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 401450 of 3635 papers

TitleStatusHype
Asymmetric Polynomial Loss For Multi-Label ClassificationCode1
Pretrained Domain-Specific Language Model for General Information Retrieval Tasks in the AEC DomainCode1
DepressionEmo: A novel dataset for multilabel classification of depression emotionsCode1
A Text Classification-Based Approach for Evaluating and Enhancing the Machine Interpretability of Building CodesCode1
Pre-Training to Learn in ContextCode1
PRL: Prompts from Reinforcement LearningCode1
A Survey on Text Classification: From Shallow to Deep LearningCode1
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language InferenceCode1
Prompting as Probing: Using Language Models for Knowledge Base ConstructionCode1
AcTune: Uncertainty-aware Active Self-Training for Semi-Supervised Active Learning with Pretrained Language ModelsCode1
A Diagnostic Study of Explainability Techniques for Text ClassificationCode1
Prompt Tuning on Graph-augmented Low-resource Text ClassificationCode1
AMR-DA: Data Augmentation by Abstract Meaning RepresentationCode1
R&R: Metric-guided Adversarial Sentence GenerationCode1
Exploiting Global and Local Hierarchies for Hierarchical Text ClassificationCode1
Distributionally Robust Models with Parametric Likelihood RatiosCode1
BanglaBERT: Language Model Pretraining and Benchmarks for Low-Resource Language Understanding Evaluation in BanglaCode1
A Neural Few-Shot Text Classification Reality CheckCode1
AttentionXML: Label Tree-based Attention-Aware Deep Model for High-Performance Extreme Multi-Label Text ClassificationCode1
A Multi-Grained Self-Interpretable Symbolic-Neural Model For Single/Multi-Labeled Text ClassificationCode1
Diffuser: Efficient Transformers with Multi-hop Attention Diffusion for Long SequencesCode1
Quaternion Graph Neural NetworksCode1
DisCo: Distilled Student Models Co-training for Semi-supervised Text MiningCode1
DiscoPrompt: Path Prediction Prompt Tuning for Implicit Discourse Relation RecognitionCode1
ReadNet: A Hierarchical Transformer Framework for Web Article Readability AnalysisCode1
Discrete Latent Variable Representations for Low-Resource Text ClassificationCode1
Distillation-Resistant Watermarking for Model Protection in NLPCode1
ReGVD: Revisiting Graph Neural Networks for Vulnerability DetectionCode1
Representation Learning of Entities and Documents from Knowledge Base DescriptionsCode1
Distinct Label Representations for Few-Shot Text ClassificationCode1
Revisiting Hierarchical Text Classification: Inference and MetricsCode1
BootAug: Boosting Text Augmentation via Hybrid Instance Filtering FrameworkCode1
Diversity Enhanced Active Learning with Strictly Proper Scoring RulesCode1
A Unified Neural Network Model for Readability Assessment with Feature Projection and Length-Balanced LossCode1
DKEC: Domain Knowledge Enhanced Multi-Label Classification for Diagnosis PredictionCode1
DocBERT: BERT for Document ClassificationCode1
RoBERTa: A Robustly Optimized BERT Pretraining ApproachCode1
Automated Essay Scoring Using Transformer ModelsCode1
Exploring and Predicting Transferability across NLP TasksCode1
Dual Contrastive Learning: Text Classification via Label-Aware Data AugmentationCode1
Rotom: A Meta-Learned Data Augmentation Framework for Entity Matching, Data Cleaning, Text Classification, and BeyondCode1
Domain-Adaptive Text Classification with Structured Knowledge from Unlabeled DataCode1
Don’t Miss the Labels: Label-semantic Augmented Meta-Learner for Few-Shot Text ClassificationCode1
SAFER: A Structure-free Approach for Certified Robustness to Adversarial Word SubstitutionsCode1
DP-BART for Privatized Text Rewriting under Local Differential PrivacyCode1
DoubleMix: Simple Interpolation-Based Data Augmentation for Text ClassificationCode1
Adversarial Training with Fast Gradient Projection Method against Synonym Substitution based Text AttacksCode1
Advanced Dropout: A Model-free Methodology for Bayesian Dropout OptimizationCode1
Fine-Tuned 'Small' LLMs (Still) Significantly Outperform Zero-Shot Generative AI Models in Text ClassificationCode1
Gradient-Based Adversarial Training on Transformer Networks for Detecting Check-Worthy Factual ClaimsCode1
Show:102550
← PrevPage 9 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
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