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Binary Classification

Papers

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Showing 1651–1675 of 2574 papers

TitleStatusHype
Testing for Normality with Neural Networks—0
Text Classification of the Precursory Accelerating Seismicity Corpus: Inference on some Theoretical Trends in Earthquake Predictability Research from 1988 to 2018—0
TextMountain: Accurate Scene Text Detection via Instance Segmentation—0
Textual Data Mining for Financial Fraud Detection: A Deep Learning Approach—0
TF-IDFC-RF: A Novel Supervised Term Weighting Scheme—0
ThangDLU at #SMM4H 2024: Encoder-decoder models for classifying text data on social disorders in children and adolescents—0
The advantages of multiple classes for reducing overfitting from test set reuse—0
The Adversarial Consistency of Surrogate Risks for Binary Classification—0
The Consistency of Adversarial Training for Binary Classification—0
The Distracting Effect: Understanding Irrelevant Passages in RAG—0
The Double Descent Behavior in Two Layer Neural Network for Binary Classification—0
The Dynamics of Learning: A Random Matrix Approach—0
Estimating the Arc Length of the Optimal ROC Curve and Lower Bounding the Maximal AUC—0
The Financial Document Causality Detection Shared Task (FinCausal 2020)—0
The Generalization Error of Stochastic Mirror Descent on Over-Parametrized Linear Models—0
The Geometry of Adversarial Training in Binary Classification—0
The Impact of an XAI-Augmented Approach on Binary Classification with Scarce Data—0
The Implicit Bias of Batch Normalization in Linear Models and Two-layer Linear Convolutional Neural Networks—0
The Implicit Bias of Gradient Descent on Separable Multiclass Data—0
Influence of Utterance and Speaker Characteristics on the Classification of Children with Cleft Lip and Palate—0
The INTERSPEECH 2021 Computational Paralinguistics Challenge: COVID-19 Cough, COVID-19 Speech, Escalation & Primates—0
The Knowledge Gradient with Logistic Belief Models for Binary Classification—0
The Landscape of Empirical Risk for Non-convex Losses—0
The late-stage training dynamics of (stochastic) subgradient descent on homogeneous neural networks—0
The Law of Total Odds—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Trompt + OpenAI embeddingAUROC0.98—Unverified
2LightGBM + OpenAI embeddingAUROC0.97—Unverified
3FTTransformer + RoBERTa fintuneAUROC0.96—Unverified
4LightGBM + RoBERTa embeddingAUROC0.95—Unverified
5FTTransformer + RoBERTa embeddingAUROC0.94—Unverified
6ResNet + RoBERTa embeddingAUROC0.93—Unverified
7ResNet + OpenAI embeddingAUROC0.92—Unverified
8FTTransformer + OpenAI embeddingAUROC0.91—Unverified
#ModelMetricClaimedVerifiedStatus
1Trompt + OpenAI embeddingAUROC0.81—Unverified
2Multimodal-Net All-TextAUROC0.8—Unverified
3ResNet + RoBERTa finetuneAUROC0.79—Unverified
4LightGBM + RoBERTa embeddingAUROC0.77—Unverified
#ModelMetricClaimedVerifiedStatus
1Attention based CNNF1 score0.93—Unverified
#ModelMetricClaimedVerifiedStatus
1XGBoostF1-Score98.79—Unverified