Papers Sentence Classification
“Sentence Classification” 태그가 달린 논문 313편 · 필터 해제
PcMSP: A Dataset for Scientific Action Graphs Extraction from Polycrystalline Materials Synthesis Procedure Text
Scientific action graphs extraction from materials synthesis procedures is important for reproducible research, machine automation, and material prediction. But the lack of annotated data has hindered progress in this fi…
ArticlesNamed Entity RecognitionNamed Entity Recognition (NER)Relation Classification+2Finding Dataset Shortcuts with Grammar Induction
Many NLP datasets have been found to contain shortcuts: simple decision rules that achieve surprisingly high accuracy. However, it is difficult to discover shortcuts automatically. Prior work on automatic shortcut detect…
DiagnosticSentenceSentence ClassificationSynergy with Translation Artifacts for Training and Inference in Multilingual Tasks
Translation has played a crucial role in improving the performance on multilingual tasks: (1) to generate the target language data from the source language data for training and (2) to generate the source language data f…
SentenceSentence ClassificationTranslationMulti-granularity Argument Mining in Legal Texts
In this paper, we explore legal argument mining using multiple levels of granularity. Argument mining has usually been conceptualized as a sentence classification problem. In this work, we conceptualize argument mining a…
Argument MiningClassificationSentenceSentence Classification+2Shapley Head Pruning: Identifying and Removing Interference in Multilingual Transformers
Multilingual transformer-based models demonstrate remarkable zero and few-shot transfer across languages by learning and reusing language-agnostic features. However, as a fixed-size model acquires more languages, its per…
SentenceSentence ClassificationMetaphorical Paraphrase Generation: Feeding Metaphorical Language Models with Literal Texts
This study presents a new approach to metaphorical paraphrase generation by masking literal tokens of literal sentences and unmasking them with metaphorical language models. Unlike similar studies, the proposed algorithm…
Data AugmentationParaphrase GenerationSentenceSentence ClassificationNSP-BERT: A Prompt-based Few-Shot Learner through an Original Pre-training Task —— Next Sentence Prediction
Using prompts to utilize language models to perform various downstream tasks, also known as prompt-based learning or prompt-learning, has lately gained significant success in comparison to the pre-train and fine-tune par…
Entity LinkingLanguage ModelingLanguage ModellingPrompt Learning+2Effective Data Augmentation for Sentence Classification Using One VAE per Class
In recent years, data augmentation has become an important field of machine learning. While images can use simple techniques such as cropping or rotating, textual data augmentation needs more complex manipulations to ens…
Binary ClassificationData AugmentationSentenceSentence ClassificationCoordination Generation via Synchronized Text-Infilling
Generating synthetic data for supervised learning from large-scale pre-trained language models has enhanced performances across several NLP tasks, especially in low-resource scenarios. In particular, many studies of data…
Data AugmentationSentenceSentence ClassificationText InfillingMaking Parameter-efficient Tuning More Efficient: A Unified Framework for Classification Tasks
Large pre-trained language models (PLMs) have demonstrated superior performance in industrial applications. Recent studies have explored parameter-efficient PLM tuning, which only updates a small amount of task-specific …
ClassificationLanguage ModelingLanguage ModellingSentence+3Query-focused Extractive Summarisation for Biomedical and COVID-19 Complex Question Answering
This paper presents Macquarie University's participation to the two most recent BioASQ Synergy Tasks (as per June 2022), and to the BioASQ10 Task~B (BioASQ10b), Phase~B. In these tasks, participating systems are expected…
Question AnsweringRe-RankingRetrievalSentence+1Figure Descriptive Text Extraction using Ontological Representation
Experimental research publications provide figure form resources including graphs, charts, and any type of images to effectively support and convey methods and results. To describe figures, authors add captions, which ar…
ArticlesDescriptiveSentenceSentence ClassificationConstruction of English Resume Corpus and Test with Pre-trained Language Models
Information extraction(IE) has always been one of the essential tasks of NLP. Moreover, one of the most critical application scenarios of information extraction is the information extraction of resumes. Constructed text …
ClassificationSentenceSentence ClassificationAttentionSiteDTI: an interpretable graph-based model for drug-target interaction prediction using NLP sentence-level relation classification
In this study, we introduce an interpretable graph-based deep learning prediction model, AttentionSiteDTI, which utilizes protein binding sites along with a self-attention mechanism to address the problem of drug–target …
Drug DiscoveryRelation ClassificationSentenceSentence ClassificationPlacing (Historical) Facts on a Timeline: A Classification cum Coref Resolution Approach
A timeline provides one of the most effective ways to visualize the important historical facts that occurred over a period of time, presenting the insights that may not be so apparent from reading the equivalent informat…
coreference-resolutionCoreference ResolutionEvent Coreference ResolutionSentence+1SynWMD: Syntax-aware Word Mover's Distance for Sentence Similarity Evaluation
Word Mover's Distance (WMD) computes the distance between words and models text similarity with the moving cost between words in two text sequences. Yet, it does not offer good performance in sentence similarity evaluati…
Semantic SimilaritySemantic Textual SimilaritySentenceSentence Classification+3Towards Classification of Legal Pharmaceutical Text using GAN-BERT
Pharmaceutical text classification is an important area of research for commercial and research institutions working in the pharmaceutical domain. Addressing this task is challenging due to the need of expert verified la…
ClassificationSentenceSentence ClassificationSpecificity+2Composing Structure-Aware Batches for Pairwise Sentence Classification
Identifying the relation between two sentences requires datasets with pairwise annotations. In many cases, these datasets contain instances that are annotated multiple times as part of different pairs. They constitute a …
ClassificationLanguage ModelingLanguage ModellingSentence+1DMix: Adaptive Distance-aware Interpolative Mixup
Interpolation-based regularisation methods such as Mixup, which generate virtual training samples, have proven to be effective for various tasks and modalities.We extend Mixup and propose DMix, an adaptive distance-aware…
Data AugmentationDiversitySentenceSentence ClassificationDataMUX: Data Multiplexing for Neural Networks
In this paper, we introduce data multiplexing (DataMUX), a technique that enables deep neural networks to process multiple inputs simultaneously using a single compact representation. DataMUX demonstrates that neural net…
image-classificationImage Classificationnamed-entity-recognitionNamed Entity Recognition+4