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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/waithz/gw-moe
공식 코드GW-MoE: Resolving Uncertainty in MoE Router with Global Workspace Theory
https://github.com/wanggrun/Adaptively-Connected-Neural-Networks
공식 코드https://github.com/wangluran/nlp-element-influence
공식 코드An Information-Theoretic Approach to Analyze NLP Classification Tasks
https://github.com/wangxinyilinda/concept-based-demonstration-selection
공식 코드https://github.com/warisgill/tracefl
공식 코드TraceFL: Interpretability-Driven Debugging in Federated Learning via Neuron Provenance
https://github.com/warnikchow/kcharemb
공식 코드Investigating an Effective Character-level Embedding in Korean Sentence Classification
https://github.com/wasiahmad/Syntax-MBERT
공식 코드Syntax-augmented Multilingual BERT for Cross-lingual Transfer
https://github.com/watermeleon/shortcut_mechanisms
공식 코드Short-circuiting Shortcuts: Mechanistic Investigation of Shortcuts in Text Classification
https://github.com/wazenmai/MIDI-BERT
공식 코드BERT-like Pre-training for Symbolic Piano Music Classification Tasks
https://github.com/wds2014/topickg
공식 코드https://github.com/weakrules/Denoise-multi-weak-sources
공식 코드Denoising Multi-Source Weak Supervision for Neural Text Classification
https://github.com/webis-de/EMNLP-20
공식 코드Detecting Media Bias in News Articles using Gaussian Bias Distributions
https://github.com/webis-de/acl22-revisiting-uncertainty-based-query-strategies-for-active-learning-with-transformers
공식 코드Revisiting Uncertainty-based Query Strategies for Active Learning with Transformers
https://github.com/webis-de/argmining-21
공식 코드Assessing the Sufficiency of Arguments through Conclusion Generation
https://github.com/webis-de/arxiv24-ranking-generated-answers
공식 코드https://github.com/webis-de/small-text
공식 코드Small-Text: Active Learning for Text Classification in Python
https://github.com/wenhuchen/Variational-Vocabulary-Selection
공식 코드How Large a Vocabulary Does Text Classification Need? A Variational Approach to Vocabulary Selection
https://github.com/wenliangdai/multi-task-offensive-language-detection
공식 코드Text generation for dataset augmentation in security classification tasks
https://github.com/wenzhihao666/g2p2-conditional
공식 코드Prompt Tuning on Graph-augmented Low-resource Text Classification
https://github.com/werywjw/sep-cvdl
공식 코드GiMeFive: Towards Interpretable Facial Emotion Classification
https://github.com/wfearn/preprocessing-paper
공식 코드https://github.com/wglab/bioformer
공식 코드Bioformer: an efficient transformer language model for biomedical text mining
https://github.com/wikipedia2vec/wikipedia2vec
공식 코드Representation Learning of Entities and Documents from Knowledge Base Descriptions
https://github.com/williambankes/REDUCR
공식 코드REDUCR: Robust Data Downsampling Using Class Priority Reweighting
https://github.com/williambrach/gqr
공식 코드https://github.com/williamlyh/pos_div_metric
공식 코드https://github.com/williamstoto/imo
공식 코드https://github.com/wimh966/QDrop
공식 코드QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quantization
https://github.com/withchencheng/ecml_pkdd_23_real
공식 코드REAL: A Representative Error-Driven Approach for Active Learning
https://github.com/wjxts/regularizedbn
공식 코드Understanding the Failure of Batch Normalization for Transformers in NLP
https://github.com/wokas36/DFNets
공식 코드DFNets: Spectral CNNs for Graphs with Feedback-Looped Filters
https://github.com/woodyx218/Deep-Learning-with-GDP
공식 코드https://github.com/woqingdoua/imbalanceclass
공식 코드Unsupervised Reinforcement Adaptation for Class-Imbalanced Text Classification
https://github.com/wq2581/gudn
공식 코드https://github.com/wtl666wtl/WOT-Class
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.