Prescriptions

VEPerform: a web resource for evaluating the performance of variant effect predictors

Computational variant effect predictors (VEPs) are providing increasingly strong evidence to classify the pathogenicity of missense variants. Precision vs. recall analysis is useful in evaluating VEP performance, especially when adjusted for imbalanced test sets. Here, we describe VEPerform, a web-based tool for evaluating the performance of VEPs at the gene level using balanced precision vs. re...

Solving Robust Markov Decision Processes: Generic, Reliable, Efficient

Markov decision processes (MDP) are a well-established model for sequential decision-making in the presence of probabilities. In robust MDP (RMDP), every action is associated with an uncertainty set of probability distributions, modelling that transition probabilities are not known precisely. Based on the known theoretical connection to stochastic games, we provide a framework for solving RMDPs ...

ManipGPT: Is Affordance Segmentation by Large Vision Models Enough for Articulated Object Manipulation?

Visual actionable affordance has emerged as a transformative approach in robotics, focusing on perceiving interaction areas prior to manipulation. T...

Precision-Enhanced Human-Object Contact Detection via Depth-Aware Perspective Interaction and Object Texture Restoration

Human-object contact (HOT) is designed to accurately identify the areas where humans and objects come into contact. Current methods frequently fail ...

Enhancing Multimodal Large Language Models Complex Reason via Similarity Computation

Multimodal large language models have experienced rapid growth, and numerous different models have emerged. The interpretability of LVLMs remains an...

Vision-Language Models Generate More Homogeneous Stories for Phenotypically Black Individuals

Vision-Language Models (VLMs) extend Large Language Models' capabilities by integrating image processing, but concerns persist about their potential...

From Bench to Bedside: A Review of Clinical Trials in Drug Discovery and Development

Clinical trials are an indispensable part of the drug development process, bridging the gap between basic research and clinical application. During ...

StreamChat: Chatting with Streaming Video

This paper presents StreamChat, a novel approach that enhances the interaction capabilities of Large Multimodal Models (LMMs) with streaming video c...

Zero-Shot ATC Coding with Large Language Models for Clinical Assessments

Manual assignment of Anatomical Therapeutic Chemical (ATC) codes to prescription records is a significant bottleneck in healthcare research and oper...

SmartAgent: Chain-of-User-Thought for Embodied Personalized Agent in Cyber World

Recent advances in embodied agents with multimodal perception and reasoning capabilities based on large vision-language models (LVLMs), excel in aut...

MPSI: Mamba enhancement model for pixel-wise sequential interaction Image Super-Resolution

Single image super-resolution (SR) has long posed a challenge in the field of computer vision. While the advent of deep learning has led to the emer...

Subgraph-Oriented Testing for Deep Learning Libraries

Deep Learning (DL) libraries, such as PyTorch, are widely used for building and deploying DL models on various hardware platforms. Meanwhile, they a...

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study

Large Language Models (LLMs) have demonstrated strong potential across legal tasks, yet the problem of legal citation prediction remains under-explo...

PBI-Attack: Prior-Guided Bimodal Interactive Black-Box Jailbreak Attack for Toxicity Maximization

Understanding the vulnerabilities of Large Vision Language Models (LVLMs) to jailbreak attacks is essential for their responsible real-world deploym...

Risk factor identification and classification of malnutrition among under-five children in Bangladesh: Machine learning and statistical approach

This study aims to understand the factors that resulted in under-five children's malnutrition from the Multiple Indicator Cluster (MICS-2019) nation...

KITE-DDI: A Knowledge graph Integrated Transformer Model for accurately predicting Drug-Drug Interaction Events from Drug SMILES and Biomedical Knowledge Graph

It is a common practice in modern medicine to prescribe multiple medications simultaneously to treat diseases. However, these medications could have...

DEMO: Reframing Dialogue Interaction with Fine-grained Element Modeling

Large language models (LLMs) enabled dialogue systems have become one of the central modes in human-machine interaction, which bring about vast amou...

CreatiLayout: Siamese Multimodal Diffusion Transformer for Creative Layout-to-Image Generation

Diffusion models have been recognized for their ability to generate images that are not only visually appealing but also of high artistic quality. A...

FedMetaMed: Federated Meta-Learning for Personalized Medication in Distributed Healthcare Systems

Personalized medication aims to tailor healthcare to individual patient characteristics. However, the heterogeneity of patient data across healthcar...

Toward clearer recognition and easier usefulness: development of a cross-lingual atherosclerotic cerebrovascular disease ontology.

Atherosclerotic cerebrovascular disease could result in a great number of deaths and disabilities. However, it did not acquire enough attention. Less ...