Papers Binary Classification
“Binary Classification” 태그가 달린 논문 3,070편 · 필터 해제
On public and private binary classification with metric space valued predictors
We consider the problem of binary classification in a framework where the predictor $X$ takes values in an arbitrary separable metric space $\mathcal X$ and the label $Y$ values in $\{ \pm 1 \}$. In the first part of thi…
Binary ClassificationSeparating Secrets from Placeholders: A Hybrid CNN-CodeBERT Framework for Three-Class Credential Leakage Detection
Credential leakage in public source code repositories poses a critical security threat, with over 23.8 million secrets exposed in 2024 alone. Existing detection tools suffer from high false-positive rates because rigid p…
Binary ClassificationImproving Selective Classification with Pairwise Queries for Binary Classification
In selective classification, a model predicts the labels of data samples where it is confident, and abstains from predicting labels for samples on which it is not confident. The rejected samples are often labeled by an e…
Binary ClassificationARMA-C3: A Contrastive ARMA Convolutional Framework for Unsupervised and Semi-supervised Classification
In biomedical and neurodegenerative disorders, accurate and early disease identification remains challenging due to the scarcity of labeled data and the complexity of imaging patterns. To address these challenges, we int…
Representation LearningBinary ClassificationContrastive LearningNode ClassificationMinimax Limits of k-Fold Cross-Validation via Majority
We study the mean-squared error of $k$-fold cross-validation as a risk estimator, with particular emphasis on how its accuracy depends on the number of folds $k$. Despite the widespread use of cross-validation, principle…
Binary ClassificationClueAegis: Heuristic-to-Reasoning Cognitive-skill Learning for Unified Evidence-based Synthetic Image Detection
The rapid advancement of generative models has made synthetic images increasingly realistic, challenging reliable detection. Existing methods are often limited to end-to-end classification or monolithic reasoning, and th…
Domain GeneralizationBinary ClassificationDecision MakingFoodMonitor: Benchmarking MLLMs for Explainable Compliance Analysis
As AI-powered compliance monitoring becomes increasingly important in public governance and industrial safety, the ability to provide verifiable evidence and traceable accountability signals is essential. However, existi…
Video Anomaly DetectionBinary ClassificationCross-Subject EEG Emotion Recognition Based on Temporal Asynchronous Alignment Contrastive Learning
With the advancement of science and technology, the importance of emotion research has become increasingly evident. Electroencephalography (EEG)-based emotion recognition has emerged as an active research area in recent …
EEG Emotion RecognitionBinary ClassificationContrastive LearningDeep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction
Aims: Coronary microvascular dysfunction (CMVD) affects approximately 40%-60% of patients with ischemia and non-obstructive coronary arteries, yet diagnosis remains challenging due to reliance on invasive functional test…
Binary ClassificationDecision-Path Patterns as Tree Reliability Signals: Path-based Adaptive Weighting for Random Forest Classification
Random forests construct each tree with a different, randomised representation of the feature space. Their uniform voting cannot correct errors in regions where trees with incorrect representations probabilistically outn…
Binary ClassificationFindings of the Counter Turing Test: AI-Generated Text Detection
The growing capability of large language models to produce fluent, contextually coherent text has created mounting pressure on the systems and institutions responsible for ensuring the authenticity of digital content. Ad…
Adversarial RobustnessDomain GeneralizationBinary ClassificationEnsemble LearningFindings of the Counter Turing Test: AI-Generated Image Detection
The rapid advancements in generative AI technologies, such as Stable Diffusion, DALL-E, and Midjourney, have significantly transformed the creation of synthetic visual content. While these models enable innovation across…
Adversarial RobustnessBinary ClassificationContrastive LearningExploring the Effectiveness of Using LLMs for Automated Assessment of Student Self Explanations in Programming Education
Worked examples are step-by-step solutions to problems in a specific domain, offered to students to acquire domain-specific problem-solving skills. The effectiveness of worked examples could be enhanced by combining them…
Binary ClassificationSemantic SimilarityAre Rationales Necessary and Sufficient? Tuning LLMs for Explainable Misinformation Detection
The rapid spread of misinformation on social media platforms has become a formidable challenge. To mitigate its proliferation, Misinformation Detection (MD) has emerged as a critical research topic. Traditional MD approa…
Binary ClassificationVon Economo neurons enable reliable social skill acquisition in recurrent spiking neural networks: a computational account with clinical predictions
Von Economo neurons (VENs) are selectively lost in behavioural-variant frontotemporal dementia (bvFTD) and reduced in autism spectrum conditions (ASC), yet their computational role in social learning remains unexplained.…
Binary ClassificationBeyond Binary: Reframing GUI Critique as Continuous Semantic Alignment
Test-Time Scaling (TTS), which samples multiple candidate actions and ranks them via a Critic Model, has emerged as a promising paradigm for generalist GUI agents. Its efficacy thus hinges on the critic's fine-grained ra…
Binary ClassificationContrastive LearningOptimal Pattern Detection Tree for Symbolic Rule-Based Classification
Pattern discovery in data plays a crucial role across diverse domains, including healthcare, risk assessment, and machinery maintenance. In contrast to black-box deep learning models, symbolic rule discovery emerges as a…
Binary ClassificationA Unified Three-Stage Machine Learning Framework for Diabetes Detection, Subtype Discrimination, and Cognitive-Metabolic Hypothesis Testing
Diabetes mellitus affects over 537 million adults worldwide and remains a major challenge in preventive healthcare. Existing machine-learning studies primarily formulate diabetes prediction as a binary classification pro…
Binary ClassificationDiabetes PredictionAttnGen: Attention-Guided Saliency Learning for Interpretable Genomic Sequence Classification
Deep neural networks have achieved strong performance in genomic sequence classification; however, relating their predictions to biologically meaningful sequence patterns remains challenging. In this work, we present Att…
Binary ClassificationA Systematic Evaluation of Imbalance Handling Methods in Biomedical Binary Classification
Objective: The primary goal of this study was to systematically examine the impact of commonly used imbalance handling methods (IHMs) on predictive performance in biomedical binary classification, considering the interpl…
Binary Classification