Prescriptions

INT: Instance-Specific Negative Mining for Task-Generic Promptable Segmentation

Task-generic promptable image segmentation aims to achieve segmentation of diverse samples under a single task description by utilizing only one task-generic prompt. Current methods leverage the generalization capabilities of Vision-Language Models (VLMs) to infer instance-specific prompts from these task-generic prompts in order to guide the segmentation process. However, when VLMs struggle to ...

Integrating Reinforcement Learning and AI Agents for Adaptive Robotic Interaction and Assistance in Dementia Care

This study explores a novel approach to advancing dementia care by integrating socially assistive robotics, reinforcement learning (RL), large language models (LLMs), and clinical domain expertise within a simulated environment. This integration addresses the critical challenge of limited experimental data in socially assistive robotics for dementia care, providing a dynamic simulation environme...

A Comprehensive Study on Fine-Tuning Large Language Models for Medical Question Answering Using Classification Models and Comparative Analysis

This paper presents the overview of the development and fine-tuning of large language models (LLMs) designed specifically for answering medical ques...

A foundation model for human-AI collaboration in medical literature mining

Systematic literature review is essential for evidence-based medicine, requiring comprehensive analysis of clinical trial publications. However, the...

Inductive-Associative Meta-learning Pipeline with Human Cognitive Patterns for Unseen Drug-Target Interaction Prediction

Significant differences in protein structures hinder the generalization of existing drug-target interaction (DTI) models, which often rely heavily o...

"Stones from Other Hills can Polish Jade": Zero-shot Anomaly Image Synthesis via Cross-domain Anomaly Injection

Industrial image anomaly detection (IAD) is a pivotal topic with huge value. Due to anomaly's nature, real anomalies in a specific modern industrial...

Design and Implementation of a Psychiatry Resident Training System Based on Large Language Models

Mental disorders have become a significant global public health issue, while the shortage of psychiatrists and inefficient training systems severely...

Distinguishing Parkinson's Patients Using Voice-Based Feature Extraction and Classification

Parkinson's disease (PD) is a progressive neurodegenerative disorder that impacts motor functions and speech characteristics This study focuses on d...

Correctness Assessment of Code Generated by Large Language Models Using Internal Representations

Ensuring the correctness of code generated by Large Language Models (LLMs) presents a significant challenge in AI-driven software development. Exist...

Bidirectional Brain Image Translation using Transfer Learning from Generic Pre-trained Models

Brain imaging plays a crucial role in the diagnosis and treatment of various neurological disorders, providing valuable insights into the structure ...

Modality Interactive Mixture-of-Experts for Fake News Detection

The proliferation of fake news on social media platforms disproportionately impacts vulnerable populations, eroding trust, exacerbating inequality, ...

UI-TARS: Pioneering Automated GUI Interaction with Native Agents

This paper introduces UI-TARS, a native GUI agent model that solely perceives the screenshots as input and performs human-like interactions (e.g., k...

Tikhonov-Fenichel Reductions and their Application to a Novel Modelling Approach for Mutualism

When formulating a model there is a trade-off between model complexity and (biological) realism. In the present paper we demonstrate how model reduc...

Prediction of Lung Metastasis from Hepatocellular Carcinoma using the SEER Database

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality, with lung metastases being the most common site of distant spread and...

Harnessing the Potential of Large Language Models in Modern Marketing Management: Applications, Future Directions, and Strategic Recommendations

Large Language Models (LLMs) have revolutionized the process of customer engagement, campaign optimization, and content generation, in marketing man...

PaSa: An LLM Agent for Comprehensive Academic Paper Search

We introduce PaSa, an advanced Paper Search agent powered by large language models. PaSa can autonomously make a series of decisions, including invo...

FiLo++: Zero-/Few-Shot Anomaly Detection by Fused Fine-Grained Descriptions and Deformable Localization

Anomaly detection methods typically require extensive normal samples from the target class for training, limiting their applicability in scenarios t...

Attention is All You Need Until You Need Retention

This work introduces a novel Retention Layer mechanism for Transformer based architectures, addressing their inherent lack of intrinsic retention ca...

Image-to-Force Estimation for Soft Tissue Interaction in Robotic-Assisted Surgery Using Structured Light

For Minimally Invasive Surgical (MIS) robots, accurate haptic interaction force feedback is essential for ensuring the safety of interacting with so...

DNMDR: Dynamic Networks and Multi-view Drug Representations for Safe Medication Recommendation

Medication Recommendation (MR) is a promising research topic which booms diverse applications in the healthcare and clinical domains. However, exist...