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 301–350 of 3635 papers

TitleStatusHype
Beyond the Tip of the Iceberg: Assessing Coherence of Text ClassifiersCode1
Cross-lingual Transfer for Text Classification with Dictionary-based Heterogeneous GraphCode1
Cartography Active LearningCode1
Bag-of-Words vs. Graph vs. Sequence in Text Classification: Questioning the Necessity of Text-Graphs and the Surprising Strength of a Wide MLPCode1
Black-Box Attacks on Sequential Recommenders via Data-Free Model ExtractionCode1
Text AutoAugment: Learning Compositional Augmentation Policy for Text ClassificationCode1
AEDA: An Easier Data Augmentation Technique for Text ClassificationCode1
Semantic-Preserving Adversarial Text AttacksCode1
Fastformer: Additive Attention Can Be All You NeedCode1
Noisy Channel Language Model Prompting for Few-Shot Text ClassificationCode1
Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text ClassificationCode1
BertGCN: Transductive Text Classification by Combining GNN and BERTCode1
SPEAR : Semi-supervised Data Programming in PythonCode1
Hierarchy-aware Label Semantics Matching Network for Hierarchical Text ClassificationCode1
Concept-Based Label Embedding via Dynamic Routing for Hierarchical Text ClassificationCode1
Distinct Label Representations for Few-Shot Text ClassificationCode1
Counterfactual Inference for Text Classification DebiasingCode1
Don’t Miss the Labels: Label-semantic Augmented Meta-Learner for Few-Shot Text ClassificationCode1
Meta-Learning Adversarial Domain Adaptation Network for Few-Shot Text ClassificationCode1
Uncertainty-Aware Reliable Text ClassificationCode1
Robust Learning for Text Classification with Multi-source Noise Simulation and Hard Example MiningCode1
Revisiting Uncertainty-based Query Strategies for Active Learning with TransformersCode1
MultiCite: Modeling realistic citations requires moving beyond the single-sentence single-label settingCode1
ChineseBERT: Chinese Pretraining Enhanced by Glyph and Pinyin InformationCode1
SSMix: Saliency-Based Span Mixup for Text ClassificationCode1
Consistency Regularization for Cross-Lingual Fine-TuningCode1
Dataset of Propaganda Techniques of the State-Sponsored Information Operation of the People's Republic of ChinaCode1
Evaluating Various Tokenizers for Arabic Text ClassificationCode1
FedNLP: An interpretable NLP System to Decode Federal Reserve CommunicationsCode1
Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question AnsweringCode1
Enhancing Label Correlation Feedback in Multi-Label Text Classification via Multi-Task LearningCode1
Syntax-augmented Multilingual BERT for Cross-lingual TransferCode1
More Identifiable yet Equally Performant Transformers for Text ClassificationCode1
VILA: Improving Structured Content Extraction from Scientific PDFs Using Visual Layout GroupsCode1
Rotom: A Meta-Learned Data Augmentation Framework for Entity Matching, Data Cleaning, Text Classification, and BeyondCode1
The Out-of-Distribution Problem in Explainability and Search Methods for Feature Importance ExplanationsCode1
Predict then Interpolate: A Simple Algorithm to Learn Stable ClassifiersCode1
Joint Optimization of Tokenization and Downstream ModelCode1
Cross-lingual Text Classification with Heterogeneous Graph Neural NetworkCode1
PTR: Prompt Tuning with Rules for Text ClassificationCode1
KLUE: Korean Language Understanding EvaluationCode1
Relative Positional Encoding for Transformers with Linear ComplexityCode1
Out-of-Manifold Regularization in Contextual Embedding Space for Text ClassificationCode1
BertGCN: Transductive Text Classification by Combining GCN and BERTCode1
FNet: Mixing Tokens with Fourier TransformsCode1
DocSCAN: Unsupervised Text Classification via Learning from NeighborsCode1
PanGu-α: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel ComputationCode1
Incremental Few-shot Text Classification with Multi-round New Classes: Formulation, Dataset and SystemCode1
Seed Word Selection for Weakly-Supervised Text Classification with Unsupervised Error EstimationCode1
skweak: Weak Supervision Made Easy for NLPCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ST5-XXLAccuracy73.42—Unverified
2ST5-XLAccuracy72.84—Unverified
3ST5-LargeAccuracy72.31—Unverified
4Ada SimilarityAccuracy70.44—Unverified
5SGPT-5.8B-nliAccuracy70.14—Unverified
6ST5-BaseAccuracy69.81—Unverified
7SGPT-5.8B-msmarcoAccuracy68.13—Unverified
8MPNet-multilingualAccuracy67.91—Unverified
9GTR-XXLAccuracy67.41—Unverified
10SimCSE-BERT-supAccuracy67.32—Unverified
#ModelMetricClaimedVerifiedStatus
1Mistral-Small-24B + CAPOError15.7—Unverified
2ToWE-SGError14—Unverified
3Qwen2.5-32B + CAPOError12.93—Unverified
4Llama-3.3-70B + CAPOError11.2—Unverified
5Seq2CNN with GWS(50)Error9.64—Unverified
6Char-level CNNError9.51—Unverified
7SVDCNNError9.45—Unverified
8VDCNError8.67—Unverified
9Balanced+bi-leaf-RNNError7.9—Unverified
10CCCapsNetError7.61—Unverified
#ModelMetricClaimedVerifiedStatus
1Seq2CNN(50)Error2.77—Unverified
2Char-level CNNError1.55—Unverified
3SWEM-concatError1.43—Unverified
4FastTextError1.4—Unverified
5VDCNError1.29—Unverified
6CCCapsNetError1.28—Unverified
7Balanced+bi-leaf-RNNError1.2—Unverified
8BERT large UDAError1.09—Unverified
9M-ACNNError1.07—Unverified
10EXAMError1—Unverified
#ModelMetricClaimedVerifiedStatus
1DeBERTaAccuracy98.45—Unverified
2C-BERT (ESGNN + BERT)Accuracy98.28—Unverified
3ESGNNAccuracy98.23—Unverified
4RoBERTaGCNAccuracy98.2—Unverified
5BERTAccuracy98.17—Unverified
6SGNNAccuracy98.09—Unverified
7ERNIE 2.0Accuracy98.04—Unverified
8DistilBERTAccuracy97.98—Unverified
9Our Model*Accuracy97.8—Unverified
10ALBERTv2Accuracy97.62—Unverified
#ModelMetricClaimedVerifiedStatus
1TM-GloveError9.96—Unverified
2byte mLSTM7Error9.6—Unverified
3DELTA (CNN)Error7.8—Unverified
4SWEM-averError7.8—Unverified
5Capsule-BError7.2—Unverified
6STM+TSED+PT+2LError7.04—Unverified
7GRU-RNN-GLOVEError7—Unverified
8MPAD-pathError6.2—Unverified
9VLAWEError5.8—Unverified
10C-LSTMError5.4—Unverified
#ModelMetricClaimedVerifiedStatus
1LinearSVM+TFIDFAccuracy93—Unverified
2RoBERTaGCNAccuracy89.5—Unverified
3SSGCAccuracy88.6—Unverified
4SGCAccuracy88.5—Unverified
5SGCNAccuracy88.5—Unverified
6RMDL (15 RDLs)Accuracy87.91—Unverified
7Sparse Tensor ClassifierAccuracy87.3—Unverified
8GraphStarAccuracy86.9—Unverified
9NABoE-fullAccuracy86.8—Unverified
10Text GCNAccuracy86.34—Unverified
#ModelMetricClaimedVerifiedStatus
1ELECTRA + ANNF199.6—Unverified
2ERNIE + ANNF199.4—Unverified
3XLNet + ANNF199.2—Unverified
4RoBERTa + ANNF198.7—Unverified
5Longformer + ANNF193.9—Unverified
6BERT + ANNF190.5—Unverified
7ALBERT + ANNF179.7—Unverified
8BERTF175—Unverified
9DistilBERTF174.4—Unverified
10LongformerF174—Unverified
#ModelMetricClaimedVerifiedStatus
1RoBERTaGCNAccuracy72.8—Unverified
2Our Model*Accuracy69.4—Unverified
3SGCNAccuracy68.5—Unverified
4SGCAccuracy68.5—Unverified
5SSGCAccuracy68.5—Unverified
6Text GCNAccuracy68.36—Unverified
7GraphStarAccuracy64.2—Unverified
8ApproxRepSetAccuracy64.06—Unverified
9REL-RWMD k-NNAccuracy58.74—Unverified
10CNN+LowercasedAccuracy36.2—Unverified
#ModelMetricClaimedVerifiedStatus
1BERT-ITPT-FiTAccuracy77.62—Unverified
2DRNNAccuracy76.26—Unverified
3DELTA (HAN)Accuracy75.1—Unverified
4EXAMAccuracy74.8—Unverified
5DNC+CUWAccuracy74.3—Unverified
6ULMFiT (Small data)Accuracy74.3—Unverified
7CCCapsNetAccuracy73.85—Unverified
8SWEM-concatAccuracy73.53—Unverified
9FastTextAccuracy72.3—Unverified
10Seq2CNN(50)Accuracy55.39—Unverified
#ModelMetricClaimedVerifiedStatus
1DeBERTaAccuracy90.21—Unverified
2RoBERTaGCNAccuracy89.7—Unverified
3ERNIE 2.0 (optimized)Accuracy89.53—Unverified
4RoBERTaAccuracy89.42—Unverified
5ERNIE 2.0Accuracy88.97—Unverified
6BERTAccuracy86.94—Unverified
7ALBERTv2Accuracy86.02—Unverified
8DistilBERTAccuracy85.31—Unverified
9SSGCAccuracy76.7—Unverified
#ModelMetricClaimedVerifiedStatus
1CliReBERT (P0L3/clirebert_clirevocab_uncased)Evaluation Macro F10.65—Unverified
2ClimateBERT (climatebert/distilroberta-base-climate-f)Evaluation Macro F10.64—Unverified
3BERT (google-bert/bert-base-uncased)Evaluation Macro F10.61—Unverified
4CliSciBERT (P0L3/cliscibert_scivocab_uncased)Evaluation Macro F10.61—Unverified
5SciBERT (allenai/scibert_scivocab_cased)Evaluation Macro F10.59—Unverified
6DistilRoBERTa (distilbert/distilroberta-base)Evaluation Macro F10.58—Unverified
7SciClimateBERT (P0L3/sciclimatebert)Evaluation Macro F10.58—Unverified
8RoBERTa (FacebookAI/roberta-base)Evaluation Macro F10.57—Unverified
#ModelMetricClaimedVerifiedStatus
1Human (Post-Rec.) (Spangher et al., 2021)macro F173.69—Unverified
2MT-Mac (Spangher et al., 2021)macro F163.46—Unverified
3MT-Mic (Spangher et al., 2021)macro F161.89—Unverified
4RL-IP/TT (Choubey et al., 2021)macro F157—Unverified
5Document LSTM + Document encoding (Choubey et al., 2020)macro F154.4—Unverified
6CRF Fine-grained (Choubey et al., 2020)macro F152.9—Unverified
7Human (Blind) (Spangher et al., 2021)macro F146.18—Unverified
8Feature-based (SVM) (Choubey et al., 2020)macro F138.3—Unverified
#ModelMetricClaimedVerifiedStatus
11-6 BertGCNAccuracy96.6—Unverified
2GraphStarAccuracy95—Unverified
3Our Model*Accuracy94.6—Unverified
4SSGCAccuracy94.5—Unverified
5SGCNAccuracy94—Unverified
6SGCAccuracy94—Unverified
7Text GCNAccuracy93.56—Unverified
8TM-GloveAccuracy89.14—Unverified