Papers with Code 아카이브
Text Classification
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Text Classification is the task of assigning a sentence or document an appropriate category. The categories depend on the chosen dataset and can range from topics.
Text Classification problems include emotion classification, news classification, citation intent classification, among others. Benchmark datasets for evaluating text classification capabilities include GLUE, AGNews, among others.
In recent years, deep learning techniques like XLNet and RoBERTa have attained some of the biggest performance jumps for text classification problems.
<span style="color:grey; opacity: 0.6">( Image credit: Text Classification Algorithms: A Survey )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/kmc0207/Stableprompt
공식 코드StablePrompt: Automatic Prompt Tuning using Reinforcement Learning for Large Language Models
https://github.com/knowledgetechnologyuhh/drill
공식 코드DRILL: Dynamic Representations for Imbalanced Lifelong Learning
https://github.com/koalaGreener/Character-level-Convolutional-Network-for-Text-Classification-Applied-to-Chinese-Corpus
공식 코드Character-level Convolutional Network for Text Classification Applied to Chinese Corpus
https://github.com/kobayashikanna01/plms_are_lifelong_learners
공식 코드Can BERT Refrain from Forgetting on Sequential Tasks? A Probing Study
https://github.com/kochsnow/distribution-matching-rationality
공식 코드https://github.com/komeijiforce/cotam
공식 코드Controllable Data Augmentation for Few-Shot Text Mining with Chain-of-Thought Attribute Manipulation
https://github.com/komeijiforce/incubator
공식 코드Incubating Text Classifiers Following User Instruction with Nothing but LLM
https://github.com/kongds/LightXML
공식 코드https://github.com/kongds/hbgl
공식 코드Exploiting Global and Local Hierarchies for Hierarchical Text Classification
https://github.com/korhansevinc/LatentG-Loss
공식 코드A new training approach for text classification in Mental Health: LatentGLoss
https://github.com/kpriyanshu256/WNUT-2020-Task-2
공식 코드https://github.com/krzysztoffiok/TextGuide
공식 코드https://github.com/kuleshov-group/llmtools
공식 코드ModuLoRA: Finetuning 2-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers
https://github.com/kuleshov-group/modulora-experiment
공식 코드ModuLoRA: Finetuning 2-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers
https://github.com/kumar-shridhar/Know-Your-Intent
공식 코드Subword Semantic Hashing for Intent Classification on Small Datasets
https://github.com/kundajelab/deeplift
공식 코드Towards better understanding of gradient-based attribution methods for Deep Neural Networks
https://github.com/kushal2000/Dravidian-Offensive-Language-Identification
공식 코드indicnlp@kgp at DravidianLangTech-EACL2021: Offensive Language Identification in Dravidian Languages
https://github.com/kwrobel-nlp/precision-reduction
공식 코드Improving text classification with vectors of reduced precision
https://github.com/kyle1668/llm-tta
공식 코드https://github.com/l3cube-pune/MarathiNLP
공식 코드https://github.com/l3cube-pune/indic-nlp
공식 코드L3Cube-IndicNews: News-based Short Text and Long Document Classification Datasets in Indic Languages
https://github.com/label-sleuth/label-sleuth
공식 코드Label Sleuth: From Unlabeled Text to a Classifier in a Few Hours
https://github.com/laddie132/LW-PT
공식 코드Label-Wise Document Pre-Training for Multi-Label Text Classification
https://github.com/laiguokun/Funnel-Transformer
공식 코드Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing
https://github.com/laiguokun/xlu-data
공식 코드Bridging the domain gap in cross-lingual document classification
https://github.com/lancopku/SU4MLC
공식 코드Semantic-Unit-Based Dilated Convolution for Multi-Label Text Classification
https://github.com/lancopku/text-autoaugment
공식 코드Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification
https://github.com/language-ml/semeval2024-task3
공식 코드AIMA at SemEval-2024 Task 3: Simple Yet Powerful Emotion Cause Pair Analysis
https://github.com/lanl/t-elf
공식 코드HEAL: Hierarchical Embedding Alignment Loss for Improved Retrieval and Representation Learning
https://github.com/lascivaroma/seligator
공식 코드Detecting Sexual Content at the Sentence Level in First Millennium Latin Texts
https://github.com/layneins/Zero-shot-RLHR
공식 코드https://github.com/lbox-kr/nestle
공식 코드NESTLE: a No-Code Tool for Statistical Analysis of Legal Corpus
https://github.com/leftthomas/CCCapsNet
공식 코드Compositional Coding Capsule Network with K-Means Routing for Text Classification
https://github.com/leiboliu/xr-lat
공식 코드Automated ICD Coding using Extreme Multi-label Long Text Transformer-based Models
https://github.com/leitro/machineunlearning-docclassification
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.