Papers Relevance Detection
“Relevance Detection” 태그가 달린 논문 14편 · 필터 해제
Relevance for Stability of Verification Status of a Set of Arguments in Incomplete Argumentation Frameworks (with Proofs)
The notion of relevance was proposed for stability of justification status of a single argument in incomplete argumentation frameworks (IAFs) in 2024 by Odekerken et al. To extend the notion, we study the relevance for s…
Relevance DetectionUsing External knowledge to Enhanced PLM for Semantic Matching
Modeling semantic relevance has always been a challenging and critical task in natural language processing. In recent years, with the emergence of massive amounts of annotated data, it has become feasible to train comple…
Relevance DetectionEnhancing Function-Calling Capabilities in LLMs: Strategies for Prompt Formats, Data Integration, and Multilingual Translation
Large language models (LLMs) have significantly advanced autonomous agents, particularly in zero-shot tool usage, also known as function calling. This research delves into enhancing the function-calling capabilities of L…
Data IntegrationInstruction FollowingRelevance DetectionTranslationFunctionChat-Bench: Comprehensive Evaluation of Language Models' Generative Capabilities in Korean Tool-use Dialogs
This study investigates language models' generative capabilities in tool-use dialogs. We categorize the models' outputs in tool-use dialogs into four distinct types: Tool Call, Answer Completion, Slot Question, and Relev…
Relevance DetectionCineXDrama: Relevance Detection and Sentiment Analysis of Bangla YouTube Comments on Movie-Drama using Transformers: Insights from Interpretability Tool
In recent years, YouTube has become the leading platform for Bangla movies and dramas, where viewers express their opinions in comments that convey their sentiments about the content. However, not all comments are releva…
Relevance DetectionSentiment AnalysisESG-FTSE: A corpus of news articles with ESG relevance labels and use cases
We present ESG-FTSE, the first corpus comprised of news articles with Environmental, Social and Governance (ESG) relevance annotations. In recent years, investors and regulators have pushed ESG investing to the mainstrea…
ArticlesRelevance DetectionVariable Selection in Maximum Mean Discrepancy for Interpretable Distribution Comparison
Two-sample testing decides whether two datasets are generated from the same distribution. This paper studies variable selection for two-sample testing, the task being to identify the variables (or dimensions) responsible…
Causal InferenceRelevance DetectionTwo-sample testingVariable SelectionBenchmarking the Performance of Bayesian Optimization across Multiple Experimental Materials Science Domains
In the field of machine learning (ML) for materials optimization, active learning algorithms, such as Bayesian Optimization (BO), have been leveraged for guiding autonomous and high-throughput experimentation systems. Ho…
Active LearningBayesian OptimisationBayesian OptimizationBenchmarking+3Relevance Detection in Cataract Surgery Videos by Spatio-Temporal Action Localization
In cataract surgery, the operation is performed with the help of a microscope. Since the microscope enables watching real-time surgery by up to two people only, a major part of surgical training is conducted using the re…
Action LocalizationRelevance DetectionRetrievalSpatio-Temporal Action Localization+1Named Entities in Medical Case Reports: Corpus and Experiments
We present a new corpus comprising annotations of medical entities in case reports, originating from PubMed Central's open access library. In the case reports, we annotate cases, conditions, findings, factors and negatio…
named-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)Negation+3A-MAL: Automatic Movement Assessment Learning from Properly Performed Movements in 3D Skeleton Videos
The task of assessing movement quality has recently gained high demand in a variety of domains. The ability to automatically assess subject movement in videos that were captured by affordable devices, such as Kinect came…
Relevance DetectionDoes Multi-Task Learning Always Help?: An Evaluation on Health Informatics
Multi-Task Learning (MTL) has been an attractive approach to deal with limited labeled datasets or leverage related tasks, for a variety of NLP problems. We examine the benefit of MTL for three specific pairs of health i…
ClassificationGeneral ClassificationMulti-Task LearningRelevance DetectionA Simple Approach to Learn Polysemous Word Embeddings
Many NLP applications require disambiguating polysemous words. Existing methods that learn polysemous word vector representations involve first detecting various senses and optimizing the sense-specific embeddings separa…
Relevance DetectionRepresentation LearningWord EmbeddingsWord Sense Induction+1The Promise of Premise: Harnessing Question Premises in Visual Question Answering
In this paper, we make a simple observation that questions about images often contain premises - objects and relationships implied by the question - and that reasoning about premises can help Visual Question Answering (V…
Question AnsweringRelevance DetectionVisual Question AnsweringVisual Question Answering (VQA)