https://github.com/sahilsid/svd-for-neural-networks
공식 코드Learning Neural Networks on SVD Boosted Latent Spaces for Semantic 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/sakibsourav019/ubmec-unified-bangla-multi-class-emotion-corpus-
공식 코드Transformer-based Text Classification on Unified Bangla Multi-class Emotion Corpus
https://github.com/salesforce/ModularPrompt
공식 코드Learning Label Modular Prompts for Text Classification in the Wild
https://github.com/salesforce/cove
공식 코드https://github.com/salesforce/decaNLP
공식 코드The Natural Language Decathlon: Multitask Learning as Question Answering
https://github.com/salesforce/mpt
공식 코드https://github.com/sami-diaf/Topic-Scaling
공식 코드Topic Scaling: A Joint Document Scaling -- Topic Model Approach To Learn Time-Specific Topics
https://github.com/satzbeleg/keras-hrp
공식 코드https://github.com/satzbeleg/study-hrp
공식 코드https://github.com/sayaendo/interpreting-cnn-for-text
공식 코드Understanding Convolutional Neural Networks for Text Classification
https://github.com/sayantan11995/event-timeline-generation-from-documents
공식 코드Placing (Historical) Facts on a Timeline: A Classification cum Coref Resolution Approach
https://github.com/sb1990gtr/Semantic-Interactive-ML
공식 코드https://github.com/sberbank-ai-lab/RuMedBench
공식 코드RuMedBench: A Russian Medical Language Understanding Benchmark
https://github.com/sciencenlp-lab/llm-ssc
공식 코드Multi-label Sequential Sentence Classification via Large Language Model
https://github.com/sco-field/speechemotionrecognition
공식 코드https://github.com/scotthlee/autism_classification
공식 코드A Comparison of Machine Learning Algorithms for the Surveillance of Autism Spectrum Disorder
https://github.com/scsmuhio/MTGCN_Resources
공식 코드https://github.com/sds-lab/sliceformer
공식 코드Sliceformer: Make Multi-head Attention as Simple as Sorting in Discriminative Tasks
https://github.com/seanbenhur/tanglish-offensive-language-identification
공식 코드Pretrained Transformers for Offensive Language Identification in Tanglish
https://github.com/sebastianpinedaar/finetuning_text_classifiers
공식 코드Ensembling Finetuned Language Models for Text Classification
https://github.com/sebischair/fusionsent
공식 코드Efficient Few-shot Learning for Multi-label Classification of Scientific Documents with Many Classes
https://github.com/sebischair/lbl2vec
공식 코드Lbl2Vec: An Embedding-Based Approach for Unsupervised Document Retrieval on Predefined Topics
https://github.com/sebischair/medical-abstracts-tc-corpus
공식 코드Evaluating Unsupervised Text Classification: Zero-shot and Similarity-based Approaches
https://github.com/seed-vt/tracefl
공식 코드TraceFL: Interpretability-Driven Debugging in Federated Learning via Neuron Provenance
https://github.com/seefreem/meme_text_retrieval_p1
공식 코드Large Vision-Language Models for Knowledge-Grounded Data Annotation of Memes
https://github.com/seongminp/lime
공식 코드https://github.com/sergioburdisso/pyss3
공식 코드t-SS3: a text classifier with dynamic n-grams for early risk detection over text streams
https://github.com/serkansulun/lyricsemotions
공식 코드Emotion4MIDI: a Lyrics-based Emotion-Labeled Symbolic Music Dataset
https://github.com/serrano-s/attn-tests
공식 코드https://github.com/serval-uni-lu/realistic_adversarial_hardening
공식 코드https://github.com/servicenow/promptmix-emnlp-2023
공식 코드PromptMix: A Class Boundary Augmentation Method for Large Language Model Distillation
https://github.com/seventychi/wc-sbert
공식 코드WC-SBERT: Zero-Shot Text Classification via SBERT with Self-Training for Wikipedia Categories
https://github.com/sf-wa-326/phrase-bert-topic-model
공식 코드Phrase-BERT: Improved Phrase Embeddings from BERT with an Application to Corpus Exploration
https://github.com/sgjimenezv/star_trek_recsys
공식 코드An Ontology-Based Recommender System with an Application to the Star Trek Television Franchise
https://github.com/shafiq-islam-cse/multimodal-marvels-of-deep-learning-using-image-speech-and-text-review-of-covid-19-detection
공식 코드https://github.com/shaharlutatipersonal/ocd
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.