Learning Hybrid Representations to Retrieve Semantically Equivalent Questions
Code (0)
등록된 구현이 없습니다.
Tasks
Information RetrievalKnowledge GraphsLearning-To-RankMachine TranslationQuestion AnsweringSemantic Textual SimilaritySimilar Papers 제목 키워드 기반
Improving Document Retrieval Coherence for Semantically Equivalent Queries
Dense Retrieval (DR) models have proven to be effective for Document Retrieval and Information Grounding tasks. Usually, these models are trained and optimized for improving the relevance of top-ranked documents for a gi…
Natural QuestionsAutomating Clinical Information Retrieval from Finnish Electronic Health Records Using Large Language Models
Clinicians often need to retrieve patient-specific information from electronic health records (EHRs), a task that is time-consuming and error-prone. We present a locally deployable Clinical Contextual Question Answering …
Information RetrievalQuestion AnsweringText GenerationSUN: Exploring Intrinsic Uncertainties in Text-to-SQL Parsers
This paper aims to improve the performance of text-to-SQL parsing by exploring the intrinsic uncertainties in the neural network based approaches (called SUN). From the data uncertainty perspective, it is indisputable th…
SQL ParsingText to SQLText-To-SQLBridging the Semantic Gaps: Improving Medical VQA Consistency with LLM-Augmented Question Sets
Medical Visual Question Answering (MVQA) systems can interpret medical images in response to natural language queries. However, linguistic variability in question phrasing often undermines the consistency of these system…
DiversityMedical Visual Question AnsweringNatural Language QueriesQuestion Answering+3