Motivation Biomedical entity linking (BEL) is the task of grounding entity mentions to a
knowledge base (KB). It plays a vital role in information extraction pipelines for the life …

We present BYOKG, a universal question-answering (QA) system that can operate on any
knowledge graph (KG), requires no human-annotated training data, and can be ready to use …

Biomedical entity linking (BioEL) is the process of connecting entities referenced in
documents to entries in biomedical databases such as the Unified Medical Language …

Objective To improve performance of medical entity normalization across many languages,
especially when fewer language resources are available compared to English. Materials …

Large autoregressive generative models have emerged as the cornerstone for achieving the
highest performance across several Natural Language Processing tasks. However, the urge …

Abstract Objectives Biomedical Knowledge Graphs play a pivotal role in various biomedical
research domains. Concurrently, term clustering emerges as a crucial step in constructing …

Multiple-choice questions (MCQs) are a kind of widely adopted approaches in learning
assessment. Recently, the automatic generation of MCQs has become a popular research …

Dual encoder models are ubiquitous in modern classification and retrieval. Crucial for
training such dual encoders is an accurate estimation of gradients from the partition function …

Motivation Biomedical entity linking (BEL) is the task of grounding entity mentions to a given
knowledge base (KB). Recently, neural name-based methods, system identifying the most …

Recent research tends to address the biomedical entity linking problem in a unified
framework solely based on surface form matching between mentions and entities …