Papers Token Classification
“Token Classification” 태그가 달린 논문 99편 · 필터 해제
Interactive DualChecker for Mitigating Hallucinations in Distilling Large Language Models
Large Language Models (LLMs) have demonstrated exceptional capabilities across various machine learning (ML) tasks. Given the high costs of creating annotated datasets for supervised learning, LLMs offer a valuable alter…
In-Context LearningKnowledge Distillationtoken-classificationToken Classification+1Acquiring Bidirectionality via Large and Small Language Models
Using token representation from bidirectional language models (LMs) such as BERT is still a widely used approach for token-classification tasks. Even though there exist much larger unidirectional LMs such as Llama-2, the…
Few-Shot Learningnamed-entity-recognitionNamed Entity Recognitiontoken-classification+1MemeMind at ArAIEval Shared Task: Spotting Persuasive Spans in Arabic Text with Persuasion Techniques Identification
This paper focuses on detecting propagandistic spans and persuasion techniques in Arabic text from tweets and news paragraphs. Each entry in the dataset contains a text sample and corresponding labels that indicate the s…
Propaganda detectiontoken-classificationToken ClassificationLeveraging Encoder-only Large Language Models for Mobile App Review Feature Extraction
Mobile app review analysis presents unique challenges due to the low quality, subjective bias, and noisy content of user-generated documents. Extracting features from these reviews is essential for tasks such as feature …
Sentiment Analysistoken-classificationToken ClassificationLooks can be Deceptive: Distinguishing Repetition Disfluency from Reduplication
Reduplication and repetition, though similar in form, serve distinct linguistic purposes. Reduplication is a deliberate morphological process used to express grammatical, semantic, or pragmatic nuances, while repetition …
token-classificationToken ClassificationDeep Content Understanding Toward Entity and Aspect Target Sentiment Analysis on Foundation Models
Introducing Entity-Aspect Sentiment Triplet Extraction (EASTE), a novel Aspect-Based Sentiment Analysis (ABSA) task which extends Target-Aspect-Sentiment Detection (TASD) by separating aspect categories (e.g., food#quali…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Aspect Sentiment Triplet ExtractionFew-Shot Learning+5In-Context Learning on a Budget: A Case Study in Token Classification
Few shot in-context learning (ICL) typically assumes access to large annotated training sets. However, in many real world scenarios, such as domain adaptation, there is only a limited budget to annotate a small number of…
Domain AdaptationIn-Context Learningnamed-entity-recognitionNamed Entity Recognition+4BEADs: Bias Evaluation Across Domains
Recent advancements in large language models (LLMs) have greatly enhanced natural language processing (NLP) applications. Nevertheless, these models often inherit biases from their training data. Despite the availability…
BenchmarkingBias DetectionClassificationtext-classification+4A Framework for Leveraging Partially-Labeled Data for Product Attribute-Value Identification
In the e-commerce domain, the accurate extraction of attribute-value pairs (e.g., Brand: Apple) from product titles and user search queries is crucial for enhancing search and recommendation systems. A major challenge wi…
AttributeNERRecommendation Systemstoken-classification+1What's Mine becomes Yours: Defining, Annotating and Detecting Context-Dependent Paraphrases in News Interview Dialogs
Best practices for high conflict conversations like counseling or customer support almost always include recommendations to paraphrase the previous speaker. Although paraphrase classification has received widespread atte…
In-Context Learningtoken-classificationToken ClassificationEvent Extraction in Basque: Typologically motivated Cross-Lingual Transfer-Learning Analysis
Cross-lingual transfer-learning is widely used in Event Extraction for low-resource languages and involves a Multilingual Language Model that is trained in a source language and applied to the target language. This paper…
Cross-Lingual TransferEvent ExtractionLanguage Modellingtoken-classification+2TM-TREK at SemEval-2024 Task 8: Towards LLM-Based Automatic Boundary Detection for Human-Machine Mixed Text
With the increasing prevalence of text generated by large language models (LLMs), there is a growing concern about distinguishing between LLM-generated and human-written texts in order to prevent the misuse of LLMs, such…
Boundary DetectionText Detectiontoken-classificationToken ClassificationEvaluating Shortest Edit Script Methods for Contextual Lemmatization
Modern contextual lemmatizers often rely on automatically induced Shortest Edit Scripts (SES), namely, the number of edit operations to transform a word form into its lemma. In fact, different methods of computing SES ha…
LEMMALemmatizationtoken-classificationToken ClassificationLLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression
This paper focuses on task-agnostic prompt compression for better generalizability and efficiency. Considering the redundancy in natural language, existing approaches compress prompts by removing tokens or lexical units …
GSM8KLanguage ModellingText Compressiontoken-classification+1Embedded Named Entity Recognition using Probing Classifiers
Streaming text generation has become a common way of increasing the responsiveness of language model powered applications, such as chat assistants. At the same time, extracting semantic information from generated text is…
DecoderFact CheckingLanguage ModelingLanguage Modelling+8Evaluating Named Entity Recognition: A comparative analysis of mono- and multilingual transformer models on a novel Brazilian corporate earnings call transcripts dataset
Since 2018, when the Transformer architecture was introduced, Natural Language Processing has gained significant momentum with pre-trained Transformer-based models that can be fine-tuned for various tasks. Most models ar…
named-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)NER+3Ignore Me But Don't Replace Me: Utilizing Non-Linguistic Elements for Pretraining on the Cybersecurity Domain
Cybersecurity information is often technically complex and relayed through unstructured text, making automation of cyber threat intelligence highly challenging. For such text domains that involve high levels of expertise…
Language ModelingLanguage Modellingtoken-classificationToken ClassificationVNLP: Turkish NLP Package
In this work, we present VNLP: the first dedicated, complete, open-source, well-documented, lightweight, production-ready, state-of-the-art Natural Language Processing (NLP) package for the Turkish language. It contains …
Morphological Analysisnamed-entity-recognitionNamed Entity RecognitionPart-Of-Speech Tagging+6Instruction Fine-Tuning: Does Prompt Loss Matter?
We present a novel study analyzing the effects of various prompt loss token weights (PLW) for supervised instruction fine-tuning (SIFT). While prompt-masking (PLW = 0) is common for SIFT, some fine-tuning APIs support fr…
Multiple-choicetoken-classificationToken ClassificationArabic Text Diacritization In The Age Of Transfer Learning: Token Classification Is All You Need
Automatic diacritization of Arabic text involves adding diacritical marks (diacritics) to the text. This task poses a significant challenge with noteworthy implications for computational processing and comprehension. In …
AllArabic Text Diacritizationtoken-classificationToken Classification+1