Papers Biomedical Information Retrieval
“Biomedical Information Retrieval” 태그가 달린 논문 19편 · 필터 해제
BioHiCL: Hierarchical Multi-Label Contrastive Learning for Biomedical Retrieval with MeSH Labels
Effective biomedical information retrieval requires modeling domain semantics and hierarchical relationships among biomedical texts. Existing biomedical generative retrievers build on coarse binary relevance signals, lim…
Biomedical Information RetrievalContrastive LearningQuestion AnsweringBioMedSearch: A Multi-Source Biomedical Retrieval Framework Based on LLMs
Biomedical queries often rely on a deep understanding of specialized knowledge such as gene regulatory mechanisms and pathological processes of diseases. They require detailed analysis of complex physiological processes …
Biomedical Information RetrievalQuestion AnsweringOntology-Guided Query Expansion for Biomedical Document Retrieval using Large Language Models
Effective Question Answering (QA) on large biomedical document collections requires effective document retrieval techniques. The latter remains a challenging task due to the domain-specific vocabulary and semantic ambigu…
Biomedical Information RetrievalQuestion AnsweringTowards Domain Specification of Embedding Models in Medicine
Medical text embedding models are foundational to a wide array of healthcare applications, ranging from clinical decision support and biomedical information retrieval to medical question answering, yet they remain hamper…
Biomedical Information RetrievalContrastive LearningQuestion AnsweringInterpretability Analysis of Domain Adapted Dense Retrievers
Dense retrievers have demonstrated significant potential for neural information retrieval; however, they exhibit a lack of robustness to domain shifts, thereby limiting their efficacy in zero-shot settings across diverse…
Biomedical Information RetrievalDomain AdaptationInformation RetrievalQuestion Answering+2MedCPT: Contrastive Pre-trained Transformers with Large-scale PubMed Search Logs for Zero-shot Biomedical Information Retrieval
Information retrieval (IR) is essential in biomedical knowledge acquisition and clinical decision support. While recent progress has shown that language model encoders perform better semantic retrieval, training such mod…
Biomedical Information RetrievalContrastive LearningInformation RetrievalLanguage Modeling+4Opportunities and Challenges for ChatGPT and Large Language Models in Biomedicine and Health
ChatGPT has drawn considerable attention from both the general public and domain experts with its remarkable text generation capabilities. This has subsequently led to the emergence of diverse applications in the field o…
Biomedical Information RetrievalInformation RetrievalQuestion AnsweringText Generation+1Maximizing Use-Case Specificity through Precision Model Tuning
Language models have become increasingly popular in recent years for tasks like information retrieval. As use-cases become oriented toward specific domains, fine-tuning becomes default for standard performance. To fine-t…
Biomedical Information RetrievalInformation RetrievalmodelRetrieval+1Direct Generation of Protein Conformational Ensembles via Machine Learning
Dynamics and conformational sampling are essential for linking protein structure to biological function. While challenging to probe experimentally, computer simulations are widely used to describe protein dynamics, but a…
BIG-bench Machine LearningBiomedical Information RetrievalDrug DiscoveryGenerative Adversarial Network+1No Parameter Left Behind: How Distillation and Model Size Affect Zero-Shot Retrieval
Recent work has shown that small distilled language models are strong competitors to models that are orders of magnitude larger and slower in a wide range of information retrieval tasks. This has made distilled and dense…
Argument RetrievalBiomedical Information RetrievalCitation PredictionDuplicate-Question Retrieval+7SGPT: GPT Sentence Embeddings for Semantic Search
Decoder transformers have continued increasing in scale reaching hundreds of billions of parameters. Due to their scale the same decoder sets state-of-the-art results on various language tasks via prompting or fine-tunin…
Argument RetrievalBiomedical Information RetrievalCitation PredictionDecoder+11Improving Biomedical Information Retrieval with Neural Retrievers
Information retrieval (IR) is essential in search engines and dialogue systems as well as natural language processing tasks such as open-domain question answering. IR serve an important function in the biomedical domain,…
Biomedical Information RetrievalInformation RetrievalOpen-Domain Question AnsweringQuestion Answering+3MedGraph: An experimental semantic information retrieval method using knowledge graph embedding for the biomedical citations indexed in PubMed
Here we study the semantic search and retrieval problem in biomedical digital libraries. First, we introduce MedGraph, a knowledge graph embedding-based method that provides semantic relevance retrieval and ranking for t…
ArticlesBiomedical Information RetrievalGraph EmbeddingInformation Retrieval+2BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models
Existing neural information retrieval (IR) models have often been studied in homogeneous and narrow settings, which has considerably limited insights into their out-of-distribution (OOD) generalization capabilities. To a…
Argument RetrievalBenchmarkingBiomedical Information RetrievalCitation Prediction+11Querying Across Genres for Medical Claims in News
We present a query-based biomedical information retrieval task across two vastly different genres {--} newswire and research literature {--} where the goal is to find the research publication that supports the primary cl…
Biomedical Information RetrievalInformation RetrievalRe-RankingRetrievalResolving the Scope of Speculation and Negation using Transformer-Based Architectures
Speculation is a naturally occurring phenomena in textual data, forming an integral component of many systems, especially in the biomedical information retrieval domain. Previous work addressing cue detection and scope r…
Biomedical Information RetrievalInformation RetrievalNegationNegation Detection+4edge2vec: Representation learning using edge semantics for biomedical knowledge discovery
Representation learning provides new and powerful graph analytical approaches and tools for the highly valued data science challenge of mining knowledge graphs. Since previous graph analytical methods have mostly focused…
Biomedical Information RetrievalInformation RetrievalKnowledge GraphsRepresentation Learning+1A Fast Deep Learning Model for Textual Relevance in Biomedical Information Retrieval
Publications in the life sciences are characterized by a large technical vocabulary, with many lexical and semantic variations for expressing the same concept. Towards addressing the problem of relevance in biomedical li…
Biomedical Information RetrievalDeep LearningInformation RetrievalRetrieval+1Deep Learning for Biomedical Information Retrieval: Learning Textual Relevance from Click Logs
We describe a Deep Learning approach to modeling the relevance of a document{'}s text to a query, applied to biomedical literature. Instead of mapping each document and query to a common semantic space, we compute a vari…
Biomedical Information RetrievalInformation RetrievalregressionRetrieval+1