SOTAVerified

Text Classification

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.

( Image credit: Text Classification Algorithms: A Survey )

Papers

Showing 27512800 of 3635 papers

TitleStatusHype
An Introduction to a New Text Classification and Visualization for Natural Language Processing Using Topological Data Analysis0
NULI at SemEval-2019 Task 6: Transfer Learning for Offensive Language Detection using Bidirectional Transformers0
SWOW-8500: Word Association task for Intrinsic Evaluation of Word Embeddings0
Beyond Context: A New Perspective for Word Embeddings0
INGEOTEC at SemEval-2019 Task 5 and Task 6: A Genetic Programming Approach for Text Classification0
Neural User Factor Adaptation for Text Classification: Learning to Generalize Across Author DemographicsCode0
Cooperative neural networks (CoNN): Exploiting prior independence structure for improved classification0
UNBNLP at SemEval-2019 Task 5 and 6: Using Language Models to Detect Hate Speech and Offensive Language0
WUT at SemEval-2019 Task 9: Domain-Adversarial Neural Networks for Domain Adaptation in Suggestion Mining0
MIDAS at SemEval-2019 Task 9: Suggestion Mining from Online Reviews using ULMFit0
FLAIR: An Easy-to-Use Framework for State-of-the-Art NLPCode0
Predicting Suicide Risk from Online Postings in Reddit The UGent-IDLab submission to the CLPysch 2019 Shared Task A0
T\"uKaSt at SemEval-2019 Task 6: Something Old, Something Neu(ral): Traditional and Neural Approaches to Offensive Text Classification0
Rouletabille at SemEval-2019 Task 4: Neural Network Baseline for Identification of Hyperpartisan Publishers0
Saagie at Semeval-2019 Task 5: From Universal Text Embeddings and Classical Features to Domain-specific Text Classification0
Predicting Helpful Posts in Open-Ended Discussion Forums: A Neural Architecture0
Adaptive Convolution for Text Classification0
CAMsterdam at SemEval-2019 Task 6: Neural and graph-based feature extraction for the identification of offensive tweets0
Fermi at SemEval-2019 Task 4: The sarah-jane-smith Hyperpartisan News Detector0
Are Fictional Voices Distinguishable? Classifying Character Voices in Modern Drama0
Vector of Locally Aggregated Embeddings for Text Representation0
Do Human Rationales Improve Machine Explanations?0
Particle Filter Recurrent Neural NetworksCode0
LANGUAGE MODEL EMBEDDINGS IMPROVE SENTIMENT ANALYSIS IN RUSSIANCode0
DSReg: Using Distant Supervision as a Regularizer0
SuperTML: Two-Dimensional Word Embedding and Transfer Learning Using ImageNet Pretrained CNN Models for the Classifications on Tabular Data0
EDUCE: Explaining model Decisions through Unsupervised Concepts Extraction0
Adaptive Region Embedding for Text Classification0
Extreme Multi-Label Legal Text Classification: A case study in EU Legislation0
Let's Agree to Agree: Neural Networks Share Classification Order on Real Datasets0
SuperCaptioning: Image Captioning Using Two-dimensional Word Embedding0
Label-aware Document Representation via Hybrid Attention for Extreme Multi-Label Text ClassificationCode0
An Investigation of Transfer Learning-Based Sentiment Analysis in Japanese0
A Text Classification Framework for Simple and Effective Early Depression Detection Over Social Media StreamsCode0
System Demo for Transfer Learning from Vision to Language using Domain Specific CNN Accelerator for On-Device NLP Applications0
SuperChat: Dialogue Generation by Transfer Learning from Vision to Language using Two-dimensional Word Embedding and Pretrained ImageNet CNN Models0
SuperTML: Domain Transfer from Computer Vision to Structured Tabular Data through Two-Dimensional Word Embedding0
An Approach for Process Model Extraction By Multi-Grained Text ClassificationCode0
Is Word Segmentation Necessary for Deep Learning of Chinese Representations?0
Modelling Instance-Level Annotator Reliability for Natural Language Labelling TasksCode0
Naive Bayes with Correlation Factor for Text Classification Problem0
SuperChat: Dialogue Generation by Transfer Learning from Vision to Language using Two-dimensional Word Embedding and Pretrained ImageNet CNN Models0
Taming Pretrained Transformers for Extreme Multi-label Text ClassificationCode0
Effectiveness of Self Normalizing Neural Networks for Text Classification0
KnowBias: A Novel AI Method to Detect Polarity in Online Content0
Disease Identification From Unstructured User Input0
Attentive Task-Agnostic Meta-Learning for Few-Shot Text Classification0
On the Use of ArXiv as a DatasetCode0
"Why Should You Trust My Explanation?" Understanding Uncertainty in LIME Explanations0
Adversarial Dropout for Recurrent Neural NetworksCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ST5-XXLAccuracy73.42Unverified
2ST5-XLAccuracy72.84Unverified
3ST5-LargeAccuracy72.31Unverified
4Ada SimilarityAccuracy70.44Unverified
5SGPT-5.8B-nliAccuracy70.14Unverified
6ST5-BaseAccuracy69.81Unverified
7SGPT-5.8B-msmarcoAccuracy68.13Unverified
8MPNet-multilingualAccuracy67.91Unverified
9GTR-XXLAccuracy67.41Unverified
10SimCSE-BERT-supAccuracy67.32Unverified
#ModelMetricClaimedVerifiedStatus
1Mistral-Small-24B + CAPOError15.7Unverified
2ToWE-SGError14Unverified
3Qwen2.5-32B + CAPOError12.93Unverified
4Llama-3.3-70B + CAPOError11.2Unverified
5Seq2CNN with GWS(50)Error9.64Unverified
6Char-level CNNError9.51Unverified
7SVDCNNError9.45Unverified
8VDCNError8.67Unverified
9Balanced+bi-leaf-RNNError7.9Unverified
10CCCapsNetError7.61Unverified
#ModelMetricClaimedVerifiedStatus
1Seq2CNN(50)Error2.77Unverified
2Char-level CNNError1.55Unverified
3SWEM-concatError1.43Unverified
4FastTextError1.4Unverified
5VDCNError1.29Unverified
6CCCapsNetError1.28Unverified
7Balanced+bi-leaf-RNNError1.2Unverified
8BERT large UDAError1.09Unverified
9M-ACNNError1.07Unverified
10EXAMError1Unverified
#ModelMetricClaimedVerifiedStatus
1DeBERTaAccuracy98.45Unverified
2C-BERT (ESGNN + BERT)Accuracy98.28Unverified
3ESGNNAccuracy98.23Unverified
4RoBERTaGCNAccuracy98.2Unverified
5BERTAccuracy98.17Unverified
6SGNNAccuracy98.09Unverified
7ERNIE 2.0Accuracy98.04Unverified
8DistilBERTAccuracy97.98Unverified
9Our Model*Accuracy97.8Unverified
10ALBERTv2Accuracy97.62Unverified
#ModelMetricClaimedVerifiedStatus
1TM-GloveError9.96Unverified
2byte mLSTM7Error9.6Unverified
3SWEM-averError7.8Unverified
4DELTA (CNN)Error7.8Unverified
5Capsule-BError7.2Unverified
6STM+TSED+PT+2LError7.04Unverified
7GRU-RNN-GLOVEError7Unverified
8MPAD-pathError6.2Unverified
9VLAWEError5.8Unverified
10C-LSTMError5.4Unverified
#ModelMetricClaimedVerifiedStatus
1LinearSVM+TFIDFAccuracy93Unverified
2RoBERTaGCNAccuracy89.5Unverified
3SSGCAccuracy88.6Unverified
4SGCAccuracy88.5Unverified
5SGCNAccuracy88.5Unverified
6RMDL (15 RDLs)Accuracy87.91Unverified
7Sparse Tensor ClassifierAccuracy87.3Unverified
8GraphStarAccuracy86.9Unverified
9NABoE-fullAccuracy86.8Unverified
10Text GCNAccuracy86.34Unverified
#ModelMetricClaimedVerifiedStatus
1ELECTRA + ANNF199.6Unverified
2ERNIE + ANNF199.4Unverified
3XLNet + ANNF199.2Unverified
4RoBERTa + ANNF198.7Unverified
5Longformer + ANNF193.9Unverified
6BERT + ANNF190.5Unverified
7ALBERT + ANNF179.7Unverified
8BERTF175Unverified
9DistilBERTF174.4Unverified
10XLNetF174Unverified
#ModelMetricClaimedVerifiedStatus
1RoBERTaGCNAccuracy72.8Unverified
2Our Model*Accuracy69.4Unverified
3SSGCAccuracy68.5Unverified
4SGCAccuracy68.5Unverified
5SGCNAccuracy68.5Unverified
6Text GCNAccuracy68.36Unverified
7GraphStarAccuracy64.2Unverified
8ApproxRepSetAccuracy64.06Unverified
9REL-RWMD k-NNAccuracy58.74Unverified
10CNN+LowercasedAccuracy36.2Unverified
#ModelMetricClaimedVerifiedStatus
1BERT-ITPT-FiTAccuracy77.62Unverified
2DRNNAccuracy76.26Unverified
3DELTA (HAN)Accuracy75.1Unverified
4EXAMAccuracy74.8Unverified
5DNC+CUWAccuracy74.3Unverified
6ULMFiT (Small data)Accuracy74.3Unverified
7CCCapsNetAccuracy73.85Unverified
8SWEM-concatAccuracy73.53Unverified
9FastTextAccuracy72.3Unverified
10Seq2CNN(50)Accuracy55.39Unverified
#ModelMetricClaimedVerifiedStatus
1DeBERTaAccuracy90.21Unverified
2RoBERTaGCNAccuracy89.7Unverified
3ERNIE 2.0 (optimized)Accuracy89.53Unverified
4RoBERTaAccuracy89.42Unverified
5ERNIE 2.0Accuracy88.97Unverified
6BERTAccuracy86.94Unverified
7ALBERTv2Accuracy86.02Unverified
8DistilBERTAccuracy85.31Unverified
9SSGCAccuracy76.7Unverified
#ModelMetricClaimedVerifiedStatus
1CliReBERT (P0L3/clirebert_clirevocab_uncased)Evaluation Macro F10.65Unverified
2ClimateBERT (climatebert/distilroberta-base-climate-f)Evaluation Macro F10.64Unverified
3BERT (google-bert/bert-base-uncased)Evaluation Macro F10.61Unverified
4CliSciBERT (P0L3/cliscibert_scivocab_uncased)Evaluation Macro F10.61Unverified
5SciBERT (allenai/scibert_scivocab_cased)Evaluation Macro F10.59Unverified
6DistilRoBERTa (distilbert/distilroberta-base)Evaluation Macro F10.58Unverified
7SciClimateBERT (P0L3/sciclimatebert)Evaluation Macro F10.58Unverified
8RoBERTa (FacebookAI/roberta-base)Evaluation Macro F10.57Unverified
#ModelMetricClaimedVerifiedStatus
1Human (Post-Rec.) (Spangher et al., 2021)macro F173.69Unverified
2MT-Mac (Spangher et al., 2021)macro F163.46Unverified
3MT-Mic (Spangher et al., 2021)macro F161.89Unverified
4RL-IP/TT (Choubey et al., 2021)macro F157Unverified
5Document LSTM + Document encoding (Choubey et al., 2020)macro F154.4Unverified
6CRF Fine-grained (Choubey et al., 2020)macro F152.9Unverified
7Human (Blind) (Spangher et al., 2021)macro F146.18Unverified
8Feature-based (SVM) (Choubey et al., 2020)macro F138.3Unverified
#ModelMetricClaimedVerifiedStatus
11-6 BertGCNAccuracy96.6Unverified
2GraphStarAccuracy95Unverified
3Our Model*Accuracy94.6Unverified
4SSGCAccuracy94.5Unverified
5SGCAccuracy94Unverified
6SGCNAccuracy94Unverified
7Text GCNAccuracy93.56Unverified
8TM-GloveAccuracy89.14Unverified