Papers Sentence Classification
“Sentence Classification” 태그가 달린 논문 313편 · 필터 해제
Joint Text-Audio Alignment for EEG-to-Text Decoding in Chinese Speech Production and Perception
Decoding speech information directly from scalp electroencephalography (EEG) into text provides a potential non-invasive neural communication pathway for individuals with severe speech and motor impairments. Compared wit…
Sentence ClassificationContrastive LearningTo Redact, or not to Redact? A Local LLM Approach to Deliberative Process Privilege Classification
Government transparency laws, like the Freedom of Information (FOIA) acts in the United States and United Kingdom, and the Woo (Open Government Act) in the Netherlands, grant citizens the right to directly request docume…
Sensitivity ClassificationSentence ClassificationMax-pooling Network Revisited: Analyzing the Role of Semantic Probability in Multiple Instance Learning for Hallucination Detection
Hallucination detection has become increasingly important for improving the reliability of large language models (LLMs). Recently, hybrid approaches such as HaMI, which combine semantic consistency with internal model st…
Multiple Instance LearningSentence ClassificationSemantic SimilarityWhy Better Cross-Lingual Alignment Fails for Better Cross-Lingual Transfer: Case of Encoders
Better cross-lingual alignment is often assumed to yield better cross-lingual transfer. However, explicit alignment techniques -- despite increasing embedding similarity -- frequently fail to improve token-level downstre…
Sentence ClassificationCross-Lingual TransferPOS TaggingLAMUS: A Large-Scale Corpus for Legal Argument Mining from U.S. Caselaw using LLMs
Legal argument mining aims to identify and classify the functional components of judicial reasoning, such as facts, issues, rules, analysis, and conclusions. Progress in this area is limited by the lack of large-scale, h…
Sentence ClassificationArgument MiningTo Predict or Not to Predict? Towards reliable uncertainty estimation in the presence of noise
This study examines the role of uncertainty estimation (UE) methods in multilingual text classification under noisy and non-topical conditions. Using a complex-vs-simple sentence classification task across several langua…
Sentence ClassificationText ClassificationConvolutional Lie Operator for Sentence Classification
Traditional Convolutional Neural Networks have been successful in capturing local, position-invariant features in text, but their capacity to model complex transformation within language can be further explored. In this …
Sentence ClassificationAdapting Multilingual Models to Code-Mixed Tasks via Model Merging
We study model merging as a practical alternative to conventional adaptation strategies for code-mixed NLP. Starting from a multilingual base model, we: (i) perform continued pre-training (CPT) on unlabeled code-mixed te…
Sentence ClassificationAdvances in Pre-trained Language Models for Domain-Specific Text Classification: A Systematic Review
The exponential increase in scientific literature and online information necessitates efficient methods for extracting knowledge from textual data. Natural language processing (NLP) plays a crucial role in addressing thi…
Sentence ClassificationText ClassificationKAConvText: Novel Approach to Burmese Sentence Classification using Kolmogorov-Arnold Convolution
This paper presents the first application of Kolmogorov-Arnold Convolution for Text (KAConvText) in sentence classification, addressing three tasks: imbalanced binary hate speech detection, balanced multiclass news class…
Sentence ClassificationLanguage IdentificationHate Speech DetectionNews ClassificationA Personalized Conversational Benchmark: Towards Simulating Personalized Conversations
We present PersonaConvBench, a large-scale benchmark for evaluating personalized reasoning and generation in multi-turn conversations with large language models (LLMs). Unlike existing work that focuses on either persona…
SentenceSentence ClassificationSentiment AnalysisSentiment Classification+1Tougher Text, Smarter Models: Raising the Bar for Adversarial Defence Benchmarks
Recent advancements in natural language processing have highlighted the vulnerability of deep learning models to adversarial attacks. While various defence mechanisms have been proposed, there is a lack of comprehensive …
Adversarial RobustnessBenchmarkingNatural Language InferenceParaphrase Identification+2Consolidating and Developing Benchmarking Datasets for the Nepali Natural Language Understanding Tasks
The Nepali language has distinct linguistic features, especially its complex script (Devanagari script), morphology, and various dialects, which pose a unique challenge for natural language processing (NLP) evaluation. W…
BenchmarkingNatural Language InferenceNatural Language UnderstandingSentence+1Cyber-Attack Technique Classification Using Two-Stage Trained Large Language Models
Understanding the attack patterns associated with a cyberattack is crucial for comprehending the attacker's behaviors and implementing the right mitigation measures. However, majority of the information regarding new att…
ClassificationSentenceSentence ClassificationMulti-label Sequential Sentence Classification via Large Language Model
Sequential sentence classification (SSC) in scientific publications is crucial for supporting downstream tasks such as fine-grained information retrieval and extractive summarization. However, current SSC methods are con…
Contrastive LearningExtractive SummarizationIn-Context LearningInformation Retrieval+7Analyzing the Evolution of Graphs and Texts
With the recent advance of representation learning algorithms on graphs (e.g., DeepWalk/GraphSage) and natural languages (e.g., Word2Vec/BERT) , the state-of-the art models can even achieve human-level performance over m…
Representation LearningSentence ClassificationLogistic Regression makes small LLMs strong and explainable "tens-of-shot" classifiers
For simple classification tasks, we show that users can benefit from the advantages of using small, local, generative language models instead of large commercial models without a trade-off in performance or introducing e…
ClassificationregressionSentenceSentence ClassificationConstructing the CORD-19 Vaccine Dataset
We introduce new dataset 'CORD-19-Vaccination' to cater to scientists specifically looking into COVID-19 vaccine-related research. This dataset is extracted from CORD-19 dataset [Wang et al., 2020] and augmented with new…
Question AnsweringSentenceSentence ClassificationLarge Language Models for Anomaly Detection in Computational Workflows: from Supervised Fine-Tuning to In-Context Learning
Anomaly detection in computational workflows is critical for ensuring system reliability and security. However, traditional rule-based methods struggle to detect novel anomalies. This paper leverages large language model…
Anomaly DetectionIn-Context LearningSentenceSentence ClassificationMMM: Multilingual Mutual Reinforcement Effect Mix Datasets & Test with Open-domain Information Extraction Large Language Models
The Mutual Reinforcement Effect (MRE) represents a promising avenue in information extraction and multitasking research. Nevertheless, its applicability has been constrained due to the exclusive availability of MRE mix d…
Language ModelingLanguage ModellingLarge Language Modelnamed-entity-recognition+5