Papers Token Classification
“Token Classification” 태그가 달린 논문 99편 · 필터 해제
Entity or Relation Embeddings? An Analysis of Encoding Strategies for Relation Extraction
Relation extraction is essentially a text classification problem, which can be tackled by fine-tuning a pre-trained language model (LM). However, a key challenge arises from the fact that relation extraction cannot strai…
Entity EmbeddingsLanguage ModelingLanguage ModellingRelation+5Lazy-k: Decoding for Constrained Token Classification
We explore the possibility of improving probabilistic models in structured prediction. Specifically, we combine the models with constrained decoding approaches in the context of token classification for information extra…
ClassificationStructured Predictiontoken-classificationToken ClassificationReading Order Matters: Information Extraction from Visually-rich Documents by Token Path Prediction
Recent advances in multimodal pre-trained models have significantly improved information extraction from visually-rich documents (VrDs), in which named entity recognition (NER) is treated as a sequence-labeling task of p…
Entity LinkingKey Information ExtractionKey-value Pair Extractionnamed-entity-recognition+9One For All & All For One: Bypassing Hyperparameter Tuning with Model Averaging For Cross-Lingual Transfer
Multilingual language models enable zero-shot cross-lingual transfer (ZS-XLT): fine-tuned on sizable source-language task data, they perform the task in target languages without labeled instances. The effectiveness of ZS…
AllCross-Lingual TransferModel SelectionNER+3Label Supervised LLaMA Finetuning
The recent success of Large Language Models (LLMs) has gained significant attention in both academia and industry. Substantial efforts have been made to enhance the zero- and few-shot generalization capabilities of open-…
GPUnamed-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)+7Revisiting Supertagging for Faster HPSG Pasing
We present new supertaggers trained on English grammar-based treebanks and test the effects of the best tagger on parsing speed and accuracy. The treebanks are produced automatically by large manually built grammars and …
token-classificationToken ClassificationDetecting Spells in Fantasy Literature with a Transformer Based Artificial Intelligence
Transformer architectures and models have made significant progress in language-based tasks. In this area, is BERT one of the most widely used and freely available transformer architecture. In our work, we use BERT for c…
token-classificationToken ClassificationNBIAS: A Natural Language Processing Framework for Bias Identification in Text
Bias in textual data can lead to skewed interpretations and outcomes when the data is used. These biases could perpetuate stereotypes, discrimination, or other forms of unfair treatment. An algorithm trained on biased da…
token-classificationToken ClassificationMultimodal Document Analytics for Banking Process Automation
Traditional banks face increasing competition from FinTechs in the rapidly evolving financial ecosystem. Raising operational efficiency is vital to address this challenge. Our study aims to improve the efficiency of docu…
token-classificationToken ClassificationRetrieval Augmented Generation using Engineering Design Knowledge
Aiming to support Retrieval Augmented Generation (RAG) in the design process, we present a method to identify explicit, engineering design facts - {head entity :: relationship :: tail entity} from patented artefact descr…
Common Sense ReasoningEdge ClassificationKnowledge GraphsRAG+5Free Lunch: Robust Cross-Lingual Transfer via Model Checkpoint Averaging
Massively multilingual language models have displayed strong performance in zero-shot (ZS-XLT) and few-shot (FS-XLT) cross-lingual transfer setups, where models fine-tuned on task data in a source language are transferre…
Cross-Lingual TransferModel SelectionNERPOS+2People and Places of Historical Europe: Bootstrapping Annotation Pipeline and a New Corpus of Named Entities in Late Medieval Texts
Although pre-trained named entity recognition (NER) models are highly accurate on modern corpora, they underperform on historical texts due to differences in language OCR errors. In this work, we develop a new NER corpus…
Information Retrievalnamed-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)+5Transfer-Free Data-Efficient Multilingual Slot Labeling
Slot labeling (SL) is a core component of task-oriented dialogue (ToD) systems, where slots and corresponding values are usually language-, task- and domain-specific. Therefore, extending the system to any new language-d…
Contrastive LearningCross-Lingual TransferSentencetoken-classification+1Persian Typographical Error Type Detection Using Deep Neural Networks on Algorithmically-Generated Misspellings
Spelling correction is a remarkable challenge in the field of natural language processing. The objective of spelling correction tasks is to recognize and rectify spelling errors automatically. The development of applicat…
Spelling Correctiontoken-classificationToken ClassificationComparing Variation in Tokenizer Outputs Using a Series of Problematic and Challenging Biomedical Sentences
Background & Objective: Biomedical text data are increasingly available for research. Tokenization is an initial step in many biomedical text mining pipelines. Tokenization is the process of parsing an input biomedical s…
Sentencetoken-classificationToken ClassificationFrom Zero to Hero: Harnessing Transformers for Biomedical Named Entity Recognition in Zero- and Few-shot Contexts
Supervised named entity recognition (NER) in the biomedical domain depends on large sets of annotated texts with the given named entities. The creation of such datasets can be time-consuming and expensive, while extracti…
few-shot-nerFew-shot NERnamed-entity-recognitionNamed Entity Recognition+4Technical Report: Impact of Position Bias on Language Models in Token Classification
Language Models (LMs) have shown state-of-the-art performance in Natural Language Processing (NLP) tasks. Downstream tasks such as Named Entity Recognition (NER) or Part-of-Speech (POS) tagging are known to suffer from d…
named-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)NER+6Information Extraction from Documents: Question Answering vs Token Classification in real-world setups
Research in Document Intelligence and especially in Document Key Information Extraction (DocKIE) has been mainly solved as Token Classification problem. Recent breakthroughs in both natural language processing (NLP) and …
ClassificationFew-Shot LearningKey Information ExtractionMachine Reading Comprehension+5ClassBases at CASE-2022 Multilingual Protest Event Detection Tasks: Multilingual Protest News Detection and Automatically Replicating Manually Created Event Datasets
In this report, we describe our ClassBases submissions to a shared task on multilingual protest event detection. For the multilingual protest news detection, we participated in subtask-1, subtask-2, and subtask-4, which …
ClassificationDocument ClassificationEvent DetectionSentence+3Comparison Study Between Token Classification and Sequence Classification In Text Classification
Unsupervised Machine Learning techniques have been applied to Natural Language Processing tasks and surpasses the benchmarks such as GLUE with great success. Building language models approach achieves good results in one…
ClassificationLanguage ModelingLanguage ModellingMasked Language Modeling+4