Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 54,181 to 54,190 of 225,930 articles

Rethinking the Design Space of Reinforcement Learning for Diffusion Models: On the Importance of Likelihood Estimation Beyond Loss Design

arXiv Feb 4, 2026
Reinforcement learning has been widely applied to diffusion and flow models for visual tasks such as text-to-image generation. However, these tasks remain challenging because diffusion models have intractable likelihoods, which creates a barrier for ... read more 
Machine Learning cs.AI

Investigating Disability Representations in Text-to-Image Models

arXiv Feb 4, 2026
Text-to-image generative models have made remarkable progress in producing high-quality visual content from textual descriptions, yet concerns remain about how they represent social groups. While characteristics like gender and race have received inc... read more 
Computation and Language cs.CV cs.CY cs.HC

DRMOT: A Dataset and Framework for RGBD Referring Multi-Object Tracking

arXiv Feb 4, 2026
Referring Multi-Object Tracking (RMOT) aims to track specific targets based on language descriptions and is vital for interactive AI systems such as robotics and autonomous driving. However, existing RMOT models rely solely on 2D RGB data, making it ... read more 
Computer Vision and Pattern Recognition cs.AI

SAR-RAG: ATR Visual Question Answering by Semantic Search, Retrieval, and MLLM Generation

arXiv Feb 4, 2026
We present a visual-context image retrieval-augmented generation (ImageRAG) assisted AI agent for automatic target recognition (ATR) of synthetic aperture radar (SAR). SAR is a remote sensing method used in defense and security applications to detect... read more 
Computer Vision and Pattern Recognition cs.AI eess.IV

Adaptive Prompt Elicitation for Text-to-Image Generation

arXiv Feb 4, 2026
Aligning text-to-image generation with user intent remains challenging, for users who provide ambiguous inputs and struggle with model idiosyncrasies. We propose Adaptive Prompt Elicitation (APE), a technique that adaptively asks visual queries to he... read more 
Human-Computer Interaction cs.AI cs.CV

Bounded-Abstention Multi-horizon Time-series Forecasting

arXiv Feb 4, 2026
Multi-horizon time-series forecasting involves simultaneously making predictions for a consecutive sequence of subsequent time steps. This task arises in many application domains, such as healthcare and finance, where mispredictions can have a high c... read more 
Machine Learning

Benchmarking and Enhancing PPG-Based Cuffless Blood Pressure Estimation Methods

arXiv Feb 4, 2026
Cuffless blood pressure screening based on easily acquired photoplethysmography (PPG) signals offers a practical pathway toward scalable cardiovascular health assessment. Despite rapid progress, existing PPG-based blood pressure estimation models hav... read more 
Machine Learning eess.SP

Less Finetuning, Better Retrieval: Rethinking LLM Adaptation for Biomedical Retrievers via Synthetic Data and Model Merging

arXiv Feb 4, 2026
Retrieval-augmented generation (RAG) has become the backbone of grounding Large Language Models (LLMs), improving knowledge updates and reducing hallucinations. Recently, LLM-based retriever models have shown state-of-the-art performance for RAG appl... read more 
Computation and Language cs.LG

Mitigating Long-Tail Bias via Prompt-Controlled Diffusion Augmentation

arXiv Feb 4, 2026
Semantic segmentation of high-resolution remote-sensing imagery is critical for urban mapping and land-cover monitoring, yet training data typically exhibits severe long-tailed pixel imbalance. In the dataset LoveDA, this challenge is compounded by a... read more 
Computer Vision and Pattern Recognition

NeuroCanvas: VLLM-Powered Robust Seizure Detection by Reformulating Multichannel EEG as Image

arXiv Feb 4, 2026
Accurate and timely seizure detection from Electroencephalography (EEG) is critical for clinical intervention, yet manual review of long-term recordings is labor-intensive. Recent efforts to encode EEG signals into large language models (LLMs) show p... read more 
Machine Learning
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