{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/binary-classification/papers/15","list_of":"/task/binary-classification","task":"Binary Classification","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":15,"pages_in_order":26,"rows_per_page":100,"rows":[1401,1500],"of":2574,"counts":{"archive_papers_tagged":2574,"with_a_code_link":710,"where_syntology_ran_a_sample":115,"not_listed_spam_title":0,"listed":2574,"listed_where_code_ran":115,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":100,"every_run_a_failure_of_syntologys_instrument":15,"listed_with_a_run_with_no_instrument_failure":100,"listed_every_run_a_failure_of_syntologys_instrument":15,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/binary-classification","prev":"/task/binary-classification/papers/14","next":"/task/binary-classification/papers/16","papers":[{"url":null,"slug":"information-transfer-rate-in-bcis-towards","title":"Information Transfer Rate in BCIs: Towards Tightly Integrated Symbiosis","date":"2023-01-01","arxiv_id":"2301.00488","repositories_listed":0,"syntology":null},{"url":null,"slug":"complai-theory-of-a-unified-framework-for","title":"ComplAI: Theory of A Unified Framework for Multi-factor Assessment of Black-Box Supervised Machine Learning Models","date":"2022-12-30","arxiv_id":"2212.14599","repositories_listed":0,"syntology":null},{"url":null,"slug":"application-of-unsupervised-domain-adaptation","title":"Application of Unsupervised Domain Adaptation for Structural MRI Analysis","date":"2022-12-26","arxiv_id":"2212.12986","repositories_listed":0,"syntology":null},{"url":null,"slug":"content-rating-classification-for-fan-fiction","title":"Content Rating Classification for Fan Fiction","date":"2022-12-23","arxiv_id":"2212.12496","repositories_listed":0,"syntology":null},{"url":null,"slug":"extractive-text-summarization-using","title":"Extractive Text Summarization Using Generalized Additive Models with Interactions for Sentence Selection","date":"2022-12-21","arxiv_id":"2212.10707","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-hybrid-and-ensemble-models-for","title":"Exploring Hybrid and Ensemble Models for Multiclass Prediction of Mental Health Status on Social Media","date":"2022-12-19","arxiv_id":"2212.09839","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-group-robustness-under-noisy-labels","title":"Improving group robustness under noisy labels using predictive uncertainty","date":"2022-12-14","arxiv_id":"2212.07026","repositories_listed":0,"syntology":null},{"url":null,"slug":"population-template-based-brain-graph","title":"Population Template-Based Brain Graph Augmentation for Improving One-Shot Learning Classification","date":"2022-12-14","arxiv_id":"2212.07790","repositories_listed":0,"syntology":null},{"url":null,"slug":"manlp-smm4h22-bert-for-classification-of-1","title":"MaNLP@SMM4H22: BERT for Classification of Twitter Posts","date":"2022-12-12","arxiv_id":"2301.05395","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-approach-for-interruption","title":"Deep learning approach for interruption attacks detection in LEO satellite networks","date":"2022-12-10","arxiv_id":"2301.03998","repositories_listed":0,"syntology":null},{"url":null,"slug":"differentially-private-bayes-consistency","title":"Differentially-Private Bayes Consistency","date":"2022-12-08","arxiv_id":"2212.04216","repositories_listed":0,"syntology":null},{"url":null,"slug":"metric-elicitation-moving-from-theory-to","title":"Metric Elicitation; Moving from Theory to Practice","date":"2022-12-07","arxiv_id":"2212.03495","repositories_listed":0,"syntology":null},{"url":null,"slug":"hybrid-model-using-feature-extraction-and-non","title":"Hybrid Model using Feature Extraction and Non-linear SVM for Brain Tumor Classification","date":"2022-12-06","arxiv_id":"2212.02794","repositories_listed":0,"syntology":null},{"url":null,"slug":"benchmarking-offline-reinforcement-learning","title":"Benchmarking Offline Reinforcement Learning Algorithms for E-Commerce Order Fraud Evaluation","date":"2022-12-05","arxiv_id":"2212.02620","repositories_listed":0,"syntology":null},{"url":null,"slug":"transformers-for-end-to-end-infosec-tasks-a","title":"Transformers for End-to-End InfoSec Tasks: A Feasibility Study","date":"2022-12-05","arxiv_id":"2212.02666","repositories_listed":0,"syntology":null},{"url":null,"slug":"high-dimensional-binary-classification-under","title":"High Dimensional Binary Classification under Label Shift: Phase Transition and Regularization","date":"2022-12-01","arxiv_id":"2212.00700","repositories_listed":0,"syntology":null},{"url":null,"slug":"forged-image-detection-using-sota-image","title":"Forged Image Detection using SOTA Image Classification Deep Learning Methods for Image Forensics with Error Level Analysis","date":"2022-11-28","arxiv_id":"2211.15196","repositories_listed":0,"syntology":null},{"url":null,"slug":"semi-supervised-binary-classification-with","title":"Semi-supervised binary classification with latent distance learning","date":"2022-11-28","arxiv_id":"2211.15153","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-based-vulnerability-detection-1","title":"Deep-Learning-based Vulnerability Detection in Binary Executables","date":"2022-11-25","arxiv_id":"2212.01254","repositories_listed":0,"syntology":null},{"url":null,"slug":"question-type-identification-for-academic","title":"Question-type Identification for Academic Questions in Online Learning Platform","date":"2022-11-24","arxiv_id":"2211.13727","repositories_listed":0,"syntology":null},{"url":null,"slug":"event-causality-identification-with-causal","title":"Event Causality Identification with Causal News Corpus -- Shared Task 3, CASE 2022","date":"2022-11-22","arxiv_id":"2211.12154","repositories_listed":0,"syntology":null},{"url":null,"slug":"photonic-quantum-computing-for-polymer","title":"Photonic Quantum Computing For Polymer Classification","date":"2022-11-22","arxiv_id":"2211.12207","repositories_listed":0,"syntology":null},{"url":null,"slug":"rooms-with-text-a-dataset-for-overlaying-text","title":"Rooms with Text: A Dataset for Overlaying Text Detection","date":"2022-11-21","arxiv_id":"2211.11350","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-artificial-intelligence-and-1","title":"Explainable Artificial Intelligence and Causal Inference based ATM Fraud Detection","date":"2022-11-19","arxiv_id":"2211.10595","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantifying-human-bias-and-knowledge-to-guide","title":"Quantifying Human Bias and Knowledge to guide ML models during Training","date":"2022-11-19","arxiv_id":"2211.10796","repositories_listed":0,"syntology":null},{"url":null,"slug":"audio-anti-spoofing-using-a-simple-attention","title":"Audio Anti-spoofing Using a Simple Attention Module and Joint Optimization Based on Additive Angular Margin Loss and Meta-learning","date":"2022-11-17","arxiv_id":"2211.09898","repositories_listed":0,"syntology":null},{"url":null,"slug":"detecting-disengagement-in-virtual-learning","title":"Detecting Disengagement in Virtual Learning as an Anomaly using Temporal Convolutional Network Autoencoder","date":"2022-11-13","arxiv_id":"2211.06870","repositories_listed":0,"syntology":null},{"url":null,"slug":"rethinking-log-odds-linear-probability","title":"Rethinking Log Odds: Linear Probability Modelling and Expert Advice in Interpretable Machine Learning","date":"2022-11-11","arxiv_id":"2211.06360","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-improved-learning-in-gaussian","title":"Towards Improved Learning in Gaussian Processes: The Best of Two Worlds","date":"2022-11-11","arxiv_id":"2211.06260","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimized-global-perturbation-attacks-for","title":"Optimized Global Perturbation Attacks For Brain Tumour ROI Extraction From Binary Classification Models","date":"2022-11-09","arxiv_id":"2211.04926","repositories_listed":0,"syntology":null},{"url":null,"slug":"are-face-detection-models-biased","title":"Are Face Detection Models Biased?","date":"2022-11-07","arxiv_id":"2211.03588","repositories_listed":0,"syntology":null},{"url":null,"slug":"accurate-and-reliable-methods-for-5g-uav","title":"Accurate and Reliable Methods for 5G UAV Jamming Identification With Calibrated Uncertainty","date":"2022-11-05","arxiv_id":"2211.02924","repositories_listed":0,"syntology":null},{"url":null,"slug":"preserving-in-context-learning-ability-in","title":"Two-stage LLM Fine-tuning with Less Specialization and More Generalization","date":"2022-11-01","arxiv_id":"2211.00635","repositories_listed":0,"syntology":null},{"url":null,"slug":"xtreme-margin-a-tunable-loss-function-for","title":"Xtreme Margin: A Tunable Loss Function for Binary Classification Problems","date":"2022-10-31","arxiv_id":"2211.00176","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-importance-of-speech-stimuli-for","title":"Influence of Utterance and Speaker Characteristics on the Classification of Children with Cleft Lip and Palate","date":"2022-10-28","arxiv_id":"2210.15941","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-class-detection-of-pathological-speech","title":"Multi-class Detection of Pathological Speech with Latent Features: How does it perform on unseen data?","date":"2022-10-27","arxiv_id":"2210.15336","repositories_listed":0,"syntology":null},{"url":null,"slug":"stochastic-mirror-descent-in-average-ensemble","title":"Stochastic Mirror Descent in Average Ensemble Models","date":"2022-10-27","arxiv_id":"2210.15323","repositories_listed":0,"syntology":null},{"url":null,"slug":"prove-a-pipeline-for-automated-provenance","title":"ProVe: A Pipeline for Automated Provenance Verification of Knowledge Graphs against Textual Sources","date":"2022-10-26","arxiv_id":"2210.14846","repositories_listed":0,"syntology":null},{"url":null,"slug":"interpolating-discriminant-functions-in-high","title":"Interpolating Discriminant Functions in High-Dimensional Gaussian Latent Mixtures","date":"2022-10-25","arxiv_id":"2210.14347","repositories_listed":0,"syntology":null},{"url":null,"slug":"investigating-the-detection-of-tortured-1","title":"Investigating the detection of Tortured Phrases in Scientific Literature","date":"2022-10-24","arxiv_id":"2210.13024","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-understanding-gd-with-hard-and","title":"Towards Understanding GD with Hard and Conjugate Pseudo-labels for Test-Time Adaptation","date":"2022-10-18","arxiv_id":"2210.10019","repositories_listed":0,"syntology":null},{"url":null,"slug":"review-learning-alleviating-catastrophic","title":"Review Learning: Alleviating Catastrophic Forgetting with Generative Replay without Generator","date":"2022-10-17","arxiv_id":"2210.09394","repositories_listed":0,"syntology":null},{"url":null,"slug":"explaining-machine-learning-models-for-age","title":"Explaining machine learning models for age classification in human gait analysis","date":"2022-10-16","arxiv_id":"2211.17016","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-fault-detection-scheme-utilizing","title":"A Fault Detection Scheme Utilizing Convolutional Neural Network for PV Solar Panels with High Accuracy","date":"2022-10-14","arxiv_id":"2210.09226","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-dysgraphia-detection-by-deep","title":"Automated dysgraphia detection by deep learning with SensoGrip","date":"2022-10-14","arxiv_id":"2210.07659","repositories_listed":0,"syntology":null},{"url":null,"slug":"vision-transformers-provably-learn-spatial","title":"Vision Transformers provably learn spatial structure","date":"2022-10-13","arxiv_id":"2210.09221","repositories_listed":0,"syntology":null},{"url":null,"slug":"synthetic-voice-detection-and-audio-splicing","title":"Synthetic Voice Detection and Audio Splicing Detection using SE-Res2Net-Conformer Architecture","date":"2022-10-07","arxiv_id":"2210.03581","repositories_listed":0,"syntology":null},{"url":null,"slug":"mutual-information-learned-classifiers-an-1","title":"Mutual Information Learned Classifiers: an Information-theoretic Viewpoint of Training Deep Learning Classification Systems","date":"2022-10-03","arxiv_id":"2210.01000","repositories_listed":0,"syntology":null},{"url":null,"slug":"effective-data-augmentation-for-sentence","title":"Effective Data Augmentation for Sentence Classification Using One VAE per Class","date":"2022-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"hierarchical-neyman-pearson-classification","title":"Hierarchical Neyman-Pearson Classification for Prioritizing Severe Disease Categories in COVID-19 Patient Data","date":"2022-10-01","arxiv_id":"2210.02197","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-evaluate-humor-in-memes-based-on","title":"Learning to Evaluate Humor in Memes Based on the Incongruity Theory","date":"2022-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"manlp-smm4h22-bert-for-classification-of","title":"MaNLP@SMM4H’22: BERT for Classification of Twitter Posts","date":"2022-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"overview-of-the-dagpap22-shared-task-on","title":"Overview of the DAGPap22 Shared Task on Detecting Automatically Generated Scientific Papers","date":"2022-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"ub-health-miners-smm4h22-exploring-pre","title":"UB Health Miners@SMM4H’22: Exploring Pre-processing Techniques To Classify Tweets Using Transformer Based Pipelines.","date":"2022-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"correlated-feature-aggregation-by-region","title":"Correlated Feature Aggregation by Region Helps Distinguish Aggressive from Indolent Clear Cell Renal Cell Carcinoma Subtypes on CT","date":"2022-09-29","arxiv_id":"2209.14657","repositories_listed":0,"syntology":null},{"url":null,"slug":"mulbot-unsupervised-bot-detection-based-on","title":"MulBot: Unsupervised Bot Detection Based on Multivariate Time Series","date":"2022-09-21","arxiv_id":"2209.10361","repositories_listed":0,"syntology":null},{"url":null,"slug":"mutual-information-learned-classifiers-an","title":"Mutual Information Learned Classifiers: an Information-theoretic Viewpoint of Training Deep Learning Classification Systems","date":"2022-09-21","arxiv_id":"2209.10058","repositories_listed":0,"syntology":null},{"url":null,"slug":"superpixel-generation-and-clustering-for","title":"Deep Superpixel Generation and Clustering for Weakly Supervised Segmentation of Brain Tumors in MR Images","date":"2022-09-20","arxiv_id":"2209.09930","repositories_listed":0,"syntology":null},{"url":null,"slug":"trigger-warnings-bootstrapping-a-violence","title":"Trigger Warnings: Bootstrapping a Violence Detector for FanFiction","date":"2022-09-09","arxiv_id":"2209.04409","repositories_listed":0,"syntology":null},{"url":null,"slug":"grouping-matrix-based-graph-pooling-with","title":"Grouping-matrix based Graph Pooling with Adaptive Number of Clusters","date":"2022-09-07","arxiv_id":"2209.02939","repositories_listed":0,"syntology":null},{"url":null,"slug":"effective-class-imbalance-learning-based-on","title":"Effective Class-Imbalance learning based on SMOTE and Convolutional Neural Networks","date":"2022-09-01","arxiv_id":"2209.00653","repositories_listed":0,"syntology":null},{"url":null,"slug":"using-taylor-approximated-gradients-to","title":"Using Taylor-Approximated Gradients to Improve the Frank-Wolfe Method for Empirical Risk Minimization","date":"2022-08-30","arxiv_id":"2208.13933","repositories_listed":0,"syntology":null},{"url":null,"slug":"two-stage-fall-events-classification-with","title":"Two-stage Fall Events Classification with Human Skeleton Data","date":"2022-08-25","arxiv_id":"2208.12027","repositories_listed":0,"syntology":null},{"url":null,"slug":"faint-features-tell-automatic-vertebrae","title":"Faint Features Tell: Automatic Vertebrae Fracture Screening Assisted by Contrastive Learning","date":"2022-08-23","arxiv_id":"2208.10698","repositories_listed":0,"syntology":null},{"url":null,"slug":"system-fingerprints-detection-for-deepfake","title":"Audio Deepfake Attribution: An Initial Dataset and Investigation","date":"2022-08-21","arxiv_id":"2208.10489","repositories_listed":0,"syntology":null},{"url":null,"slug":"classification-performance-metric-elicitation","title":"Classification Performance Metric Elicitation and its Applications","date":"2022-08-19","arxiv_id":"2208.09142","repositories_listed":0,"syntology":null},{"url":null,"slug":"fold-se-scalable-explainable-ai","title":"FOLD-SE: An Efficient Rule-based Machine Learning Algorithm with Scalable Explainability","date":"2022-08-16","arxiv_id":"2208.07912","repositories_listed":0,"syntology":null},{"url":null,"slug":"is-your-model-sensitive-spedac-a-new","title":"Is Your Model Sensitive? SPeDaC: A New Benchmark for Detecting and Classifying Sensitive Personal Data","date":"2022-08-12","arxiv_id":"2208.06216","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-prediction-of-qcodes-for-notams","title":"Explainable prediction of Qcodes for NOTAMs using column generation","date":"2022-08-09","arxiv_id":"2208.04955","repositories_listed":0,"syntology":null},{"url":null,"slug":"data-centric-ai-approach-to-improve-optic","title":"Data-centric AI approach to improve optic nerve head segmentation and localization in OCT en face images","date":"2022-08-08","arxiv_id":"2208.03868","repositories_listed":0,"syntology":null},{"url":null,"slug":"gradient-flows-for-l2-support-vector-machine","title":"Gradient Flows for L2 Support Vector Machine Training","date":"2022-08-08","arxiv_id":"2208.04365","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-example-of-use-of-variational-methods-in","title":"An example of use of Variational Methods in Quantum Machine Learning","date":"2022-08-07","arxiv_id":"2208.04316","repositories_listed":0,"syntology":null},{"url":null,"slug":"compressing-multidimensional-learned-bloom-1","title":"Compressing (Multidimensional) Learned Bloom Filters","date":"2022-08-05","arxiv_id":"2208.03029","repositories_listed":0,"syntology":null},{"url":null,"slug":"transformer-convolutional-neural-networks-for","title":"Transformer Convolutional Neural Networks for Automated Artifact Detection in Scalp EEG","date":"2022-08-04","arxiv_id":"2208.02405","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-novel-approach-to-network-intrusion","title":"A Novel Approach To Network Intrusion Detection System Using Deep Learning For Sdn: Futuristic Approach","date":"2022-08-03","arxiv_id":"2208.02094","repositories_listed":0,"syntology":null},{"url":null,"slug":"binary-classification-with-positive-labeling","title":"Binary Classification with Positive Labeling Sources","date":"2022-08-02","arxiv_id":"2208.01704","repositories_listed":0,"syntology":null},{"url":null,"slug":"is-attention-interpretation-a-quantitative","title":"Is Attention Interpretation? A Quantitative Assessment On Sets","date":"2022-07-26","arxiv_id":"2207.13018","repositories_listed":0,"syntology":null},{"url":null,"slug":"overview-of-the-shared-task-on-fake-news-1","title":"Overview of the Shared Task on Fake News Detection in Urdu at FIRE 2020","date":"2022-07-25","arxiv_id":"2207.11893","repositories_listed":0,"syntology":null},{"url":null,"slug":"urdufake-fire2020-shared-track-on-fake-news","title":"UrduFake@FIRE2020: Shared Track on Fake News Identification in Urdu","date":"2022-07-25","arxiv_id":"2207.12406","repositories_listed":0,"syntology":null},{"url":null,"slug":"octal-graph-representation-learning-for-ltl","title":"OCTAL: Graph Representation Learning for LTL Model Checking","date":"2022-07-24","arxiv_id":"2207.11649","repositories_listed":0,"syntology":null},{"url":null,"slug":"classification-via-score-based-generative","title":"Classification via score-based generative modelling","date":"2022-07-22","arxiv_id":"2207.11091","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-from-few-examples-classifying-sex","title":"Learning from few examples: Classifying sex from retinal images via deep learning","date":"2022-07-20","arxiv_id":"2207.09624","repositories_listed":0,"syntology":null},{"url":null,"slug":"subclass-knowledge-distillation-with-known","title":"Subclass Knowledge Distillation with Known Subclass Labels","date":"2022-07-17","arxiv_id":"2207.08063","repositories_listed":0,"syntology":null},{"url":null,"slug":"problexity-an-open-source-python-library-for","title":"problexity -- an open-source Python library for binary classification problem complexity assessment","date":"2022-07-14","arxiv_id":"2207.06709","repositories_listed":0,"syntology":null},{"url":null,"slug":"qsan-a-near-term-achievable-quantum-self","title":"QSAN: A Near-term Achievable Quantum Self-Attention Network","date":"2022-07-14","arxiv_id":"2207.07563","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-merging-feature-engineering-and-deep","title":"On Merging Feature Engineering and Deep Learning for Diagnosis, Risk-Prediction and Age Estimation Based on the 12-Lead ECG","date":"2022-07-13","arxiv_id":"2207.06096","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-understanding-how-momentum-improves-1","title":"Towards understanding how momentum improves generalization in deep learning","date":"2022-07-13","arxiv_id":"2207.05931","repositories_listed":0,"syntology":null},{"url":null,"slug":"overview-of-the-shared-task-on-fake-news","title":"Overview of the Shared Task on Fake News Detection in Urdu at FIRE 2021","date":"2022-07-11","arxiv_id":"2207.05133","repositories_listed":0,"syntology":null},{"url":null,"slug":"urdufake-fire2021-shared-track-on-fake-news","title":"UrduFake@FIRE2021: Shared Track on Fake News Identification in Urdu","date":"2022-07-11","arxiv_id":"2207.05144","repositories_listed":0,"syntology":null},{"url":null,"slug":"detecting-people-interested-in-non-suicidal","title":"Detecting People Interested in Non-Suicidal Self-Injury on Social Media","date":"2022-07-10","arxiv_id":"2207.07014","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-intrinsic-common-discriminative","title":"Towards Intrinsic Common Discriminative Features Learning for Face Forgery Detection using Adversarial Learning","date":"2022-07-08","arxiv_id":"2207.03776","repositories_listed":0,"syntology":null},{"url":null,"slug":"virtual-axle-detector-based-on-analysis-of","title":"Virtual Axle Detector based on Analysis of Bridge Acceleration Measurements by Fully Convolutional Network","date":"2022-07-08","arxiv_id":"2207.03758","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-novel-iot-based-framework-for-non-invasive","title":"A Novel IoT-based Framework for Non-Invasive Human Hygiene Monitoring using Machine Learning Techniques","date":"2022-07-07","arxiv_id":"2207.03529","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-hybrid-approach-for-binary-classification","title":"A Hybrid Approach for Binary Classification of Imbalanced Data","date":"2022-07-06","arxiv_id":"2207.02738","repositories_listed":0,"syntology":null},{"url":null,"slug":"amsqr-at-semeval-2022-task-4-towards-autonlp","title":"Amsqr at SemEval-2022 Task 4: Towards AutoNLP via Meta-Learning and Adversarial Data Augmentation for PCL Detection","date":"2022-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"asrtrans-at-semeval-2022-task-5-transformer","title":"ASRtrans at SemEval-2022 Task 5: Transformer-based Models for Meme Classification","date":"2022-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"cardiffnlp-metaphor-at-semeval-2022-task-2","title":"CardiffNLP-Metaphor at SemEval-2022 Task 2: Targeted Fine-tuning of Transformer-based Language Models for Idiomaticity Detection","date":"2022-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"felix-julia-at-semeval-2022-task-4","title":"Felix&Julia at SemEval-2022 Task 4: Patronizing and Condescending Language Detection","date":"2022-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"guts-at-semeval-2022-task-4-adversarial","title":"GUTS at SemEval-2022 Task 4: Adversarial Training and Balancing Methods for Patronizing and Condescending Language Detection","date":"2022-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"hw-tsc-at-semeval-2022-task-3-a-unified","title":"HW-TSC at SemEval-2022 Task 3: A Unified Approach Fine-tuned on Multilingual Pretrained Model for PreTENS","date":"2022-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null}],"record_sha256":"cb20d84ef4b19961047d632830f682633bfd0ad14b36bed3a848ae0ac889c56c","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}