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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.
Topics in Computer Science & AI
AI & Machine Learning
Systems & Networks
Theory & Algorithms
Security & Cryptography
Applied & Human-Centered
- Human-Computer Interaction1,000 papers
- Software Engineering1,448 papers
- Robotics4,418 papers
- Information Retrieval979 papers
- Programming Languages81 papers
- Multimedia192 papers
- Sound553 papers
- Graphics278 papers
- Digital Libraries83 papers
- Mathematical Software26 papers
- Symbolic Computation38 papers
- Social & Information Networks172 papers
Newest papers
Using Transformers for Teaching and Learning via Symbolic Distillation of Neural A-life Agents
Neural networks controlling behavior of A-life agents can evolve over multiple generations.TriAttention: Unified Sparse Mixed-Precision Attention for Long-Context LLM Inference
Sparsity and quantization reduce the cost of attention by skipping interactions and lowering the precision of those retained.Evolutionary Adaptive Neighborhood Learning: A Genetic Algorithm for Instance-Dependent k Optimization in Nearest Neighbor Classification
The number of neighbours k is the central hyperparameter of the k-nearest neighbour (k-NN) classifier and is usually selected globally through cross-validation or evolutionary search.Reweighting is not Harmless: Understanding the Role of Dataset Characteristics
Reweighting is a widely used pre-processing method for promoting discrimination-free model behavior by assigning different weights to data points during model training.An Empirical Study of Reinforcement Learning for Keypoint Positioning of Deformable Linear Objects
Deformable linear object (DLO) manipulation is challenging because high-dimensional configurations, nonlinear contact dynamics, and diverse material and geometric properties produce a broad range of…HyFlash: A Prefix-Memory Prior for On-Device Speculative Decoding
Parallel block drafting accelerates speculative decoding by predicting multiple future positions in a single backbone pass, but on-device deployment constrains both drafter capacity and context…Energy Measurement and Optimization of TinyML in Resource-Constrained Embedded Systems: A Systematic Mapping Study
The rapid expansion of the Internet of Things (IoT) has increased the volume of data generated at the network edge, where many devices operate under severe memory, processing, and energy constraints.How Deep is the Signal? Time-Context up to 30 Years for Colorectal Cancer Prediction in a Primary-Care EHR Model
EHR foundation models read medical events within a fixed context window, and long context has so far been measured only in tokens.CRISP: Constraint-Resolved Interactions between Subsystems for Predictive Whole-Body Cooperation
This paper presents a layered control framework that recasts high-dimensional system dynamics as a composition of dynamically interconnected subsystems, with dynamic dual-arm manipulation on the…Satisficing as competitive Bayesian weighting: a minimal model of goal-directed choice under an unattained target
Animals and humans often do not maximize; they act relative to goals (aspiration levels) that are frequently not yet met.VREgo: Consumer VR Headsets for Learning Robot Manipulation from Egocentric Demonstrations
VREgo trains manipulation policies from demonstrations recorded on consumer VR headsets; we instantiate it with EgoKit on one such headset, the PICO 4 Ultra.Efficient Diffusion Policy Fine Tuning with Latent Noise Representation Bridging
Pre-trained diffusion and flow policies have emerged as powerful backbones for robotics, yet adapting them to novel data via reinforcement learning (RL) remains computationally expensive, sample…Graph Neural Networks for Resource Allocation in Integrated Sensing and Communication
In vehicular integrated sensing and communication (ISAC) networks, each service-provider vehicle uses a limited power budget to serve multiple sensing targets and communication receivers.Scenario Augmentation for Rare Financial Events via Multimodal Latent Diffusion
Extreme market movements are scarce, heterogeneous, and difficult to learn from imbalanced historical data.Encoding and Propagation of Grammatical Number in Large Language Models
Sparse autoencoders (SAEs) have become an increasingly popular means of translating Large Language Model (LLM) hidden state vectors into a human-comprehensible list of features or symbols.How Should Agents See Code? Rethinking Code Representations for Agentic Software Engineering
LLM agents are increasingly used for repository-level software engineering tasks.Neural Realized Measures: Forecast-Supervised Intraday Aggregation for Volatility Forecasting
High-frequency volatility forecasting typically separates measurement from prediction: intraday observations are first compressed into a daily realized measure using a fixed aggregation rule, and…Patch-Based Generalized Neural Texture Upscaling
We propose a lightweight neural texture upscaling method.How do Transformers Perform Low-Level Control In-Context?
One of the remarkable abilities of Transformer-based neural networks is in-context learning.An Ordering Optimization for Fruit-Vegetable in High-Density Environment based on Genetic Algorithm
This paper presents a robotic harvesting method that combines RGB-D fruit localization, GA-based harvest ordering, and waypoint-based robot motion in dense and unstructured crop environments.
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