SOTAVerified

Binary Classification

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1126–1150 of 2574 papers

TitleStatusHype
Benchmarking Offline Reinforcement Learning Algorithms for E-Commerce Order Fraud Evaluation—0
High Dimensional Binary Classification under Label Shift: Phase Transition and Regularization—0
Split-PU: Hardness-aware Training Strategy for Positive-Unlabeled LearningCode0
Semi-supervised binary classification with latent distance learning—0
Forged Image Detection using SOTA Image Classification Deep Learning Methods for Image Forensics with Error Level Analysis—0
Positive unlabeled learning with tensor networksCode0
Deep-Learning-based Vulnerability Detection in Binary Executables—0
Lifting Weak Supervision To Structured PredictionCode0
Question-type Identification for Academic Questions in Online Learning Platform—0
Event Causality Identification with Causal News Corpus -- Shared Task 3, CASE 2022—0
Photonic Quantum Computing For Polymer Classification—0
Rooms with Text: A Dataset for Overlaying Text Detection—0
Patch-level Gaze Distribution Prediction for Gaze FollowingCode0
Explainable Artificial Intelligence and Causal Inference based ATM Fraud Detection—0
Quantifying Human Bias and Knowledge to guide ML models during Training—0
Audio Anti-spoofing Using a Simple Attention Module and Joint Optimization Based on Additive Angular Margin Loss and Meta-learning—0
Detecting Disengagement in Virtual Learning as an Anomaly using Temporal Convolutional Network Autoencoder—0
Rethinking Log Odds: Linear Probability Modelling and Expert Advice in Interpretable Machine Learning—0
Towards Improved Learning in Gaussian Processes: The Best of Two Worlds—0
Optimized Global Perturbation Attacks For Brain Tumour ROI Extraction From Binary Classification Models—0
Are Face Detection Models Biased?—0
Okapi: Generalising Better by Making Statistical Matches MatchCode0
Accurate and Reliable Methods for 5G UAV Jamming Identification With Calibrated Uncertainty—0
Two-stage LLM Fine-tuning with Less Specialization and More Generalization—0
Xtreme Margin: A Tunable Loss Function for Binary Classification Problems—0
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All datasetsfakekickstarterGlyphnet DatasetTII-SSRC-23

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