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Interdisciplinary & Society
Economics, finance, engineering and the social sciences share preprints on arXiv, and papers in chemistry and the earth sciences reach ReadSearch through OpenAlex. This page shows the newest papers ReadSearch has read in them.
The newest 1,000 papers, from 8 October 2026 to 5 November 2026: 997 arXiv preprints and 3 OpenAlex records.
Newest papers, page 50
Model-agnostic Knowledge Augmented Machine Learning for Weakly Annotated Bioimaging Data
Machine learning models are increasingly used for automated feature extraction from weakly annotated bioimaging data, such as microscopy and cytomorphology images.Can Multimodal Decision Models Classify Breast Ultrasound Images? Benchmarking CLEF and CLEF-Flash Across Prompts and Datasets
Multimodal decision models return probabilities over predefined alternatives, offering a structured interface for image classification.OpenPA: Forced-alignment-free Multi-granular Pronunciation Assessment with Mixed-transcript Adaptation
Recent advances in automatic pronunciation assessment (APA) have driven a shift from scripted to free-form assessment.Goal-Oriented Bundle Management and Flow Control for Deep-Space Communications via Reinforcement Learning
Deep-space communications operate under intermittent connectivity, long propagation delays, and relay storage constraints.Early Detection of Pension-Sponsor Distress from Public Filings: A Sponsor Vulnerability Index, Stress-Augmented VaR, and Dynamic Self-Investment Caps
A defined-benefit pension is only as safe as its sponsor, yet sponsor distress is under-instrumented relative to plan-side modelling.Exploring the Latent Structure of AMD Severity Using Retinal Foundation Models
Retinal foundation models have demonstrated strong performance across a wide range of ophthalmic tasks, yet relatively little is known about how disease-related information is represented within…Frozen Site-Probe Accuracy Is Not a Standalone Harmonization Score: An Audit of Evaluation Practice for Multi-Site MRI
Image-level MRI harmonization is often evaluated with a frozen site probe, a site classifier trained on raw scans and applied unchanged to harmonized ones: a drop in its accuracy is read as removal…C$^2$LUE: Clinically Aligned Patient-Level Ultrasound Diagnosis via Evidence-Aware Multi-Instance Learning
Patient-level ultrasound diagnosis demands not only high predictive accuracy but also clinically aligned mitigation of asymmetric diagnostic risks.Beyond Discrimination: Evaluating Probability Calibration in Radiomics-Image Fusion for Renal Cell Carcinoma Classification
Reliable probability estimates are important for the clinical interpretation of machine-learning classifiers, yet radiomics--image fusion models for renal cell carcinoma (RCC) are commonly evaluated…Beyond Gate Weights: Decision-Level Interpretation of Radiomics-Image Feature Fusion for RCC Classification
Gate coefficients describe how a fusion layer weights intermediate features, but they do not necessarily reflect the magnitude of branch contributions at the classifier output.Semantic Edge-Cloud Communication for Real-Time Urban Traffic Digital Twins
Urban traffic systems are becoming increasingly complex, demanding real-time traffic perception, proactive collision prediction, and intelligent management to improve safety and reduce congestion.RUBATO: Decoupled Clocks Allow Full-Duplex Models to Think as Fast as They Can
Recent Speech Full-Duplex (FDX) models are capable of engaging in naturalistic conversation by listening and speaking at the same time.ConicFlow: constrained Inference-time optimal control for flow matching models
We propose ConicFlow, which frames constrained sampling from a flow matching model at inference time as an optimal control problem that balances deviation from the pretrained trajectory against…History, Adaptation, and Hidden Gain: Two Prospective Tests of Learned Predictive Control in a Synthetic Neural Population
We study learned one-step predictive control of a synthetic population of 64 leaky integrate-and-fire neurons whose light sensitivity is scaled by a hidden factor s, using two prospective…Deep learning from a control vantage point
This article offers an overview of recent developments in deep learning from a control vantage point.Risk Ceilings and Development Deadlines: Pacing AI under Uncertain Safety Productivity
Can a regulator promise both a risk ceiling and a development deadline when safety productivity is unknown?Skeleton-Guided Progressive Test-Time Adaptation for Thin Curvilinear Structures
Accurate segmentation of thin curvilinear structures is vital for various real-world applications, from vessel analysis to road extraction.Improving Image-Based Nutrition Estimation Through Multimodal Food-Item Verification and Recovery
Single-image nutrition estimation can fail silently when visible foods are missed.A Unified Score Matching Paradigm for Video Anomaly Detection and Anticipation
Video anomaly detection (VAD) is a fundamental and safety-critical task in computer vision.Causal-fate dynamics of unrealized influence
Many dynamical systems generate influences whose consequences are not fully exhausted in the realized trajectory at the moment they arise.
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