evolution
Agent harness evolution enables recursive self-improvement (RSI) without updating model weights.Online Learning with Ordered Experts (via Two-point Feedback)
We study adversarial online learning with expert recommendations in a totally ordered action space, where the experts' recommendations may change and be reordered arbitrarily.Real-Time Event-Based LED Tracking and Pose Estimation with PWM-Encoded Markers
Event cameras are neuromorphic vision sensors with pixels that independently and asynchronously respond to brightness changes at microsecond resolution, supporting state estimation under rapid…MEMOIR: A Training-Free Memory Lifecycle for Long-Horizon LLM Agents
Long-horizon LLM agents require memory systems that preserve useful information across sessions and retrieve it when needed.TRACEMARK: Editor-Aware Watermarking for User Attribution in Text-Guided Image Editing
An image editing service records which user requests each edit, but the edited image itself does not contain this account information.Redacting Personal Data: A Speed and Accuracy Comparison of Regex, Presidio and Hybrid Designs
Many enterprise projects now pass free text to large language models (LLMs), and that text often contains personally identifiable information (PII) such as names, phone numbers, email addresses…Measuring the Marginal Value of Verifier-Based RL Beyond Supervised Fine-Tuning
Reinforcement learning from verifiable rewards (RLVR) is usually evaluated as an alternative to supervised fine-tuning (SFT), or as a stage that follows it, with the implicit assumption that the RL…Beyond Instruction Override: Benchmarking Indirect Prompt Injection with Task-Tampering Attacks
Indirect prompt-injection (IPI) benchmarks predominantly test planted instructions that redirect a tool-using agent toward an attacker-chosen task.Projection-Free Gradient Tracking Neurodynamic for Distributed Nonnegative Sparse Optimization
This paper proposes a continuous-time, projection-free neurodynamic system based on gradient tracking for distributed nonnegative sparse optimization.Neural Image Compression with Internal-External Prior Fusion and Alignment
Existing context models for learned image com- pression rely primarily on internal priors from the current image, overlooking common patterns and typical textures shared across natural images.WaSP: Wasserstein Data Synthesis Pipeline for Solver-Free Operator Learning
Neural operators offer fast surrogates for solving PDEs, but training them typically requires expensive input-solution pairs.UniGADD: Universal Generator-Agnostic Deepfake Detector
In this paper, we introduce Universal Generator-Agnostic Deepfake Detector (UniGADD), a novel method that employs supervised learning to achieve high accuracy on known deepfake generators, while…Generator-Aligned Reward Modeling with Target-Aware Bounded Optimization for Visual Generation
Post-training aims to enhance desired attributes in visual generative models while preserving their general generation capabilities.What the Middleman Delivers: Answer Behavior, Tool Permissions, and Billed Usage in LLM API Relays
Third-party application programming interface (API) relays offer access to large language models (LLMs), often at lower prices.GraspBench: Execution-Aware Cross-Robot Evaluation of 6-DoF Grasp Generation in MuJoCo
Modern 6-DoF grasp generators are often evaluated using grasp scores, dataset-level metrics, or single-robot demonstrations, yet proposal quality alone does not determine whether a grasp is…Don't Prompt Your Agents. Equip Them: Skillware as a Modular Standard for Sovereign, Auditable, and Deterministic Capability Execution for Logical Systems
Current autonomous logical systems rely on a fragile assumption: that language models should dynamically write code, guess API payloads, and memorize operational constraints through prompt…PharmAgents2: Towards Autonomous End-to-End Drug Discovery
Drug discovery requires continuous scientific decision-making across a vast research space.English Calibration Erodes Lithuanian in Expert-Pruned Mixture-of-Experts Language Models
Expert pruning compresses Mixture-of-Experts (MoE) language models by removing the experts that a calibration set marks as unimportant.Joint Flexible Beamforming, Resource Allocation, and Task Buffering for Movable-Antenna Enabled MEC Systems
The proliferation of computation-intensive applications, such as generative artificial intelligence and low-altitude economy services, demands mobile edge computing (MEC) systems that are both…
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