Papers Sentence Classification
“Sentence Classification” 태그가 달린 논문 313편 · 필터 해제
Healing Powers of BERT: How Task-Specific Fine-Tuning Recovers Corrupted Language Models
Language models like BERT excel at sentence classification tasks due to extensive pre-training on general data, but their robustness to parameter corruption is unexplored. To understand this better, we look at what happe…
Language ModelingLanguage ModellingSentenceSentence ClassificationEstimating the Level of Dialectness Predicts Interannotator Agreement in Multi-dialect Arabic Datasets
On annotating multi-dialect Arabic datasets, it is common to randomly assign the samples across a pool of native Arabic speakers. Recent analyses recommended routing dialectal samples to native speakers of their respecti…
SentenceSentence ClassificationSoftware Mention Recognition with a Three-Stage Framework Based on BERTology Models at SOMD 2024
This paper describes our systems for the sub-task I in the Software Mention Detection in Scholarly Publications shared-task. We propose three approaches leveraging different pre-trained language models (BERT, SciBERT, an…
named-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)NER+3Multi-Granularity Guided Fusion-in-Decoder
In Open-domain Question Answering (ODQA), it is essential to discern relevant contexts as evidence and avoid spurious ones among retrieved results. The model architecture that uses concatenated multiple contexts in the d…
DecoderMulti-Task LearningNatural QuestionsOpen-Domain Question Answering+6Classification and Clustering of Sentence-Level Embeddings of Scientific Articles Generated by Contrastive Learning
Scientific articles are long text documents organized into sections, each describing aspects of the research. Analyzing scientific production has become progressively challenging due to the increase in the number of avai…
ArticlesClusteringContrastive LearningSentence+2Neural Architecture Search for Sentence Classification with BERT
Pre training of language models on large text corpora is common practice in Natural Language Processing. Following, fine tuning of these models is performed to achieve the best results on a variety of tasks. In this pape…
AutoMLClassificationNeural Architecture SearchSentence+1Task-Agnostic Detector for Insertion-Based Backdoor Attacks
Textual backdoor attacks pose significant security threats. Current detection approaches, typically relying on intermediate feature representation or reconstructing potential triggers, are task-specific and less effectiv…
named-entity-recognitionNamed Entity RecognitionQuestion AnsweringSentence+1Detecting AI-Generated Sentences in Human-AI Collaborative Hybrid Texts: Challenges, Strategies, and Insights
This study explores the challenge of sentence-level AI-generated text detection within human-AI collaborative hybrid texts. Existing studies of AI-generated text detection for hybrid texts often rely on synthetic dataset…
Boundary DetectionSentenceSentence ClassificationText Detection+1How do Large Language Models Learn In-Context? Query and Key Matrices of In-Context Heads are Two Towers for Metric Learning
We investigate the mechanism of in-context learning (ICL) on sentence classification tasks with semantically-unrelated labels ("foo"/"bar"). We find intervening in only 1\% heads (named "in-context heads") significantly …
In-Context LearningMetric LearningPositionSentence+1Evaluation of Google's Voice Recognition and Sentence Classification for Health Care Applications
This study examined the use of voice recognition technology in perioperative services (Periop) to enable Periop staff to record workflow milestones using mobile technology. The use of mobile technology to improve patient…
SentenceSentence ClassificationLSTM-based Deep Neural Network With A Focus on Sentence Representation for Sequential Sentence Classification in Medical Scientific Abstracts
The Sequential Sentence Classification task within the domain of medical abstracts, termed as SSC, involves the categorization of sentences into pre-defined headings based on their roles in conveying critical information…
SentenceSentence ClassificationSentence EmbeddingSentence-Embedding+1Do We Need Language-Specific Fact-Checking Models? The Case of Chinese
This paper investigates the potential benefits of language-specific fact-checking models, focusing on the case of Chinese. We first demonstrate the limitations of translation-based methods and multilingual large language…
Evidence SelectionFact CheckingMisinformationSentence+2Application of LLM Agents in Recruitment: A Novel Framework for Resume Screening
The automation of resume screening is a crucial aspect of the recruitment process in organizations. Automated resume screening systems often encompass a range of natural language processing (NLP) tasks. This paper introd…
Decision MakingSentenceSentence ClassificationSECNN: Squeeze-and-Excitation Convolutional Neural Network for Sentence Classification
Sentence classification is one of the basic tasks of natural language processing. Convolution neural network (CNN) has the ability to extract n-grams features through convolutional filters and capture local correlations …
ClassificationSentenceSentence ClassificationCan Large Language Models Follow Concept Annotation Guidelines? A Case Study on Scientific and Financial Domains
Although large language models (LLMs) exhibit remarkable capacity to leverage in-context demonstrations, it is still unclear to what extent they can learn new concepts or facts from ground-truth labels. To address this q…
counterfactualSentenceSentence ClassificationAspect-based Meeting Transcript Summarization: A Two-Stage Approach with Weak Supervision on Sentence Classification
Aspect-based meeting transcript summarization aims to produce multiple summaries, each focusing on one aspect of content in a meeting transcript. It is challenging as sentences related to different aspects can mingle tog…
SentenceSentence ClassificationAdaSent: Efficient Domain-Adapted Sentence Embeddings for Few-Shot Classification
Recent work has found that few-shot sentence classification based on pre-trained Sentence Encoders (SEs) is efficient, robust, and effective. In this work, we investigate strategies for domain-specialization in the conte…
ClassificationLanguage ModellingSentenceSentence Classification+3Robustifying Language Models with Test-Time Adaptation
Large-scale language models achieved state-of-the-art performance over a number of language tasks. However, they fail on adversarial language examples, which are sentences optimized to fool the language models but with s…
Language ModelingLanguage ModellingSentenceSentence Classification+1On the Dimensionality of Sentence Embeddings
Learning sentence embeddings is a fundamental problem in natural language processing. While existing research primarily focuses on enhancing the quality of sentence embeddings, the exploration of sentence embedding dimen…
Representation LearningSentenceSentence ClassificationSentence Embedding+3Detecting Sexual Content at the Sentence Level in First Millennium Latin Texts
In this study, we propose to evaluate the use of deep learning methods for semantic classification at the sentence level to accelerate the process of corpus building in the field of humanities and linguistics, a traditio…
SentenceSentence Classification