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 31513200 of 3635 papers

TitleStatusHype
Incubating Text Classifiers Following User Instruction with Nothing but LLMCode0
Exclusive Supermask Subnetwork Training for Continual LearningCode0
On the Sensitivity and Stability of Model Interpretations in NLPCode0
On-the-fly Denoising for Data Augmentation in Natural Language UnderstandingCode0
indicnlp@kgp at DravidianLangTech-EACL2021: Offensive Language Identification in Dravidian LanguagesCode0
indicnlp@ kgp at DravidianLangTech-EACL2021: Offensive Language Identification in Dravidian LanguagesCode0
Indic-Transformers: An Analysis of Transformer Language Models for Indian LanguagesCode0
On the Fragility of Active Learners for Text ClassificationCode0
Inducing Generalized Multi-Label Rules with Learning Classifier SystemsCode0
Contextual Augmentation: Data Augmentation by Words with Paradigmatic RelationsCode0
Evolutionary Verbalizer Search for Prompt-based Few Shot Text ClassificationCode0
On the Impact of Seed Words on Sentiment Polarity Lexicon InductionCode0
On the Impact of Temporal Concept Drift on Model ExplanationsCode0
Adversarial Mixing Policy for Relaxing Locally Linear Constraints in MixupCode0
Automated Bug Report Prioritization in Large Open-Source ProjectsCode0
Inferring the source of official texts: can SVM beat ULMFiT?Code0
Evolutionary Data Measures: Understanding the Difficulty of Text Classification TasksCode0
INFODENS: An Open-source Framework for Learning Text RepresentationsCode0
Information Aggregation via Dynamic Routing for Sequence EncodingCode0
SepLL: Separating Latent Class Labels from Weak Supervision NoiseCode0
On the Noise Robustness of In-Context Learning for Text GenerationCode0
On the privacy-utility trade-off in differentially private hierarchical text classificationCode0
Text Classification Improved by Integrating Bidirectional LSTM with Two-dimensional Max PoolingCode0
On the Role of Text Preprocessing in Neural Network Architectures: An Evaluation Study on Text Categorization and Sentiment AnalysisCode0
An Improvement of Data Classification Using Random Multimodel Deep Learning (RMDL)Code0
Token Sequence Labeling vs. Clause Classification for English Emotion Stimulus DetectionCode0
Every Document Owns Its Structure: Inductive Text Classification via Graph Neural NetworksCode0
On the Universal Adversarial Perturbations for Efficient Data-free Adversarial DetectionCode0
Evaluation of Language Models in the Medical Context Under Resource-Constrained SettingsCode0
Word Embeddings for the Armenian Language: Intrinsic and Extrinsic EvaluationCode0
Integrating Attention Feedback into the Recurrent Neural NetworkCode0
Integrating Semantic Knowledge to Tackle Zero-shot Text ClassificationCode0
Intentional Control of Type I Error over Unconscious Data Distortion: a Neyman-Pearson Approach to Text ClassificationCode0
Evaluation of a Sequence Tagging Tool for Biomedical TextsCode0
Interactive Refinement of Cross-Lingual Word EmbeddingsCode0
On the Use of ArXiv as a DatasetCode0
On Tree-Based Neural Sentence ModelingCode0
Sequential Short-Text Classification with Recurrent and Convolutional Neural NetworksCode0
Interpretable-by-Design Text Understanding with Iteratively Generated Concept BottleneckCode0
Adapting Neural Text Classification for Improved Software CategorizationCode0
An Explainable Probabilistic Classifier for Categorical Data Inspired to Quantum PhysicsCode0
When Automated Assessment Meets Automated Content Generation: Examining Text Quality in the Era of GPTsCode0
An Experimental Evaluation of Japanese Tokenizers for Sentiment-Based Text ClassificationCode0
ProtoryNet - Interpretable Text Classification Via Prototype TrajectoriesCode0
Towards better understanding of gradient-based attribution methods for Deep Neural NetworksCode0
Evaluation Measures for Hierarchical Classification: a unified view and novel approachesCode0
Context Reinforced Neural Topic Modeling over Short TextsCode0
Interpreting Neural Networks With Nearest NeighborsCode0
Adversarial Examples for Extreme Multilabel Text ClassificationCode0
Zero-Shot Topic Classification of Column Headers: Leveraging LLMs for Metadata EnrichmentCode0
Show:102550
← PrevPage 64 of 73Next →

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
3DELTA (CNN)Error7.8Unverified
4SWEM-averError7.8Unverified
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
10LongformerF174Unverified
#ModelMetricClaimedVerifiedStatus
1RoBERTaGCNAccuracy72.8Unverified
2Our Model*Accuracy69.4Unverified
3SSGCAccuracy68.5Unverified
4SGCNAccuracy68.5Unverified
5SGCAccuracy68.5Unverified
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