AI & Machine Learning · Computer Science & AI
Artificial Intelligence
The newest papers in Artificial Intelligence that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
The newest 5,000 papers, from 11 October 2026 to 5 November 2026: 4,998 arXiv preprints and 2 OpenAlex records.
Get the few papers worth your time in Artificial Intelligence every morning.
Follow Artificial Intelligence and ReadSearch reads its new papers each day, then brings you the few worth reading, each with its key finding in a sentence.
Newest papers, page 173
A Small Model Asks Better: Fine-Tuning Query Clarification for Retrieval-Augmented Generation
Query clarification is essential for retrieval-augmented generation (RAG) systems that face ambiguous user queries.When Stable and Preferred Semantics Agree: A Path-Based Approach
We investigate structural conditions under which preferred and stable semantics agree in abstract argumentation frameworks.GeoDiv KAN Solver for Time Fractional Navier Stokes Equations on Complex Domains to Realistic CFD Reconstruction
Scientific machine learning provides a promising framework for solving complex problems in science and engineering.Detecting AI Training in Datacentre Power
AI governance agreements require methods to detect large model training runs on a monitored computing cluster, without trusting the operator.Stable Signer V3: 4D Deformable Primitive Splatting Is All You Need for Sign Language Production
We present Stable Signer V3, an interactive high-resolution sign language avatar system built on 4D Deformable Primitive Splatting.Means-Ends Analysis Helps LLMs Plan in Continuous-State Domains
LLM planning research has traditionally focused on discrete-state domains, where actions form a finite, enumerable set.What Can't Jev Decide? Probing the Limits of One-Pass Decision Models
Jev and its open replicas choose among the options a caller supplies with a single forward pass, fast enough to decide inside an agent loop.TrustAgent-RFF: Agentic Diagnostic Planning for Reliable RF Fingerprinting under Domain Shift
Radio frequency fingerprinting (RFF) models can achieve accuracy under source domain conditions but become unreliable when the receiver, distance, collection day, or environment changes.LowNet: Looped Wavelet Neural Networks with 24 Learnable Parameters for Solving Poisson Equations
Poisson equations frequently appear in various fields, such as mathematics, physics and informatics.Epi: Towards a Persistent, Self-Improving Agent for Autonomous Research
We present Épi, an autonomous research agent that sustains investigations across model sessions and evolves its methods through accumulated experience. Épi combines persistent research history…Robust Direct Preference Optimization under Preference Label-Flip Attacks
Direct Preference Optimization (DPO) is widely used for offline Reinforcement Learning from Human Feedback.ControlJEPA: Principled Trajectory Regularization via Lyapunov Tube Loss
Next-token prediction leaves hidden-state trajectories largely unconstrained, while existing geometric regularizers primarily control the direction rather than the magnitude of trajectory deviations.CasePlay: Self-Play Reinforcement Learning from Case Reports for Medical Reasoning
Reinforcement learning (RL) is a promising way to improve the clinical reasoning abilities of large language models (LLMs), but current pipelines often rely on expert-labeled questions or costly…MemPrice: Online Memory Allocation via Adaptive Pricing for Long-Horizon Agents
Long-horizon LLM agents face a fundamental allocation problem as interaction histories grow: which information to retain, how much context to devote to it, and at what granularity.Revealing what benchmark scores hide: Jointly measuring the breadth and reliability of LLM capabilities using accessibility profiles
Language model benchmarks assign each question a single outcome from one fixed wording, even though the same underlying request can be expressed in many equivalent ways.CoworkEnv: Synthesizing Training Environments for Long-Horizon Cowork Agents
AI coworkers must coordinate tools, communicate across turns, and act on changing workspace state while respecting workflow constraints.Label-Space Mismatch Distorts Cross-Cohort Evaluation in Breast Cancer Molecular Subtyping
Cross-cohort evaluation of breast cancer subtype classifiers is unreliable when source and target cohorts use different annotation standards: METABRIC labels six classes, PAM50 defines five, and a…Towards Human-AI Complementarity for AI Safety
Safely overseeing AI is increasingly challenging for the humans doing it, as they must evaluate longer and more complex outputs with every new model generation.PRECOCIAL: Pretraining with Code Curriculums via Iterative Search for Accelerated Learning
Fully synthetic pretraining data generated by symbolic programs can bootstrap downstream training on naturalistic tasks, such as language modeling, but the generating programs have so far been…CorrectRTL: Boost RTL Generation Quality Through Automated Self-Correction with Instruction Decomposition
Large language models (LLMs) have shown strong promise in specification-to-RTL generation.