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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/Lingkai-Kong/Calibrated-BERT-Fine-Tuning
공식 코드Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data
https://github.com/LiteSSLHub/PSNET
공식 코드https://github.com/Liu-Hy/nlp-contrib-graph
공식 코드https://github.com/Louis-udm/VGCN-BERT
공식 코드VGCN-BERT: Augmenting BERT with Graph Embedding for Text Classification
https://github.com/Louis-udm/Word-Grounded-Graph-Convolutional-Network
공식 코드https://github.com/LuisPB7/fnc-msc
공식 코드https://github.com/Lvchangze/SpikeBERT
공식 코드SpikeBERT: A Language Spikformer Learned from BERT with Knowledge Distillation
https://github.com/Lvchangze/snn
공식 코드Spiking Convolutional Neural Networks for Text Classification
https://github.com/MIR-MU/regularized-embeddings
공식 코드Text classification with word embedding regularization and soft similarity measure
https://github.com/MaartenGr/BERTopic
공식 코드BERTopic: Neural topic modeling with a class-based TF-IDF procedure
https://github.com/Machine-Learning-for-Medical-Language/SMMH-Medication-Detection
공식 코드https://github.com/Mai-CS/OptBA
공식 코드OptBA: Optimizing Hyperparameters with the Bees Algorithm for Improved Medical Text Classification
https://github.com/Mao-KU/lightweight-crosslingual-sent2vec
공식 코드https://github.com/MarkChenYutian/GPT-Sentinel-public
공식 코드GPT-Sentinel: Distinguishing Human and ChatGPT Generated Content
https://github.com/MedChaabane/deepRAM
공식 코드https://github.com/MemoriesJ/KAMG
공식 코드Multi-label Few/Zero-shot Learning with Knowledge Aggregated from Multiple Label Graphs
https://github.com/MihaelaGaman/SaRoCo
공식 코드SaRoCo: Detecting Satire in a Novel Romanian Corpus of News Articles
https://github.com/MilaNLProc/contextualized-topic-models
공식 코드Pre-training is a Hot Topic: Contextualized Document Embeddings Improve Topic Coherence
https://github.com/MingruiLiu-ML-Lab/Single-Loop-bilevel-Optimizer-under-Unbounded-Smoothness
공식 코드https://github.com/MirunaPislar/multi-head-attention-labeller
공식 코드https://github.com/MiuLab/RCT-Gen
공식 코드Towards Understanding of Medical Randomized Controlled Trials by Conclusion Generation
https://github.com/Mohammad-Abdul-Hadi/AOBTM-Adaptive-Online-Biterm-Topic-Modeling
공식 코드AOBTM: Adaptive Online Biterm Topic Modeling Method for Version Sensitive Short-texts Analysis
https://github.com/Mohammad-Abdul-Hadi/Result-Set-Visualization-d3js-R
공식 코드https://github.com/Moradnejad/Bert-Based-Tag-Recommendation
공식 코드Tag Recommendation for Online Q&A Communities based on BERT Pre-Training Technique
https://github.com/NLPrinceton/ALaCarte
공식 코드A La Carte Embedding: Cheap but Effective Induction of Semantic Feature Vectors
https://github.com/NYU-MLL/spinn
공식 코드Do latent tree learning models identify meaningful structure in sentences?
https://github.com/Nardien/NMG
공식 코드Neural Mask Generator: Learning to Generate Adaptive Word Maskings for Language Model Adaptation
https://github.com/Natooz/music-modeling-time-duration
공식 코드Impact of time and note duration tokenizations on deep learning symbolic music modeling
https://github.com/Neural-Space/indic-transformers
공식 코드Indic-Transformers: An Analysis of Transformer Language Models for Indian Languages
https://github.com/Neutralzz/syntax_aware_local_attention
공식 코드https://github.com/Nigiva/hatespeech-detection-models
공식 코드A benchmark for toxic comment classification on Civil Comments dataset
https://github.com/Nithin-Holla/MetaLifelongLanguage
공식 코드Meta-Learning with Sparse Experience Replay for Lifelong Language Learning
https://github.com/Noahs-ARK/rational-recurrences
공식 코드https://github.com/Noahs-ARK/soft_patterns
공식 코드SoPa: Bridging CNNs, RNNs, and Weighted Finite-State Machines
https://github.com/NonvolatileMemory/AAAI_2019_EXAM
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.