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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 5
Two-stage residual learning for calibrated uncertainty in solar irradiance forecasts
Accurate forecasting of renewable generation requires not only point predictions but also reliable estimates of the uncertainty attached to them, particularly at extended horizons.Latency-Aware Adaptive Best-of-$N$
Test-time compute (TTC) improves language model responses by spending additional computation at inference time, and the right amount of compute depends on the prompt.The Last Mile to the Real World: Agent-Native Primitives as Reusable Building Blocks for Solving Real-World Tasks
How can an agent handle a real-world task end to end?Information-Spectrum General Formulas for the Capacity Region of Classical-Quantum Multiple Access Channels
For classical-quantum multiple access channels (cq-MACs) with two senders, we give several general expressions for the capacity region, valid for arbitrary sequences of channels.FREE-LIVO: Physically Decoupled Yet Tightly Coupled LiDAR-Inertial-Visual Odometry
LiDAR-Inertial-Visual Odometry (LIVO) integrates complementary LiDAR, camera, and IMU measurements to achieve robust state estimation.FINCOSMOS: An Open-World Evaluation Paradigm for Agents in Finance
Language agents increasingly work for users on the open Web, and finance is where trusting them is hardest.Recursive Self-Improvement for Long-Horizon Role-Playing Dialogue
Long-horizon role-playing dialogue requires consistent character identity, reliable memory, and context-sensitive interaction.Kinematic analysis of a double-closed-loop four-bar chain-based leg for a multimodal quadruped-pentarotor robot
This paper presents the kinematic modeling and singularity analysis of a three-degree-of-freedom, double four-bar closed-loop quadruped leg mechanism.Echoes of Error: Residual-Directional Local Rollout Consistency for Timeseries Forecasting
In time-series forecasting, rollout errors are not merely one-step fitting discrepancies: once fed back into the evolving state, they can perturb future predictions.Adversarial Robustness of Kernel Machines: A Comprehensive Analysis
Kernel machines are an important class of models in machine learning.KOSMOS: Self-scheduling Persistent Kernels for Communication-Compute Overlap
Tensor and sequence parallelism (TP+SP) and expert parallelism (EP) put collectives on the critical path of transformer layers.Localization Does Not Imply Steerability: A Mechanistic Study of Sign Errors in LLM Mathematics
When large language models do multi-step mathematics, a characteristic failure recurs: the model writes one wrong sign token mid-computation -- a cofactor sign, the minus of a recursive…Compact Motion Embeddings for Feed-forward Unified Human Animation
Animating a reference image with a driver's motion requires a motion representation that captures face, hand, and body articulation but excludes the driver's appearance.SAVeR$^2$: Reasoning-based Safety Alignment for Large Reasoning Models via Verifiable Rewards
Large Reasoning Models (LRMs) have achieved impressive performance via explicit Chain-of-Thought (CoT) reasoning, yet this process introduces critical safety risks.Signed but Not Safe: Requirement Integrity in Multi-Agent LLM Handoffs
Enterprise AI agents increasingly split a user's request across subagents and merge their results, and each handoff can summarize away, alter or ignore a requirement.MEvince: Knowledge-Constrained LLM Reasoning for Technique Identification from Malware Reports
Mapping behavioral intelligence in malware analysis reports to ATT&CK techniques supports threat analysis and defense, but reliable identification remains challenging.When Does Blockwise Additivity Break? Diagnosing and Repairing the Additive Assumption in Distillation-Based Architecture Search
Blockwise distillation methods for architecture search, such as DNA, DONNA, LANA and Puzzle, score each candidate replacement block in isolation and assemble a child network by minimizing the sum of…OPRD-Imp: a dataset of experimentally observed impurities and side products in multi-step pharmaceutical syntheses
Predicting reaction impurities is a critical yet persistently data-limited challenge in pharmaceutical process chemistry.ReviewMap: Mapping Evaluative Acts and Automation Boundaries in Peer-Review Comments
Peer-review comments check what a paper does and judge why it matters, but no existing scheme distinguishes these two evaluative acts.Statistical and Privacy Guarantees for Deep M-Regression via Stochastic Gradient Langevin Dynamics
In this article, we study deep nonparametric regression trained via stochastic gradient Langevin dynamics (SGLD), a variant of stochastic gradient descent that injects carefully calibrated Gaussian…
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