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Found 7 papers, 1 papers with code
Leveraging Large Language Model as Simulated Patients for Clinical Education
Simulated Patients (SPs) play a crucial role in clinical medical education by providing realistic scenarios for student practice.
Two is Better Than One: Answering Complex Questions by Multiple Knowledge Sources with Generalized Links
Incorporating multiple knowledge sources is proven to be beneficial for answering complex factoid questions.
ADMUS: A Progressive Question Answering Framework Adaptable to Multiple Knowledge Sources
With the introduction of deep learning models, semantic parsingbased knowledge base question answering (KBQA) systems have achieved high performance in handling complex questions.
Joint Channel Estimation and Turbo Equalization of Single-Carrier Systems over Time-Varying Channels
Block transmission systems have been proven successful over frequency-selective channels.
Crake: Causal-Enhanced Table-Filler for Question Answering over Large Scale Knowledge Base
Semantic parsing solves knowledge base (KB) question answering (KBQA) by composing a KB query, which generally involves node extraction (NE) and graph composition (GC) to detect and connect related nodes in a query.
NAMER: A Node-Based Multitasking Framework for Multi-Hop Knowledge Base Question Answering
We present NAMER, an open-domain Chinese knowledge base question answering system based on a novel node-based framework that better grasps the structural mapping between questions and KB queries by aligning the nodes in a query with their corresponding mentions in question.
Overview of the CCKS 2019 Knowledge Graph Evaluation Track: Entity, Relation, Event and QA
Knowledge graph models world knowledge as concepts, entities, and the relationships between them, which has been widely used in many real-world tasks.
