{"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/attribute/papers/37","list_of":"/task/attribute","task":"Attribute","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":37,"pages_in_order":54,"rows_per_page":100,"rows":[3601,3700],"of":5387,"counts":{"archive_papers_tagged":5387,"with_a_code_link":1923,"where_syntology_ran_a_sample":475,"not_listed_spam_title":0,"listed":5387,"listed_where_code_ran":475,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":387,"every_run_a_failure_of_syntologys_instrument":88,"listed_with_a_run_with_no_instrument_failure":387,"listed_every_run_a_failure_of_syntologys_instrument":88,"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/attribute","prev":"/task/attribute/papers/36","next":"/task/attribute/papers/38","papers":[{"url":null,"slug":"controlling-extra-textual-attributes-about","title":"Controlling Extra-Textual Attributes about Dialogue Participants -- A Case Study of English-to-Polish Neural Machine Translation","date":"2022-05-10","arxiv_id":"2205.04747","repositories_listed":0,"syntology":null},{"url":null,"slug":"reconstruction-enhanced-multi-view","title":"Reconstruction Enhanced Multi-View Contrastive Learning for Anomaly Detection on Attributed Networks","date":"2022-05-10","arxiv_id":"2205.04816","repositories_listed":0,"syntology":null},{"url":null,"slug":"acm-attribute-conditioning-for-abstractive","title":"ACM -- Attribute Conditioning for Abstractive Multi Document Summarization","date":"2022-05-09","arxiv_id":"2205.03978","repositories_listed":0,"syntology":null},{"url":null,"slug":"interpretable-machine-learning-for-self","title":"Interpretable Machine Learning for Self-Service High-Risk Decision-Making","date":"2022-05-09","arxiv_id":"2205.04032","repositories_listed":0,"syntology":null},{"url":null,"slug":"joint-learning-of-object-graph-and-relation","title":"Joint learning of object graph and relation graph for visual question answering","date":"2022-05-09","arxiv_id":"2205.04188","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-disentangled-textual-representations","title":"Learning Disentangled Textual Representations via Statistical Measures of Similarity","date":"2022-05-07","arxiv_id":"2205.03589","repositories_listed":0,"syntology":null},{"url":null,"slug":"cats-are-fuzzy-pets-a-corpus-and-analysis-of","title":"CATs are Fuzzy PETs: A Corpus and Analysis of Potentially Euphemistic Terms","date":"2022-05-05","arxiv_id":"2205.02728","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-disentangled-and-locally-fair","title":"On Disentangled and Locally Fair Representations","date":"2022-05-05","arxiv_id":"2205.02673","repositories_listed":0,"syntology":null},{"url":null,"slug":"nonstationary-bandit-learning-via-predictive","title":"Non-Stationary Bandit Learning via Predictive Sampling","date":"2022-05-04","arxiv_id":"2205.01970","repositories_listed":0,"syntology":null},{"url":null,"slug":"assessing-confidence-with-assurance-2-0","title":"Assessing Confidence with Assurance 2.0","date":"2022-05-03","arxiv_id":"2205.04522","repositories_listed":0,"syntology":null},{"url":null,"slug":"assessing-dataset-bias-in-computer-vision","title":"Assessing Dataset Bias in Computer Vision","date":"2022-05-03","arxiv_id":"2205.01811","repositories_listed":0,"syntology":null},{"url":null,"slug":"continuing-pre-trained-model-with-multiple","title":"Continuing Pre-trained Model with Multiple Training Strategies for Emotional Classification","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"data-quality-estimation-framework-for-faster","title":"Data Quality Estimation Framework for Faster Tax Code Classification","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"de-bias-for-generative-extraction-in-unified","title":"De-Bias for Generative Extraction in Unified NER Task","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"echogen-generating-conclusions-from","title":"EchoGen: Generating Conclusions from Echocardiogram Notes","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"extreme-multi-label-classification-with-label","title":"Extreme Multi-Label Classification with Label Masking for Product Attribute Value Extraction","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-controllable-text-generation-with-1","title":"Improving Controllable Text Generation with Position-Aware Weighted Decoding","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"interactive-latent-knowledge-selection-for-e","title":"Interactive Latent Knowledge Selection for E-Commerce Product Copywriting Generation","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"molecular-identification-from-afm-images","title":"Molecular Identification from AFM images using the IUPAC Nomenclature and Attribute Multimodal Recurrent Neural Networks","date":"2022-05-01","arxiv_id":"2205.00449","repositories_listed":0,"syntology":null},{"url":null,"slug":"product-titles-to-attributes-as-a-text-to","title":"Product Titles-to-Attributes As a Text-to-Text Task","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"semipqa-a-study-on-product-question-answering","title":"semiPQA: A Study on Product Question Answering over Semi-structured Data","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"fairsr-fairness-aware-sequential","title":"FairSR: Fairness-aware Sequential Recommendation through Multi-Task Learning with Preference Graph Embeddings","date":"2022-04-30","arxiv_id":"2205.00313","repositories_listed":0,"syntology":null},{"url":null,"slug":"heterogeneous-graph-neural-networks-using","title":"Heterogeneous Graph Neural Networks using Self-supervised Reciprocally Contrastive Learning","date":"2022-04-30","arxiv_id":"2205.00256","repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-learning-from-multivariate-dependent","title":"Graph Learning from Multivariate Dependent Time Series via a Multi-Attribute Formulation","date":"2022-04-29","arxiv_id":"2205.00007","repositories_listed":0,"syntology":null},{"url":null,"slug":"ae-nerf-auto-encoding-neural-radiance-fields","title":"AE-NeRF: Auto-Encoding Neural Radiance Fields for 3D-Aware Object Manipulation","date":"2022-04-28","arxiv_id":"2204.13426","repositories_listed":0,"syntology":null},{"url":null,"slug":"discriminative-region-attention-and","title":"Discriminative-Region Attention and Orthogonal-View Generation Model for Vehicle Re-Identification","date":"2022-04-28","arxiv_id":"2204.13323","repositories_listed":0,"syntology":null},{"url":null,"slug":"tailor-a-prompt-based-approach-to-attribute","title":"Tailor: A Prompt-Based Approach to Attribute-Based Controlled Text Generation","date":"2022-04-28","arxiv_id":"2204.13362","repositories_listed":0,"syntology":null},{"url":null,"slug":"discovering-representative-attribute-stars","title":"Discovering Representative Attribute-stars via Minimum Description Length","date":"2022-04-27","arxiv_id":"2204.12704","repositories_listed":0,"syntology":null},{"url":null,"slug":"svd-perspectives-for-augmenting-deeponet","title":"SVD Perspectives for Augmenting DeepONet Flexibility and Interpretability","date":"2022-04-27","arxiv_id":"2204.12670","repositories_listed":0,"syntology":null},{"url":null,"slug":"4dac-learning-attribute-compression-for","title":"4DAC: Learning Attribute Compression for Dynamic Point Clouds","date":"2022-04-25","arxiv_id":"2204.11723","repositories_listed":0,"syntology":null},{"url":null,"slug":"constructing-dynamic-residential-energy","title":"Constructing dynamic residential energy lifestyles using Latent Dirichlet Allocation","date":"2022-04-22","arxiv_id":"2204.10770","repositories_listed":0,"syntology":null},{"url":null,"slug":"benchmarking-answer-verification-methods-for-1","title":"Benchmarking Answer Verification Methods for Question Answering-Based Summarization Evaluation Metrics","date":"2022-04-21","arxiv_id":"2204.10206","repositories_listed":0,"syntology":null},{"url":null,"slug":"graphhop-new-insights-into-graphhop-and-its","title":"Label Efficient Regularization and Propagation for Graph Node Classification","date":"2022-04-19","arxiv_id":"2204.08646","repositories_listed":0,"syntology":null},{"url":null,"slug":"demographic-reliant-algorithmic-fairness","title":"Demographic-Reliant Algorithmic Fairness: Characterizing the Risks of Demographic Data Collection in the Pursuit of Fairness","date":"2022-04-18","arxiv_id":"2205.01038","repositories_listed":0,"syntology":null},{"url":null,"slug":"fair-classification-under-covariate-shift-and","title":"Fair Classification under Covariate Shift and Missing Protected Attribute -- an Investigation using Related Features","date":"2022-04-17","arxiv_id":"2204.07987","repositories_listed":0,"syntology":null},{"url":null,"slug":"global-supervised-contrastive-loss-and-view","title":"Global-Supervised Contrastive Loss and View-Aware-Based Post-Processing for Vehicle Re-Identification","date":"2022-04-17","arxiv_id":"2204.07943","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-compositional-representations-for-1","title":"Learning Compositional Representations for Effective Low-Shot Generalization","date":"2022-04-17","arxiv_id":"2204.08090","repositories_listed":0,"syntology":null},{"url":null,"slug":"sources-of-irreproducibility-in-machine","title":"Sources of Irreproducibility in Machine Learning: A Review","date":"2022-04-15","arxiv_id":"2204.07610","repositories_listed":0,"syntology":null},{"url":null,"slug":"estimating-structural-disparities-for-face","title":"Estimating Structural Disparities for Face Models","date":"2022-04-13","arxiv_id":"2204.06562","repositories_listed":0,"syntology":null},{"url":null,"slug":"stylized-knowledge-grounded-dialogue","title":"Stylized Knowledge-Grounded Dialogue Generation via Disentangled Template Rewriting","date":"2022-04-12","arxiv_id":"2204.05610","repositories_listed":0,"syntology":null},{"url":null,"slug":"dependable-intrusion-detection-system-for-iot","title":"Dependable Intrusion Detection System for IoT: A Deep Transfer Learning-based Approach","date":"2022-04-11","arxiv_id":"2204.04837","repositories_listed":0,"syntology":null},{"url":null,"slug":"gaining-insights-into-unrecognized-user","title":"Gaining Insights into Unrecognized User Utterances in Task-Oriented Dialog Systems","date":"2022-04-11","arxiv_id":"2204.05158","repositories_listed":0,"syntology":null},{"url":null,"slug":"process-mining-on-uncertain-event-data","title":"Process Mining on Uncertain Event Data","date":"2022-04-08","arxiv_id":"2204.04148","repositories_listed":0,"syntology":null},{"url":null,"slug":"marrying-fairness-and-explainability-in","title":"Marrying Fairness and Explainability in Supervised Learning","date":"2022-04-06","arxiv_id":"2204.02947","repositories_listed":0,"syntology":null},{"url":null,"slug":"representation-selective-self-distillation","title":"Representation Selective Self-distillation and wav2vec 2.0 Feature Exploration for Spoof-aware Speaker Verification","date":"2022-04-06","arxiv_id":"2204.02639","repositories_listed":0,"syntology":null},{"url":null,"slug":"spread-spurious-attribute-improving-worst-1","title":"Spread Spurious Attribute: Improving Worst-group Accuracy with Spurious Attribute Estimation","date":"2022-04-05","arxiv_id":"2204.02070","repositories_listed":0,"syntology":null},{"url":"/paper/attribute-prototype-network-for-any-shot","slug":"attribute-prototype-network-for-any-shot","title":"Attribute Prototype Network for Any-Shot Learning","date":"2022-04-04","arxiv_id":"2204.01208","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalized-zero-shot-learning-for-medical","title":"Interpretable Saliency Maps And Self-Supervised Learning For Generalized Zero Shot Medical Image Classification","date":"2022-04-04","arxiv_id":"2204.01728","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-web-phishing-detection-limitations","title":"Towards Web Phishing Detection Limitations and Mitigation","date":"2022-04-03","arxiv_id":"2204.00985","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-versatile-framework-for-evaluating-ranked","title":"A Versatile Framework for Evaluating Ranked Lists in terms of Group Fairness and Relevance","date":"2022-04-01","arxiv_id":"2204.00280","repositories_listed":0,"syntology":null},{"url":null,"slug":"fairrank-fairness-aware-single-tower-ranking","title":"FairRank: Fairness-aware Single-tower Ranking Framework for News Recommendation","date":"2022-04-01","arxiv_id":"2204.00541","repositories_listed":0,"syntology":null},{"url":null,"slug":"semi-fairvae-semi-supervised-fair","title":"Semi-FairVAE: Semi-supervised Fair Representation Learning with Adversarial Variational Autoencoder","date":"2022-04-01","arxiv_id":"2204.00536","repositories_listed":0,"syntology":null},{"url":null,"slug":"robin-a-robust-interpretable-deep-network-for","title":"RobIn: A Robust Interpretable Deep Network for Schizophrenia Diagnosis","date":"2022-03-31","arxiv_id":"2203.17085","repositories_listed":0,"syntology":null},{"url":null,"slug":"truth-serum-poisoning-machine-learning-models","title":"Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets","date":"2022-03-31","arxiv_id":"2204.00032","repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-reputation-independence-in-ranking","title":"Robust Reputation Independence in Ranking Systems for Multiple Sensitive Attributes","date":"2022-03-30","arxiv_id":"2203.16663","repositories_listed":0,"syntology":null},{"url":null,"slug":"disentangling-speech-from-surroundings-in-a","title":"Disentangling speech from surroundings with neural embeddings","date":"2022-03-29","arxiv_id":"2203.15578","repositories_listed":0,"syntology":null},{"url":null,"slug":"hybrid-routing-transformer-for-zero-shot","title":"Hybrid Routing Transformer for Zero-Shot Learning","date":"2022-03-29","arxiv_id":"2203.15310","repositories_listed":0,"syntology":null},{"url":null,"slug":"adversarial-representation-sharing-a","title":"Adversarial Representation Sharing: A Quantitative and Secure Collaborative Learning Framework","date":"2022-03-27","arxiv_id":"2203.14299","repositories_listed":0,"syntology":null},{"url":null,"slug":"3d-gan-inversion-for-controllable-portrait","title":"3D GAN Inversion for Controllable Portrait Image Animation","date":"2022-03-25","arxiv_id":"2203.13441","repositories_listed":0,"syntology":null},{"url":null,"slug":"navigable-proximity-graph-driven-native","title":"Navigable Proximity Graph-Driven Native Hybrid Queries with Structured and Unstructured Constraints","date":"2022-03-25","arxiv_id":"2203.13601","repositories_listed":0,"syntology":null},{"url":null,"slug":"intrinsic-bias-identification-on-medical","title":"Intrinsic Bias Identification on Medical Image Datasets","date":"2022-03-24","arxiv_id":"2203.12872","repositories_listed":0,"syntology":null},{"url":null,"slug":"is-fairness-only-metric-deep-evaluating-and-1","title":"Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning","date":"2022-03-23","arxiv_id":"2203.12748","repositories_listed":0,"syntology":null},{"url":null,"slug":"gated-domain-invariant-feature","title":"Gated Domain-Invariant Feature Disentanglement for Domain Generalizable Object Detection","date":"2022-03-22","arxiv_id":"2203.11432","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-modal-learning-using-physicians","title":"Multi-Modal Learning Using Physicians Diagnostics for Optical Coherence Tomography Classification","date":"2022-03-20","arxiv_id":"2203.10622","repositories_listed":0,"syntology":null},{"url":null,"slug":"analyzing-speaker-verification-embedding","title":"Analyzing speaker verification embedding extractors and back-ends under language and channel mismatch","date":"2022-03-19","arxiv_id":"2203.10300","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-price-of-unfairness-in-linear-bandits","title":"The price of unfairness in linear bandits with biased feedback","date":"2022-03-18","arxiv_id":"2203.09784","repositories_listed":0,"syntology":null},{"url":null,"slug":"lorenz-map-inequality-ordering-and-curves","title":"Lorenz map, inequality ordering and curves based on multidimensional rearrangements","date":"2022-03-17","arxiv_id":"2203.09000","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-aligned-fusion-transformer-for-one","title":"Semantic-aligned Fusion Transformer for One-shot Object Detection","date":"2022-03-17","arxiv_id":"2203.09093","repositories_listed":0,"syntology":null},{"url":null,"slug":"measuring-fairness-of-text-classifiers-via-1","title":"Measuring Fairness of Text Classifiers via Prediction Sensitivity","date":"2022-03-16","arxiv_id":"2203.08670","repositories_listed":0,"syntology":null},{"url":null,"slug":"differentiated-relevances-embedding-for-group","title":"Differentiated Relevances Embedding for Group-based Referring Expression Comprehension","date":"2022-03-12","arxiv_id":"2203.06382","repositories_listed":0,"syntology":null},{"url":null,"slug":"stylebabel-artistic-style-tagging-and","title":"StyleBabel: Artistic Style Tagging and Captioning","date":"2022-03-10","arxiv_id":"2203.05321","repositories_listed":0,"syntology":null},{"url":null,"slug":"estimating-the-uncertainty-in-emotion-class","title":"Estimating the Uncertainty in Emotion Class Labels with Utterance-Specific Dirichlet Priors","date":"2022-03-08","arxiv_id":"2203.04443","repositories_listed":0,"syntology":null},{"url":null,"slug":"it-s-ai-match-a-two-step-approach-for-schema","title":"It's AI Match: A Two-Step Approach for Schema Matching Using Embeddings","date":"2022-03-08","arxiv_id":"2203.04366","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-modal-attribute-extraction-for-e","title":"Multi-Modal Attribute Extraction for E-Commerce","date":"2022-03-07","arxiv_id":"2203.03441","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-split-semantic-detection-algorithm-for","title":"Split Semantic Detection in Sandplay Images","date":"2022-03-02","arxiv_id":"2203.00907","repositories_listed":0,"syntology":null},{"url":null,"slug":"assortative-pairing-alone-can-lead-to-a","title":"Assortative pairing alone can lead to a structured biota in organisms with cultural transmission","date":"2022-02-28","arxiv_id":"2202.13685","repositories_listed":0,"syntology":null},{"url":null,"slug":"controllable-natural-language-generation-with-1","title":"Controllable Natural Language Generation with Contrastive Prefixes","date":"2022-02-27","arxiv_id":"2202.13257","repositories_listed":0,"syntology":null},{"url":null,"slug":"vertical-machine-unlearning-selectively","title":"Efficient Attribute Unlearning: Towards Selective Removal of Input Attributes from Feature Representations","date":"2022-02-27","arxiv_id":"2202.13295","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-general-framework-for-adaptive-two-index","title":"A general framework for adaptive two-index fusion attribute weighted naive Bayes","date":"2022-02-24","arxiv_id":"2202.11963","repositories_listed":0,"syntology":null},{"url":null,"slug":"community-trend-prediction-on-heterogeneous","title":"Community Trend Prediction on Heterogeneous Graph in E-commerce","date":"2022-02-24","arxiv_id":"2202.12081","repositories_listed":0,"syntology":null},{"url":null,"slug":"controlling-memorability-of-face-images","title":"Controlling Memorability of Face Images","date":"2022-02-24","arxiv_id":"2202.11896","repositories_listed":0,"syntology":null},{"url":null,"slug":"koopman-spectral-analysis-of-intermittent","title":"Koopman Spectral Analysis of Intermittent Dynamics in Complex Systems: A Case Study in Pathophysiological Processes of Obstructive Sleep Apnea","date":"2022-02-24","arxiv_id":"2202.12430","repositories_listed":0,"syntology":null},{"url":null,"slug":"fairness-aware-naive-bayes-classifier-for","title":"Fairness-Aware Naive Bayes Classifier for Data with Multiple Sensitive Features","date":"2022-02-23","arxiv_id":"2202.11499","repositories_listed":0,"syntology":null},{"url":null,"slug":"slogan-handwriting-style-synthesis-for","title":"SLOGAN: Handwriting Style Synthesis for Arbitrary-Length and Out-of-Vocabulary Text","date":"2022-02-23","arxiv_id":"2202.11456","repositories_listed":0,"syntology":null},{"url":null,"slug":"secure-joint-communication-and-sensing","title":"Secure Joint Communication and Sensing","date":"2022-02-22","arxiv_id":"2202.10790","repositories_listed":0,"syntology":null},{"url":null,"slug":"why-fair-labels-can-yield-unfair-predictions","title":"Why Fair Labels Can Yield Unfair Predictions: Graphical Conditions for Introduced Unfairness","date":"2022-02-22","arxiv_id":"2202.10816","repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-based-extractive-explainer-for","title":"Graph-based Extractive Explainer for Recommendations","date":"2022-02-20","arxiv_id":"2202.09730","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-3d-index-for-measuring-economic-resilience","title":"A 3D index for measuring economic resilience with application to the modern international and global financial crises","date":"2022-02-17","arxiv_id":"2202.08564","repositories_listed":0,"syntology":null},{"url":null,"slug":"contextualize-differential-privacy-in-image","title":"Contextualize differential privacy in image database: a lightweight image differential privacy approach based on principle component analysis inverse","date":"2022-02-16","arxiv_id":"2202.08309","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-class-granular-approximation-by-means","title":"Multi-class granular approximation by means of disjoint and adjacent fuzzy granules","date":"2022-02-15","arxiv_id":"2202.07584","repositories_listed":0,"syntology":null},{"url":null,"slug":"forecasting-large-scale-circulation-regimes","title":"Forecasting large-scale circulation regimes using deformable convolutional neural networks and global spatiotemporal climate data","date":"2022-02-10","arxiv_id":"2202.04964","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-novel-ontology-guided-attribute","title":"A Novel Ontology-guided Attribute Partitioning Ensemble Learning Model for Early Prediction of Cognitive Deficits using Quantitative Structural MRI in Very Preterm Infants","date":"2022-02-08","arxiv_id":"2202.04134","repositories_listed":0,"syntology":null},{"url":null,"slug":"counterfactual-multi-token-fairness-in-text","title":"Counterfactual Multi-Token Fairness in Text Classification","date":"2022-02-08","arxiv_id":"2202.03792","repositories_listed":0,"syntology":null},{"url":null,"slug":"dikaios-privacy-auditing-of-algorithmic","title":"Dikaios: Privacy Auditing of Algorithmic Fairness via Attribute Inference Attacks","date":"2022-02-04","arxiv_id":"2202.02242","repositories_listed":0,"syntology":null},{"url":null,"slug":"offline-reinforcement-learning-for-mobile","title":"Offline Reinforcement Learning for Mobile Notifications","date":"2022-02-04","arxiv_id":"2202.03867","repositories_listed":0,"syntology":null},{"url":null,"slug":"network-resource-allocation-strategy-based-on","title":"Network Resource Allocation Strategy Based on Deep Reinforcement Learning","date":"2022-02-03","arxiv_id":"2202.03193","repositories_listed":0,"syntology":null},{"url":null,"slug":"gradient-estimators-for-normalising-flows","title":"Gradient estimators for normalising flows","date":"2022-02-02","arxiv_id":"2202.01314","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-order-networks-for-action-unit","title":"Multi-Order Networks for Action Unit Detection","date":"2022-02-01","arxiv_id":"2202.00446","repositories_listed":0,"syntology":null},{"url":null,"slug":"constrained-density-matching-and-modeling-for-1","title":"Constrained Density Matching and Modeling for Cross-lingual Alignment of Contextualized Representations","date":"2022-01-31","arxiv_id":"2201.13429","repositories_listed":0,"syntology":null},{"url":null,"slug":"sparse-centroid-encoder-a-nonlinear-model-for","title":"Sparse Centroid-Encoder: A Nonlinear Model for Feature Selection","date":"2022-01-30","arxiv_id":"2201.12910","repositories_listed":0,"syntology":null}],"record_sha256":"e9d8aecb3094c67448b37fdac98cb0e73d665e1e5d2638a21e94c3bab1e0e88d","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}