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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 19
Optimal Competitive Ratios for Chasing Convex Functions with Quadratic Growth
Chasing convex function has attracted much attention in recent years, which can be formulated as a game between a learner and an adversary.Spatiotemporal Dynamics-Aware Industrial Anomaly Detection and Reasoning
Industrial Anomaly Detection (IAD) is a long-established problem that aims to detect defects in industrial products during manufacturing for quality control.TerraMesh-Masks: Open-Vocabulary Segmentation for Earth Observation
Open-vocabulary segmentation (OVS) enables models to segment a variety of concepts specified in natural language, removing the need for fixed label sets and fine-tuning.DictLLM: Post-training Compression of Large Language Model with Dictionary Kernels
Efficient deployment of large language models (LLMs) on mobile devices requires balancing performance with compute and memory constraints.Linguistic boundaries emerge from pressure-constrained processing dynamics
Human cognition organizes continuous experience into bounded units while maintaining continuity across them.MUSS: A Multi-scale and Sequence-based Model for Single-cell Gene Regulation
Modeling gene regulation in single cells requires jointly representing DNA sequence, chromatin accessibility, and gene expression across regulatory scales.Value or Attention: Investigating Layer-wise Relevance Propagation for Graph Attention Networks
Graph Attention Networks (GATs) are increasingly used in domains where scientists need to read a model's reasoning, from medicine to materials science, yet the routing they learn remains opaque to…SAE Interprets MoE: Sparse AutoEncoders Reveal That MoE Experts Exhibit Human-Interpretable Fine-Grained Specialization
Mixture-of-Experts (MoE) models route each token to a few of many experts, yet what an individual expert is responsible for remains unsettled.ATHAAR: A Medieval Scientific Arabic Manuscript Dataset for Handwritten Text Recognition
Despite recent progress in handwritten text recognition, medieval Arabic scientific manuscripts remain an open challenge for current vision-language models (VLMs) due to cursive ligatures, variable…Gabor Gabor: E-Gaborformer, a Strictly Causal Speech Recognizer with Gabor-Dictionary Convolutions and Delta-Rule Memory
Real-time voice agents need a speech recognizer that never waits for future audio and whose memory per call does not grow with the length of the call.Gradient Boosting for Efficient Rank Discovery in Tensor Network Kernel Machines
Tensor network kernel machines (TNKMs) combine nonlinear features with low-rank tensor representations to model complex relationships efficiently.PersonaAgent: Retrieval-Augmented Transaction Anomaly Scoring with Refreshable Multi-Entity Persona Memory
In large-scale payment networks, entities (card, merchant, etc.) and their interactions play a key role in transaction anomaly detection.National-scale mapping of tree species composition in Switzerland from high-resolution aerial imagery and multimodal data
Tree-species composition shapes forest productivity and how forests respond to climate disturbances such as drought, windthrow and insect outbreaks.STEP: Spatiotemporal Training with Explicit Prediction for Perceptive Humanoid Locomotion
For perceptive humanoid locomotion, the relevance of terrain geometry depends on the robot's body state and how both evolve under its actions.Towards Practical 20 kbps Generative Video Compression via Adaptive Tokenization and Entropy Modeling
Video compression at ultra-low bitrates remains challenging due to the loss of perceptually important details under limited bit budgets.An Integrated Open-Source Stack for Vision-Based Autonomous Navigation of Wheeled Rovers
Vision-based rover autonomy requires integrating perception, localization, planning and platform-specific control under limited sensing and computing resources.Reinforcing End-to-End Autonomous Driving Safety via Negative-Aware Planning in a Unified World-Action Model
World-action models (WAMs) jointly model future traffic states and driving actions for end-to-end autonomous driving in intelligent transportation systems.Identifying Neural Dynamics Using Nonlinear Interventional State Space Models
State-space models (SSMs) recover low-dimensional latent dynamics from high-dimensional observations, but latents are generally not identifiable from observational data alone.Sum-of-Squares Refutation Implies Planted Recovery for Semirandom CSPs
We give a $n^{O(\ell)}$-time algorithm for solving semirandom planted instances of a $k$-ary Boolean constraint satisfaction problem (CSP) with $m \gtrsim \left(\frac{n}{\ell}\right)^{k/2} \ell \…Create Your Own Work Stack: Deploying Self-hosted AI and Tooling in a Tech Startup
Self-hosting AI is often presented as a way to reduce inference costs and increase control, but deployment introduces its own costs.
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