Papers Binary Classification
“Binary Classification” 태그가 달린 논문 3,070편 · 필터 해제
External Observers May See More Clearly: Cross-Model Span-Level Hallucination Detection in Large Language Models via Hidden State Probing
As Large Language Models (LLMs) increasingly serve as foundational reasoning engines, their tendency to hallucinate remains a critical vulnerability. While recent internal state probes offer a promising alternative to sl…
Binary ClassificationControllable Multi-label Video Safety Detection via Adaptive Tversky Policy Optimization
The rapid growth of video-based social media has increased users' exposure to harmful content, creating a need for reliable automated video safety detection. Although recent Vision-Language Models (VLMs) show strong vide…
Reinforcement LearningBinary ClassificationA Hybrid Approach to Malware Detection: Integrating Few-Shot Model-Agnostic Meta-Learning with Autoencoders
Ransomware has emerged as a major cybersecurity threat, with incidents increasing in frequency and impact across critical sectors. These attacks are typically launched through phishing emails, malicious downloads, or exp…
Binary ClassificationMalware DetectionProbPlug: A Plugin Uncertainty Network for Reliable Confidence in LLM Binary Classification
Large language models (LLMs) have achieved strong performance across a broad range of classification settings, yet the reliability of their predictions remains a major obstacle to deployment in high-stakes scenarios. Alt…
Binary ClassificationWho Are They to Each Other? Multi-Agent Reasoning for Speaker Relationship Inference
Inferring speaker relationships from spoken conversations is an important step towards socially aware speech understanding. However, this task remains underexplored, and supervised modeling is costly to train and scale. …
Binary ClassificationSpectral Features Dominate BCG Respiratory-Event Detection: A Large-Scale Patient-Independent Comparison of Feature Groups in Sleep Apnea Patients
Unobtrusive ballistocardiographic (BCG) sensing is a promising modality for long-term sleep-apnea monitoring, yet it remains unclear which signal features are most discriminative for respiratory-event detection. We prese…
Binary ClassificationOver-The-Air Extreme Learning Machines with Nonlinear Stacked Intelligent Metasurfaces
The recently envisioned goal-oriented communications paradigm requires machine learning inference to be performed directly on wirelessly transferred data. This paper presents an eXtremely Large (XL) Multiple-Input Multip…
Binary ClassificationLess Contouring, More Accuracy: Lesion-Guided ROI Deep Learning for Ovarian Ultrasound Classification
Ovarian lesion classification using transvaginal ultrasound remains challenging due to overlapping imaging characteristics and the dependence on expert interpretation. This study investigates whether lesion-guided region…
Binary ClassificationLesion SegmentationAre Concept Bottleneck Models Effective as Decision-Support Systems?
Concept Bottleneck Models (CBMs) are interpretable-by-design neural networks that detect human-understandable concepts from the input and use them to generate predictions. By allowing users to inspect the concepts underl…
Binary ClassificationPolyChirp: Multi-Species Birdsong Classification Using TinyML on Low-Power Acoustic Sensors
Recent progress in the field of TinyML has demonstrated that low-power hardware based on microcontrollers can achieve bird species monitoring in real time based on acoustic sensor data for an entire breeding period on a …
Binary ClassificationReal-TurnTurk: A Multimodal Turkish Corpus for Turn-Taking Prediction
Turn-taking is a basic organizational feature of human conversation and remains difficult to model in natural, synchronous dialog systems. While existing research has explored multimodal approaches and large language mod…
Binary ClassificationExplainable Deepfake Detection with Feature-robust Augmentation and Evidence-grounded Explanation Optimization
Explainable deepfake detection extends binary classification by requiring models to not only predict authenticity but also provide interpretable justifications. This expanded scope is critical in practice, where users li…
Binary ClassificationContrastive LearningDeepFake DetectionImage-Guided Pavement Defect Recognition in GPR Data with novel 3D Deep Learning Architecture
Ground Penetrating Radar (GPR) is a widely adopted non-destructive sensing technology for subsurface inspection in civil and transportation engineering. Despite its potential for pavement condition assessment, the large-…
Binary ClassificationConvex losses and their applications to SVM, SVR, and Shallow Neural Networks
We propose multiple new convex losses for SVM and Neural Networks, applied to binary classification tasks. While there are practical limitations in exploiting them with the dual SVM models, we are able to use them with S…
Binary ClassificationSurv-IPTB: An Attention-Based Model for Estimating Individual Probability of Treatment Benefit with Survival Data
This work presents a novel attention-based framework for estimating the Individual Probability of Treatment Benefit (IPTB) in survival analysis contexts. The proposed model, called Surv-IPTB, directly quantifies the prob…
Binary ClassificationHARGO: Heterogeneity-Aware Reward-Guided Optimization for RL Post-Training of LLMs on HPC Tasks
Supervised fine-tuning (SFT) can equip large language models (LLMs) with domain knowledge for high-performance computing (HPC) tasks such as data race detection and benchmark question answering. However, knowledge alone …
Reinforcement LearningBinary ClassificationQuestion AnsweringCORE: In-Context Reconstruction for Unified Tabular Anomaly Detection
Tabular anomaly detection (TAD), which focuses on identifying abnormal samples that deviate from the majority in tabular data, has received growing attention. Recently, there has been an emerging trend towards unified TA…
Binary ClassificationAnomaly DetectionEgoSafe: A First-Person Mobile-Captured Benchmark for Visual Safety Understanding
Reliable visual safety understanding in real-world scenarios demands more than just object recognition; it requires causal reasoning under epistemic uncertainty. While Large Vision-Language Models (LVLMs) demonstrate imp…
Binary ClassificationObject RecognitionNeurai-VN Benchmark: Standardized Machine Learning Models for Multimodal Digital Phenotyping in Mental Health Classification
Digital phenotyping (DP) using smartphones and wearable devices has shown considerable potential for mental health monitoring. However, progress remains difficult to evaluate due to heterogeneous datasets, inconsistent p…
Binary ClassificationVariable Importance Identification Through Lazy Training for Binary Classification
Deep neural networks have been widely used in many applications (e.g., computer vision and natural language processing); however, understanding their explainability remains a challenging task. Recently, substantial resea…
Binary Classification