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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.
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Newest papers, page 71
How to Loop Your Transformer: Loop Scaling, Specialization, and Parallel Inference
Looping in transformer models reuses weights by repeatedly applying the same transformer, or parts of it, making the model deeper without increasing its parameter count.Radiology Guideline-derived Decision Graph for Efficient Clinical Decision Support
Radiological risk stratification and management planning are essential downstream tasks in medical imaging.Multistep and Multivariate Time Series Explainability with GradientSHAP: A Wind Power Case Study
As the effects of climate change become increasingly apparent, the demand for renewable energy sources such as wind power continues to grow.A Unified Hessian-Guided Framework for Post-Training Quantization
Low-bit quantization enables efficient deployment of large language models by reducing memory footprint and computational cost.The Athlete as a Scientist of One: Agentic Bayesian Experimental Design for Individualized Physiology from Consumer Wearables
Large language model (LLM) agents for personal health read wearable data and recommend, but do not learn about the individual in a way that can be audited or falsified.Beyond Selected Breakthroughs: Evaluating Language Models on Randomly Sampled Mathematical Conjectures
The last year has seen a shift in AI-assisted mathematics, with frontier language models producing proofs of and counterexamples to long-standing open conjectures.Scaling Mathematical Proof Supervision from Structured Textbooks
Mathematical supervision for language models is typically flattened into isolated problem-solution pairs, discarding the curricular organization and evidential structure of the original sources.Understanding and Mitigating Role Spoofing in LLMs
Despite growing capabilities, LLMs remain susceptible to prompt injections: malicious inputs that can manipulate or hijack models.SCARL: Sequence Confidence-Aligned Reinforcement Learning
Reinforcement learning with verifiable rewards (RLVR) improves language-model reasoning by scoring sampled responses with a rule-based verifier and reinforcing those that pass.Retrieving from Your Own Mistakes: On-Policy Training of Embedding Models for Multi-Hop Retrieval-Augmented Generation
Complex questions in retrieval-augmented generation require evidence spread over several documents, and an answer is reliable only when the retriever finds all of it.Bridging Neural Representations and Symbolic Semantics in Audio Classification
Deep audio classifiers can achieve strong predictive performance, but their hidden representations remain difficult to interpret.IMPACT: Inverter-Informed Multimodal Learning for Photovoltaic Generation Forecasting
This work develops a physics-informed multimodal deep learning framework for 10- to 110-minute-ahead probabilistic photovoltaic power forecasting.NECA: Neighbor Event Curve Augmentation for Multi-Horizon ICU Deterioration Prediction
Early prediction of ICU organ dysfunction events supports timely clinical monitoring and intervention, but estimating short-term organ-specific risk from early ICU records remains challenging due to…Prefix Executability: Evaluating Tool-Using Agents Beyond Final Success
Tool-use benchmarks often score agents by final task success, but terminal outcomes can obscure whether the intermediate tool-call trajectory was executable.Training language models in simulation for psychiatric intake
In psychiatric practice, the clinical intake interview remains a primary diagnostic instrument, requiring the clinician to establish rapport while disentangling complex, overlapping presentations.FIRME: Registry-Anchored Memory Graphs for Evolving, Heterogeneous Investor Knowledge
Financial AI workflows that reuse investor knowledge need persistent memory that integrates observations across sources and periods without losing identity or provenance.MetaRefine: Score Refinement with Multi-Level Features for Image Assessment
An image's original dimensions, aspect ratio, and composition provide important cues that can affect its technical and aesthetic quality.rTaste: Do Research Agents Have Taste? Evaluating Early Stage Research Judgment
Do research agents have taste, the judgment of which experiments are worth running before their outcomes are known?Fast and accurate neural triage decoding of ultra-high-rate quantum LDPC codes
Quantum error correction is essential for fault-tolerant quantum computing.Agentic University: Collaborative Agents for Personalized Learning
Large language models support personalized tutoring, content generation, and adaptive learning paths.