https://github.com/SkBlaz/tax2vec
공식 코드tax2vec: Constructing Interpretable Features from Taxonomies for Short Text Classification
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/SparseTensorClassifier/stc
공식 코드An Explainable Probabilistic Classifier for Categorical Data Inspired to Quantum Physics
https://github.com/Stefan-Pasch/CultureBERT
공식 코드CultureBERT: Measuring Corporate Culture With Transformer-Based Language Models
https://github.com/StonyBrookNLP/emotion-label-semantics
공식 코드https://github.com/THEEJUNG/PosCal
공식 코드Posterior Calibrated Training on Sentence Classification Tasks
https://github.com/TUDB-Labs/MixLoRA
공식 코드MixLoRA: Enhancing Large Language Models Fine-Tuning with LoRA-based Mixture of Experts
https://github.com/TahaAslani/two-stage-fine-tuning
공식 코드Two-Stage Fine-Tuning: A Novel Strategy for Learning Class-Imbalanced Data
https://github.com/TajaKuzman/IPTC-Media-Topic-Classification
공식 코드https://github.com/Teddyzander/FairR
공식 코드How Robust is your Fair Model? Exploring the Robustness of Diverse Fairness Strategies
https://github.com/TencentGameMate/gnn_cross_lingual
공식 코드Cross-lingual Text Classification with Heterogeneous Graph Neural Network
https://github.com/Text-Analytics-and-Retrieval/Clustering-based-Cross-Lingual-Topic-Model
공식 코드Refining Dimensions for Improving Clustering-based Cross-lingual Topic Models
https://github.com/ThirdAIResearch/BOLT_Benchmarks/tree/main/graph_learning
공식 코드https://github.com/ThuongTNguyen/ALchemist
공식 코드https://github.com/Tianyi-Lei/Adaptive-Meta-learner-via-Gradient-Similarity-for-Few-shot-Text-Classification
공식 코드Adaptive Meta-learner via Gradient Similarity for Few-shot Text Classification
https://github.com/TigerSense/PMLDA
공식 코드https://github.com/Tiiiger/SGC
공식 코드https://github.com/TonyTangYu/ADMMiRNN
공식 코드P-ADMMiRNN: Training RNN with Stable Convergence via An Efficient and Paralleled ADMM Approach
https://github.com/Top-Ranger/text_adversarial_attack
공식 코드https://github.com/TovlyDeutsch/Linguistic-Features-for-Readability
공식 코드https://github.com/UTibetNLP/TSTricker
공식 코드Multi-Granularity Tibetan Textual Adversarial Attack Method Based on Masked Language Model
https://github.com/UVa-NLP/HEDGE
공식 코드Generating Hierarchical Explanations on Text Classification via Feature Interaction Detection
https://github.com/UVa-NLP/VMASK
공식 코드Learning Variational Word Masks to Improve the Interpretability of Neural Text Classifiers
https://github.com/UniModal4Reasoning/DocGenome
공식 코드https://github.com/VictorProkhorov/HSVAE
공식 코드https://github.com/VinAIResearch/BERTweet
공식 코드https://github.com/WHUIR/SMTM
공식 코드Multi-label Dataless Text Classification with Topic Modeling
https://github.com/WadeYin9712/SentiBERT
공식 코드SentiBERT: A Transferable Transformer-Based Architecture for Compositional Sentiment Semantics
https://github.com/Westlake-AI/SemiReward
공식 코드SemiReward: A General Reward Model for Semi-supervised Learning
https://github.com/Wluper/edm
공식 코드Evolutionary Data Measures: Understanding the Difficulty of Text Classification Tasks
https://github.com/XN-BoWenMa/Chapter-category-identification
공식 코드Enhancing Identification of Structure Function of Academic Articles Using Contextual Information
https://github.com/XiaofengZhu/hrLDA
공식 코드Unsupervised Terminological Ontology Learning based on Hierarchical Topic Modeling
https://github.com/XinyiZ001/LA-HCN
공식 코드LA-HCN: Label-based Attention for Hierarchical Multi-label TextClassification Neural Network
https://github.com/Xtra-Computing/thundersvm
공식 코드Sampling Bias in Deep Active Classification: An Empirical Study
https://github.com/XuhuiZhou/Toxic_Debias
공식 코드Challenges in Automated Debiasing for Toxic Language Detection
https://github.com/YanhaoHuang23/FAT
공식 코드A novel Fourier Adjacency Transformer for advanced EEG emotion recognition
https://github.com/YatinChaudhary/NCLM
공식 코드Explainable and Discourse Topic-aware Neural Language Understanding
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.