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Automatic Configuration of LLM Post-Training Pipelines

LLM post-training pipelines that combine supervised fine-tuning and reinforcement learning are diffi...

Visual Product Search Benchmark

Reliable product identification from images is a critical requirement in industrial and commercial a...

Informative Perturbation Selection for Uncertainty-Aware Post-hoc Explanations

Trust and ethical concerns due to the widespread deployment of opaque machine learning (ML) models m...

Informative Perturbation Selection for Uncertainty-Aware Post-hoc Explanations

Trust and ethical concerns due to the widespread deployment of opaque machine learning (ML) models m...

Managing Cognitive Bias in Human Labeling Operations for Rare-Event AI: Evidence from a Field Experiment

Many operational AI systems depend on large-scale human annotation to detect rare but consequential ...

mRNA-Protein Coordination is Contextualized by Metastatic Biological Phenotypes

A central goal of conducting omics measurements is to understand how molecular features inform highe...

Why Does It Look There? Structured Explanations for Image Classification

Deep learning models achieve remarkable predictive performance, yet their black-box nature limits tr...

A prospective clinical feasibility study of a conversational diagnostic AI in an ambulatory primary care clinic

Large language model (LLM)-based AI systems have shown promise for patient-facing diagnostic and man...

Synthetic Defect Image Generation for Power Line Insulator Inspection Using Multimodal Large Language Models

Utility companies increasingly rely on drone imagery for post-event and routine inspection, but trai...

A prospective clinical feasibility study of a conversational diagnostic AI in an ambulatory primary care clinic

Large language model (LLM)-based AI systems have shown promise for patient-facing diagnostic and man...

Interpretable Aneurysm Classification via 3D Concept Bottleneck Models: Integrating Morphological and Hemodynamic Clinical Features

We are concerned with the challenge of reliably classifying and assessing intracranial aneurysms usi...

GRD-Net: Generative-Reconstructive-Discriminative Anomaly Detection with Region of Interest Attention Module

Anomaly detection is nowadays increasingly used in industrial applications and processes. One of the...

Trustworthy personalized treatment selection: causal effect-trees and calibration in perioperative medicine

Background Personalized medicine promises to tailor treatments to the individual, but it carries a h...

vToxiNet: a biologically constrained deep learning framework for interpretable prediction of drug-induced hepatotoxicity

Hepatotoxicity remains a leading cause of drug attrition and post-marketing withdrawal, resulting fr...

Interpretable Debiasing of Vision-Language Models for Social Fairness

The rapid advancement of Vision-Language models (VLMs) has raised growing concerns that their black-...

Space Syntax-guided Post-training for Residential Floor Plan Generation

Pre-trained generative models for residential floor plans are typically optimized to fit large-scale...

Early Risk Stratification of Dosing Errors in Clinical Trials Using Machine Learning

Objective: The objective of this study is to develop a machine learning (ML)-based framework for ear...

Biomedical Large Language Models and Prompt Engineering for Causality Assessment of Individual Case Safety Reports in Pharmacovigilance

Background: Biomedical Large Language Models (LLMs) combined with prompt engineering offer domain-sp...

Mobile-O: Unified Multimodal Understanding and Generation on Mobile Device

Unified multimodal models can both understand and generate visual content within a single architectu...

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