A field on ReadSearch
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 37
RDT-3D: Resolution-Decoupled Training for High-Fidelity 3D Geometry Generation
High-fidelity 3D geometry generation requires maintaining global structural coherence alongside fine-grained surface details.PTQ4SAM3: Semantics-Preserving Post-Training Quantization for Segment Anything Model 3
Segment Anything Model 3 (SAM 3) can segment objects from text prompts and track them across video, but its memory and computation costs make deployment difficult.SafeStart: Mitigating the Overlooked Safety Cost of Active Expert Reduction in MoE LLM Serving
Mixture-of-Experts (MoE) language models send each token through a few of many expert subnetworks.Grounding in the Dark: Text-Only Training for Zero-Shot Video Temporal Localization
Video-LLMs are typically trained on paired video-text data for temporal tasks, yet collecting precise temporal annotations and training on large-scale video datasets are both costly.CARM: Conformal Adaptive Risk Masking for Reliable Scientific Super-Resolution
Deep learning-based super-resolution (SR) can reconstruct fine-scale Earth-observation fields from coarse observations, but reconstruction accuracy alone does not provide a calibrated rule for…Neural Stochastic Forecasting for Lateral Molecular Diffusion Simulations
Predicting the long-time diffusion of membrane proteins is challenging because molecular dynamics (MD) simulations are computationally expensive, while experimental single-particle tracking is often…Selective Prediction Intervals: Jointly Learning to Predict, Bound, and Abstain
Many high-stakes regression decisions ask three things of a model at once: a point estimate to act on, an interval that bounds the risk of acting, and the option to abstain when neither can be…Regret Bounds for Market Making with Persistent Orders
We study adversarial market making with orders that remain active until execution.DSRS: Teaching MLLMs to Perceive, Reason, and Segment in Complex Driving Scenes
Existing reasoning segmentation frameworks typically employ multimodal large language models (MLLMs) with broad world knowledge to extract semantics in a human-like manner and generate corresponding…A Layered View of LLM Support in Underwater Robotics
This extended abstract discusses a specific and, in our experience, practically relevant role for large language models (LLMs) in underwater robotics.FaCoDiff: Factor-Correlated Diffusion for Multivariate Probabilistic Forecasting
Multivariate probabilistic forecasting requires modeling cross-variable dependence alongside marginal uncertainty.Reasoning-Aware Cross-Modal Association Unlearning in Multimodal Large Reasoning Models
Multimodal large reasoning models (MLRMs) integrate visual inputs with textual and parametric knowledge, allowing sensitive information to be accessed through cross-modal associations during…AssameseLM-E2B: An Open-Weight Assamese Language Model for Efficient Consumer-Grade Deployment
While Large Language Models (LLMs) excel in high-resource languages, their performance often degrades in low-resource languages due to tokenization inefficiencies, generative instability, and…Network Intrusion Forensic Detection System with Explainable Artificial Intelligence and Digital Chain of Custody
Deploying an explainable intrusion detection model from a validated laboratory setting into a forensic workflow requires guarantees that benchmarks do not test: that the certified model is the exact…FireOPS: A Human-Centric Emergency Operations Platform
Volunteer fire brigades rely on fragmented alerting channels and radio plus paper for situational awareness, hindering a shared common operational picture (COP).Efficient Stable Word-RAM Simulation by Population Protocols
Population protocols model computation by indistinguishable agents interacting in uniformly random pairs, with unary inputs and outputs encoded by state counts.Chiron: Cache Management Empowered by LLM Intelligence for AI Workloads
AI clusters keep data in remote object stores and rely on local caches to stop GPUs from waiting for data.Rohbau3D-Semantics: Dense Semantic and Instance Labels for Point Clouds of Indoor Shell Construction Scenes
We present the Rohbau3D-Semantics dataset, which adds dense semantic and instance-level labels to laser scans of the previously released Rohbau3D domain data from shell construction sites.Fano's Inequality and Channel Capacity in the Individual-Sequence Regime
We derive an individual-sequence analogue of Fano's inequality, replacing entropy by Lempel--Ziv (LZ) complexity and probability of error by empirical error frequency.Can Astra Solve RoboMME without Breaking the Bank?
Robotic manipulation often requires remembering information that is no longer visible, such as an object's location before occlusion or the order of a demonstrated action sequence.
Get the few papers worth your time in Computer Science & AI every morning.
Choose your topics and ReadSearch reads the new papers in them each day, then brings you the few worth reading, each with its key finding in a sentence.