SOTAVerified

General Classification

Algorithms trying to solve the general task of classification.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 7451–7475 of 14581 papers

TitleStatusHype
Personalized Microblog Sentiment Classification via Adversarial Cross-lingual Multi-task Learning—0
Limbic: Author-Based Sentiment Aspect Modeling Regularized with Word Embeddings and Discourse Relations—0
Neural Multitask Learning for Simile Recognition—0
Self-Governing Neural Networks for On-Device Short Text ClassificationCode0
Sentiment Classification towards Question-Answering with Hierarchical Matching Network—0
MCapsNet: Capsule Network for Text with Multi-Task Learning—0
Memory, Show the Way: Memory Based Few Shot Word Representation Learning—0
Speed Reading: Learning to Read ForBackward via ShuttleCode0
End-to-End Non-Autoregressive Neural Machine Translation with Connectionist Temporal Classification—0
Improving Multi-label Emotion Classification via Sentiment Classification with Dual Attention Transfer Network—0
A Hierarchical Neural Attention-based Text ClassifierCode0
Increasing In-Class Similarity by Retrofitting Embeddings with Demographic InformationCode0
ICON: Interactive Conversational Memory Network for Multimodal Emotion Detection—0
Adversarial Training for Multi-task and Multi-lingual Joint Modeling of Utterance Intent Classification—0
IARM: Inter-Aspect Relation Modeling with Memory Networks in Aspect-Based Sentiment AnalysisCode0
Content Explorer: Recommending Novel Entities for a Document Writer—0
Investigating the Role of Argumentation in the Rhetorical Analysis of Scientific Publications with Neural Multi-Task Learning Models—0
Few-Shot and Zero-Shot Multi-Label Learning for Structured Label SpacesCode0
Joint Learning for Emotion Classification and Emotion Cause Detection—0
Attentive Gated Lexicon Reader with Contrastive Contextual Co-Attention for Sentiment Classification—0
Labeled Anchors and a Scalable, Transparent, and Interactive Classifier—0
Large-scale Exploration of Neural Relation Classification ArchitecturesCode0
How Powerful are Graph Neural Networks?Code1
Convergence Rates for Empirical Estimation of Binary Classification Bounds—0
Classification from Positive, Unlabeled and Biased Negative DataCode0
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All datasetsXORirisActivityFashion-MNISTISOLETMice ProteinMNISTWine

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1KNNAccuracy93.1—Unverified
2RFAccuracy92.96—Unverified
3CARTAccuracy92.82—Unverified
4LDAAccuracy77.22—Unverified
#ModelMetricClaimedVerifiedStatus
1XBNETAccuracy100—Unverified
2MONT3Accuracy100—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy42—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy67.7—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy68.5—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy13.4—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy90.6—Unverified
#ModelMetricClaimedVerifiedStatus
1MONT3Accuracy100—Unverified