Papers Citation Prediction
“Citation Prediction” 태그가 달린 논문 24편 · 필터 해제
CiteBART: Learning to Generate Citations for Local Citation Recommendation
Local citation recommendation (LCR) suggests a set of papers for a citation placeholder within a given context. The task has evolved as generative approaches have become more promising than the traditional pre-fetch and …
Citation PredictionCitation RecommendationCitation worthinessHallucinationMethods for Legal Citation Prediction in the Age of LLMs: An Australian Law Case Study
In recent years, Large Language Models (LLMs) have shown great potential across a wide range of legal tasks. Despite these advances, mitigating hallucination remains a significant challenge, with state-of-the-art LLMs st…
Citation PredictionHallucinationRetrievalDynamic technology impact analysis: A multi-task learning approach to patent citation prediction
Machine learning (ML) models are valuable tools for analyzing the impact of technology using patent citation information. However, existing ML-based methods often struggle to account for the dynamic nature of the technol…
Citation PredictionMulti-Task LearningHLM-Cite: Hybrid Language Model Workflow for Text-based Scientific Citation Prediction
Citation networks are critical in modern science, and predicting which previous papers (candidates) will a new paper (query) cite is a critical problem. However, the roles of a paper's citations vary significantly, rangi…
Binary ClassificationCitation PredictionLanguage ModelingLanguage Modelling+1PaECTER: Patent-level Representation Learning using Citation-informed Transformers
PaECTER is a publicly available, open-source document-level encoder specific for patents. We fine-tune BERT for Patents with examiner-added citation information to generate numerical representations for patent documents.…
Citation PredictionLanguage ModelingLanguage ModellingRepresentation Learning+2Citation-Enhanced Generation for LLM-based Chatbots
Large language models (LLMs) exhibit powerful general intelligence across diverse scenarios, including their integration into chatbots. However, a vital challenge of LLM-based chatbots is that they may produce hallucinat…
ChatbotCitation PredictionHallucinationNatural Language Inference+2When Large Language Models Meet Citation: A Survey
Citations in scholarly work serve the essential purpose of acknowledging and crediting the original sources of knowledge that have been incorporated or referenced. Depending on their surrounding textual context, these ci…
Citation PredictionCitation RecommendationSurveyEncoding Multi-Domain Scientific Papers by Ensembling Multiple CLS Tokens
Many useful tasks on scientific documents, such as topic classification and citation prediction, involve corpora that span multiple scientific domains. Typically, such tasks are accomplished by representing the text with…
Citation PredictionTopic ClassificationModeling Dynamic Heterogeneous Graph and Node Importance for Future Citation Prediction
Accurate citation count prediction of newly published papers could help editors and readers rapidly figure out the influential papers in the future. Though many approaches are proposed to predict a paper's future citatio…
Citation PredictionNetwork EmbeddingPrototype-Based Interpretability for Legal Citation Prediction
Deep learning has made significant progress in the past decade, and demonstrates potential to solve problems with extensive social impact. In high-stakes decision making areas such as law, experts often require interpret…
Citation PredictionDecision MakingPredictionPre-training Multi-task Contrastive Learning Models for Scientific Literature Understanding
Scientific literature understanding tasks have gained significant attention due to their potential to accelerate scientific discovery. Pre-trained language models (LMs) have shown effectiveness in these tasks, especially…
Citation PredictionContrastive LearningMixture-of-Expertsscientific discoveryGalactica: A Large Language Model for Science
Information overload is a major obstacle to scientific progress. The explosive growth in scientific literature and data has made it ever harder to discover useful insights in a large mass of information. Today scientific…
AnachronismsBias DetectionCitation PredictionClassification+21No 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+11Neighborhood Contrastive Learning for Scientific Document Representations with Citation Embeddings
Learning scientific document representations can be substantially improved through contrastive learning objectives, where the challenge lies in creating positive and negative training samples that encode the desired simi…
Citation PredictionContrastive LearningDocument ClassificationDocument Embedding+3Semantic Analysis for Automated Evaluation of the Potential Impact of Research Articles
Can the analysis of the semantics of words used in the text of a scientific paper predict its future impact measured by citations? This study details examples of automated text classification that achieved 80% success ra…
ArticlesCitation PredictionGeneral Classificationtext-classification+1BEIR: 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+11Structured Citation Trend Prediction Using Graph Neural Networks
Academic citation graphs represent citation relationships between publications across the full range of academic fields. Top cited papers typically reveal future trends in their corresponding domains which is of importan…
BIG-bench Machine LearningCitation PredictionPredictionSChuBERT: Scholarly Document Chunks with BERT-encoding boost Citation Count Prediction
Predicting the number of citations of scholarly documents is an upcoming task in scholarly document processing. Besides the intrinsic merit of this information, it also has a wider use as an imperfect proxy for quality w…
Citation PredictionPredictionLongitudinal Citation Prediction using Temporal Graph Neural Networks
Citation count prediction is the task of predicting the number of citations a paper has gained after a period of time. Prior work viewed this as a static prediction task. As papers and their citations evolve over time, c…
Citation PredictionPrediction