Papers Binary Classification
“Binary Classification” 태그가 달린 논문 3,070편 · 필터 해제
Only Train Once: Uncertainty-Aware One-Class Learning for Face Authenticity Detection
The rapid evolution of generative paradigms has enabled the creation of highly realistic imagery, which escalating the risks of identity fraud and the dissemination of disinformation. Most existing approaches frame face …
Binary ClassificationSCOPE: Siamese Contrastive Operon Pair Embeddings for Functional Sequence Representation and Classification
Identifying operons is a fundamental step in understanding prokaryotic gene regulation, as classifying genes into operons supports the reconstruction of regulatory networks, functional annotation of unannotated genes, an…
Protein Language ModelBinary ClassificationDiscriminative Span as a Predictor of Synthetic Data Utility via Classifier Reconstruction
In many real-world computer vision applications, including medical imaging and industrial inspection, binary classification tasks are characterized by a severe scarcity of positive samples. A widely adopted solution is t…
Binary ClassificationThe Minimax Rate of Second-Order Calibration
We characterize the minimax rate of estimating the second-order calibration error for binary classification, which quantifies whether a higher-order predictor's epistemic-uncertainty estimate matches the conditional vari…
Binary ClassificationIn-Context Positive-Unlabeled Learning
Positive-unlabeled (PU) learning addresses binary classification when only a set of labeled positives is available alongside a pool of unlabeled samples drawn from a mixture of positives and negatives. Existing PU method…
Binary ClassificationTransformer-Based Wildlife Species Classification from Daily Movement Trajectories
Inferring the identity of wildlife species from daily movement data alone is a challenging task. We train sequence models on large-scale, 7-species GPS trajectories from the Movebank platform. Trajectories models are eva…
Binary ClassificationMedical Imaging Classification with Cold-Atom Reservoir Computing using Auto-Encoders and Surrogate-Driven Training
We introduce a hybrid quantum-classical pipeline, based on neutral-atom reservoir computing, for medical image classification, focusing on the binary classification task of polyp detection. To deal effectively with the h…
Medical Image ClassificationBinary ClassificationTFM-Retouche: A Lightweight Input-Space Adapter for Tabular Foundation Models
Tabular foundation models (TFMs), such as TabPFN-2.6, TabICLv2, ConTextTab, Mitra, LimiX, and TabDPT, achieve strong zero-shot performance through in-context learning, but their inductive biases remain fixed at inference…
Binary ClassificationFast Gauss-Newton for Multiclass Cross-Entropy
In multiclass softmax cross-entropy, the full generalized Gauss-Newton (GGN) curvature couples all output logits through the softmax covariance, making curvature-vector products harder to scale as the number of classes g…
Binary ClassificationInductive Venn-Abers and related regressors
Venn-Abers predictors are probabilistic predictors that enjoy appealing properties of validity, but their major limitation is that they have been applicable only to binary classification, apart from a recent extension to…
Binary ClassificationPSK at SemEval-2026 Task 9: Multilingual Polarization Detection Using Ensemble Gemma Models with Synthetic Data Augmentation
We present our system for SemEval-2026 Task 9: Multilingual Polarization Detection, a binary classification task spanning 22 languages. Our approach fine-tunes separate Gemma~3 models (12B and 27B parameters) per languag…
Binary ClassificationData AugmentationSegmenting Human-LLM Co-authored Text via Change Point Detection
The rise of large language models (LLMs) has created an urgent need to distinguish between human-written and LLM-generated text to ensure authenticity and societal trust. Existing detectors typically provide a binary cla…
Change Point DetectionBinary ClassificationText DetectionRethinking the Rank Threshold for LoRA Fine-Tuning
A recent landscape analysis of LoRA fine-tuning in the neural tangent kernel regime establishes a sufficient condition $r(r+1)/2 > KN$ on the LoRA rank $r$ for the absence of spurious local minima under squared-error los…
Binary ClassificationThe Manokhin Probability Matrix: A Diagnostic Framework for Classifier Probability Quality
The Brier score conflates two distinct properties of probabilistic predictions: reliability (calibration error) and resolution (discriminatory power). We introduce the Manokhin Probability Matrix, a BCG-style two-dimensi…
Binary ClassificationFMI_SU_Yotkova_Kastreva at SemEval-2026 Task 13: Lightweight Detection of LLM-Generated Code via Stylometric Signals
SemEval-2026 Task 13 investigates machine-generated code detection across multiple programming languages and application scenarios, asking participating systems to generalize to unseen languages and domains. This paper d…
Binary ClassificationToward Fine-Grained Speech Inpainting Forensics:A Dataset, Method, and Metric for Multi-Region Tampering Localization
Recent advances in voice cloning and text-to-speech synthesis have made partial speech manipulation - where an adversary replaces a few words within an utterance to alter its meaning while preserving the speaker's identi…
Text-To-Speech SynthesisAudio Deepfake DetectionBinary ClassificationPredicting Post Virality with Temporal Cross-Attention over Trend Signals
Current models for predicting social media virality rely heavily on static textual and structural features, effectively ignoring the highly dynamic nature of trend signals. We study whether real-world attention signals c…
Binary ClassificationIs It Novel and Why? Fine-Grained Patent Novelty Prediction Based on Passage Retrieval
Novelty assessment is a critical yet complex task in the examination process for patent acceptance, requiring examiners to determine whether an invention is disclosed in a prior art document. The process involves intrica…
Binary ClassificationPassage RetrievalAn explainable hypothesis-driven approach to Drug-Induced Liver Injury with HADES
Drug-induced liver injury (DILI) remains a leading cause of late-stage clinical trial attrition. However, existing computational predictors primarily rely on binary classification, a framing that limits generalization an…
Binary ClassificationBolek: A Multimodal Language Model for Molecular Reasoning
Molecular property models increasingly support high-stakes drug-discovery decisions, but their outputs are often difficult to audit: classical predictors return scores without rationale, while language models can produce…
Binary Classification