{"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/survey/papers/7","list_of":"/task/survey","task":"Survey","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":7,"pages_in_order":41,"rows_per_page":100,"rows":[601,700],"of":4084,"counts":{"archive_papers_tagged":4084,"with_a_code_link":877,"where_syntology_ran_a_sample":71,"not_listed_spam_title":0,"listed":4084,"listed_where_code_ran":71,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":61,"every_run_a_failure_of_syntologys_instrument":10,"listed_with_a_run_with_no_instrument_failure":61,"listed_every_run_a_failure_of_syntologys_instrument":10,"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/survey","prev":"/task/survey/papers/6","next":"/task/survey/papers/8","papers":[{"url":"/paper/towards-reasoning-in-large-language-models-a","slug":"towards-reasoning-in-large-language-models-a","title":"Towards Reasoning in Large Language Models: A Survey","date":"2022-12-20","arxiv_id":"2212.10403","repositories_listed":1,"syntology":null},{"url":"/paper/a-large-scale-and-pcr-referenced-vocal-audio","slug":"a-large-scale-and-pcr-referenced-vocal-audio","title":"A large-scale and PCR-referenced vocal audio dataset for COVID-19","date":"2022-12-15","arxiv_id":"2212.07738","repositories_listed":1,"syntology":null},{"url":"/paper/instrumental-variables-in-causal-inference","slug":"instrumental-variables-in-causal-inference","title":"Instrumental Variables in Causal Inference and Machine Learning: A Survey","date":"2022-12-12","arxiv_id":"2212.05778","repositories_listed":1,"syntology":null},{"url":"/paper/reasoning-over-different-types-of-knowledge","slug":"reasoning-over-different-types-of-knowledge","title":"A Survey of Knowledge Graph Reasoning on Graph Types: Static, Dynamic, and Multimodal","date":"2022-12-12","arxiv_id":"2212.05767","repositories_listed":1,"syntology":null},{"url":"/paper/training-data-influence-analysis-and","slug":"training-data-influence-analysis-and","title":"Training Data Influence Analysis and Estimation: A Survey","date":"2022-12-09","arxiv_id":"2212.04612","repositories_listed":1,"syntology":null},{"url":"/paper/a-survey-of-graph-neural-networks-for-social","slug":"a-survey-of-graph-neural-networks-for-social","title":"A Survey of Graph Neural Networks for Social Recommender Systems","date":"2022-12-08","arxiv_id":"2212.04481","repositories_listed":1,"syntology":null},{"url":"/paper/leveraging-structure-for-improved","slug":"leveraging-structure-for-improved","title":"Leveraging Structure for Improved Classification of Grouped Biased Data","date":"2022-12-07","arxiv_id":"2212.03697","repositories_listed":1,"syntology":null},{"url":"/paper/fingerprint-pore-detection-a-survey","slug":"fingerprint-pore-detection-a-survey","title":"Fingerprint Pore Detection: A Survey","date":"2022-11-27","arxiv_id":"2211.14716","repositories_listed":1,"syntology":null},{"url":"/paper/continual-learning-of-natural-language","slug":"continual-learning-of-natural-language","title":"Continual Learning of Natural Language Processing Tasks: A Survey","date":"2022-11-23","arxiv_id":"2211.12701","repositories_listed":1,"syntology":null},{"url":"/paper/interpretable-scientific-discovery-with","slug":"interpretable-scientific-discovery-with","title":"Interpretable Scientific Discovery with Symbolic Regression: A Review","date":"2022-11-20","arxiv_id":"2211.10873","repositories_listed":1,"syntology":null},{"url":"/paper/video-unsupervised-domain-adaptation-with","slug":"video-unsupervised-domain-adaptation-with","title":"Video Unsupervised Domain Adaptation with Deep Learning: A Comprehensive Survey","date":"2022-11-17","arxiv_id":"2211.10412","repositories_listed":1,"syntology":null},{"url":"/paper/deep-emotion-recognition-in-textual","slug":"deep-emotion-recognition-in-textual","title":"Deep Emotion Recognition in Textual Conversations: A Survey","date":"2022-11-16","arxiv_id":"2211.09172","repositories_listed":1,"syntology":null},{"url":"/paper/photometric-identification-of-compact","slug":"photometric-identification-of-compact","title":"Photometric identification of compact galaxies, stars and quasars using multiple neural networks","date":"2022-11-15","arxiv_id":"2211.08388","repositories_listed":1,"syntology":null},{"url":"/paper/diffusion-models-for-medical-image-analysis-a","slug":"diffusion-models-for-medical-image-analysis-a","title":"Diffusion Models for Medical Image Analysis: A Comprehensive Survey","date":"2022-11-14","arxiv_id":"2211.07804","repositories_listed":1,"syntology":null},{"url":"/paper/methods-for-recovering-conditional","slug":"methods-for-recovering-conditional","title":"Methods for Recovering Conditional Independence Graphs: A Survey","date":"2022-11-13","arxiv_id":"2211.06829","repositories_listed":1,"syntology":null},{"url":"/paper/a-survey-on-explainable-reinforcement","slug":"a-survey-on-explainable-reinforcement","title":"A Survey on Explainable Reinforcement Learning: Concepts, Algorithms, Challenges","date":"2022-11-12","arxiv_id":"2211.06665","repositories_listed":1,"syntology":null},{"url":"/paper/deep-generative-models-on-3d-representations","slug":"deep-generative-models-on-3d-representations","title":"Deep Generative Models on 3D Representations: A Survey","date":"2022-10-27","arxiv_id":"2210.15663","repositories_listed":1,"syntology":null},{"url":"/paper/a-survey-on-3d-aware-image-synthesis","slug":"a-survey-on-3d-aware-image-synthesis","title":"A Survey on Deep Generative 3D-aware Image Synthesis","date":"2022-10-25","arxiv_id":"2210.14267","repositories_listed":1,"syntology":null},{"url":"/paper/a-survey-of-active-learning-for-natural","slug":"a-survey-of-active-learning-for-natural","title":"A Survey of Active Learning for Natural Language Processing","date":"2022-10-18","arxiv_id":"2210.10109","repositories_listed":1,"syntology":null},{"url":"/paper/attribute-inference-attacks-in-online","slug":"attribute-inference-attacks-in-online","title":"Attribute Inference Attacks in Online Multiplayer Video Games: a Case Study on Dota2","date":"2022-10-17","arxiv_id":"2210.09028","repositories_listed":1,"syntology":null},{"url":"/paper/3d-brain-and-heart-volume-generative-models-a","slug":"3d-brain-and-heart-volume-generative-models-a","title":"3D Brain and Heart Volume Generative Models: A Survey","date":"2022-10-12","arxiv_id":"2210.05952","repositories_listed":1,"syntology":null},{"url":"/paper/a-comprehensive-survey-of-data-augmentation","slug":"a-comprehensive-survey-of-data-augmentation","title":"A Comprehensive Survey of Data Augmentation in Visual Reinforcement Learning","date":"2022-10-10","arxiv_id":"2210.04561","repositories_listed":1,"syntology":null},{"url":"/paper/clad-a-realistic-continual-learning-benchmark","slug":"clad-a-realistic-continual-learning-benchmark","title":"CLAD: A realistic Continual Learning benchmark for Autonomous Driving","date":"2022-10-07","arxiv_id":"2210.03482","repositories_listed":1,"syntology":null},{"url":"/paper/physical-adversarial-attack-meets-computer","slug":"physical-adversarial-attack-meets-computer","title":"Physical Adversarial Attack meets Computer Vision: A Decade Survey","date":"2022-09-30","arxiv_id":"2209.15179","repositories_listed":1,"syntology":null},{"url":"/paper/a-survey-of-deep-causal-model","slug":"a-survey-of-deep-causal-model","title":"A Survey of Deep Causal Models and Their Industrial Applications","date":"2022-09-19","arxiv_id":"2209.08860","repositories_listed":1,"syntology":null},{"url":"/paper/communitylm-probing-partisan-worldviews-from","slug":"communitylm-probing-partisan-worldviews-from","title":"CommunityLM: Probing Partisan Worldviews from Language Models","date":"2022-09-15","arxiv_id":"2209.07065","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/communitylm-probing-partisan-worldviews-from#ran","syntology_url":"https://syntology.ai/paper/2209.07065","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2209.07065"}},"official":{"repos":["hjian42/communitylm"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/diffusion-models-in-vision-a-survey","slug":"diffusion-models-in-vision-a-survey","title":"Diffusion Models in Vision: A Survey","date":"2022-09-10","arxiv_id":"2209.04747","repositories_listed":1,"syntology":null},{"url":"/paper/general-place-recognition-survey-towards-the","slug":"general-place-recognition-survey-towards-the","title":"General Place Recognition Survey: Towards the Real-world Autonomy Age","date":"2022-09-09","arxiv_id":"2209.04497","repositories_listed":1,"syntology":null},{"url":"/paper/a-survey-of-neural-trees","slug":"a-survey-of-neural-trees","title":"A Survey of Neural Trees","date":"2022-09-07","arxiv_id":"2209.03415","repositories_listed":1,"syntology":null},{"url":"/paper/a-survey-of-machine-unlearning","slug":"a-survey-of-machine-unlearning","title":"A Survey of Machine Unlearning","date":"2022-09-06","arxiv_id":"2209.02299","repositories_listed":1,"syntology":null},{"url":"/paper/a-survey-on-generative-diffusion-model","slug":"a-survey-on-generative-diffusion-model","title":"A Survey on Generative Diffusion Model","date":"2022-09-06","arxiv_id":"2209.02646","repositories_listed":1,"syntology":null},{"url":"/paper/the-neural-process-family-survey-applications","slug":"the-neural-process-family-survey-applications","title":"The Neural Process Family: Survey, Applications and Perspectives","date":"2022-09-01","arxiv_id":"2209.00517","repositories_listed":1,"syntology":null},{"url":"/paper/causal-inference-in-recommender-systems-a","slug":"causal-inference-in-recommender-systems-a","title":"Causal Inference in Recommender Systems: A Survey and Future Directions","date":"2022-08-26","arxiv_id":"2208.12397","repositories_listed":1,"syntology":null},{"url":"/paper/on-the-implicit-bias-in-deep-learning","slug":"on-the-implicit-bias-in-deep-learning","title":"On the Implicit Bias in Deep-Learning Algorithms","date":"2022-08-26","arxiv_id":"2208.12591","repositories_listed":1,"syntology":null},{"url":"/paper/recent-advances-in-text-to-sql-a-survey-of","slug":"recent-advances-in-text-to-sql-a-survey-of","title":"Recent Advances in Text-to-SQL: A Survey of What We Have and What We Expect","date":"2022-08-22","arxiv_id":"2208.10099","repositories_listed":1,"syntology":null},{"url":"/paper/survey-of-machine-learning-techniques-to","slug":"survey-of-machine-learning-techniques-to","title":"Survey of Machine Learning Techniques To Predict Heartbeat Arrhythmias","date":"2022-08-22","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/survey-of-machine-learning-techniques-to-1","slug":"survey-of-machine-learning-techniques-to-1","title":"Survey of Machine Learning Techniques To Predict Heartbeat Arrhythmias","date":"2022-08-22","arxiv_id":"2208.10463","repositories_listed":1,"syntology":null},{"url":"/paper/a-survey-on-incomplete-multi-view-clustering","slug":"a-survey-on-incomplete-multi-view-clustering","title":"A Survey on Incomplete Multi-view Clustering","date":"2022-08-17","arxiv_id":"2208.08040","repositories_listed":1,"syntology":null},{"url":"/paper/3d-vision-with-transformers-a-survey","slug":"3d-vision-with-transformers-a-survey","title":"3D Vision with Transformers: A Survey","date":"2022-08-08","arxiv_id":"2208.04309","repositories_listed":1,"syntology":null},{"url":"/paper/vision-centric-bev-perception-a-survey","slug":"vision-centric-bev-perception-a-survey","title":"Vision-Centric BEV Perception: A Survey","date":"2022-08-04","arxiv_id":"2208.02797","repositories_listed":1,"syntology":null},{"url":"/paper/a-survey-of-syntactic-modelling-structures-in","slug":"a-survey-of-syntactic-modelling-structures-in","title":"A Survey of Syntactic Modelling Structures in Biomedical Ontologies","date":"2022-07-28","arxiv_id":"2207.14119","repositories_listed":1,"syntology":null},{"url":"/paper/real-time-object-detection-system-with-yolo","slug":"real-time-object-detection-system-with-yolo","title":"Real Time Object Detection System with YOLO and CNN Models: A Review","date":"2022-07-23","arxiv_id":"2208.00773","repositories_listed":1,"syntology":null},{"url":"/paper/computer-vision-to-the-rescue-infant-postural","slug":"computer-vision-to-the-rescue-infant-postural","title":"Computer Vision to the Rescue: Infant Postural Symmetry Estimation from Incongruent Annotations","date":"2022-07-19","arxiv_id":"2207.09352","repositories_listed":1,"syntology":null},{"url":"/paper/deep-learning-for-anomaly-detection-in-log","slug":"deep-learning-for-anomaly-detection-in-log","title":"Deep Learning for Anomaly Detection in Log Data: A Survey","date":"2022-07-08","arxiv_id":"2207.03820","repositories_listed":1,"syntology":null},{"url":"/paper/facke-a-survey-on-generative-models-for-face","slug":"facke-a-survey-on-generative-models-for-face","title":"Facke: a Survey on Generative Models for Face Swapping","date":"2022-06-22","arxiv_id":"2206.11203","repositories_listed":1,"syntology":null},{"url":"/paper/3d-object-detection-for-autonomous-driving-a-1","slug":"3d-object-detection-for-autonomous-driving-a-1","title":"3D Object Detection for Autonomous Driving: A Comprehensive Survey","date":"2022-06-19","arxiv_id":"2206.09474","repositories_listed":1,"syntology":null},{"url":"/paper/self-supervised-learning-for-videos-a-survey","slug":"self-supervised-learning-for-videos-a-survey","title":"Self-Supervised Learning for Videos: A Survey","date":"2022-06-18","arxiv_id":"2207.00419","repositories_listed":1,"syntology":null},{"url":"/paper/a-comprehensive-survey-on-deep-clustering","slug":"a-comprehensive-survey-on-deep-clustering","title":"A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions","date":"2022-06-15","arxiv_id":"2206.07579","repositories_listed":1,"syntology":null},{"url":"/paper/all-one-needs-to-know-about-priors-for-deep","slug":"all-one-needs-to-know-about-priors-for-deep","title":"Priors in Deep Image Restoration and Enhancement: A Survey","date":"2022-06-04","arxiv_id":"2206.02070","repositories_listed":1,"syntology":null},{"url":"/paper/a-survey-on-deep-learning-for-skin-lesion","slug":"a-survey-on-deep-learning-for-skin-lesion","title":"A Survey on Deep Learning for Skin Lesion Segmentation","date":"2022-06-01","arxiv_id":"2206.00356","repositories_listed":1,"syntology":null},{"url":"/paper/multimodality-for-nlp-centered-applications","slug":"multimodality-for-nlp-centered-applications","title":"Multimodality for NLP-Centered Applications: Resources, Advances and Frontiers","date":"2022-06-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/explainable-deep-learning-methods-in-medical","slug":"explainable-deep-learning-methods-in-medical","title":"Explainable Deep Learning Methods in Medical Image Classification: A Survey","date":"2022-05-10","arxiv_id":"2205.04766","repositories_listed":1,"syntology":null},{"url":"/paper/affective-medical-estimation-and-decision","slug":"affective-medical-estimation-and-decision","title":"Affective Medical Estimation and Decision Making via Visualized Learning and Deep Learning","date":"2022-05-09","arxiv_id":"2205.04599","repositories_listed":1,"syntology":null},{"url":"/paper/detecting-and-understanding-harmful-memes-a","slug":"detecting-and-understanding-harmful-memes-a","title":"Detecting and Understanding Harmful Memes: A Survey","date":"2022-05-09","arxiv_id":"2205.04274","repositories_listed":1,"syntology":null},{"url":"/paper/a-survey-on-sentence-embedding-models","slug":"a-survey-on-sentence-embedding-models","title":"A Survey on Sentence Embedding Models Performance for Patent Analysis","date":"2022-04-28","arxiv_id":"2206.02690","repositories_listed":1,"syntology":null},{"url":"/paper/computer-vision-for-road-imaging-and-pothole","slug":"computer-vision-for-road-imaging-and-pothole","title":"Computer Vision for Road Imaging and Pothole Detection: A State-of-the-Art Review of Systems and Algorithms","date":"2022-04-28","arxiv_id":"2204.13590","repositories_listed":1,"syntology":null},{"url":"/paper/a-survey-on-non-autoregressive-generation-for","slug":"a-survey-on-non-autoregressive-generation-for","title":"A Survey on Non-Autoregressive Generation for Neural Machine Translation and Beyond","date":"2022-04-20","arxiv_id":"2204.09269","repositories_listed":1,"syntology":null},{"url":"/paper/survey-of-aspect-based-sentiment-analysis","slug":"survey-of-aspect-based-sentiment-analysis","title":"Survey of Aspect-based Sentiment Analysis Datasets","date":"2022-04-11","arxiv_id":"2204.05232","repositories_listed":1,"syntology":null},{"url":"/paper/learning-based-approaches-for-graph-problems","slug":"learning-based-approaches-for-graph-problems","title":"A Survey on Machine Learning Solutions for Graph Pattern Extraction","date":"2022-04-03","arxiv_id":"2204.01057","repositories_listed":1,"syntology":null},{"url":"/paper/graph-neural-networks-in-iot-a-survey","slug":"graph-neural-networks-in-iot-a-survey","title":"Graph Neural Networks in IoT: A Survey","date":"2022-03-29","arxiv_id":"2203.15935","repositories_listed":1,"syntology":null},{"url":"/paper/self-supervised-learning-for-recommender","slug":"self-supervised-learning-for-recommender","title":"Self-Supervised Learning for Recommender Systems: A Survey","date":"2022-03-29","arxiv_id":"2203.15876","repositories_listed":1,"syntology":null},{"url":"/paper/a-comparative-survey-of-deep-active-learning","slug":"a-comparative-survey-of-deep-active-learning","title":"A Comparative Survey of Deep Active Learning","date":"2022-03-25","arxiv_id":"2203.13450","repositories_listed":1,"syntology":{"n":7,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/a-comparative-survey-of-deep-active-learning#ran","syntology_url":"https://syntology.ai/paper/2203.13450","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.13450"}},"official":{"repos":["SineZHAN/deepALplus"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/recovering-3d-human-mesh-from-monocular","slug":"recovering-3d-human-mesh-from-monocular","title":"Recovering 3D Human Mesh from Monocular Images: A Survey","date":"2022-03-03","arxiv_id":"2203.01923","repositories_listed":1,"syntology":null},{"url":"/paper/evaluating-the-construct-validity-of-text","slug":"evaluating-the-construct-validity-of-text","title":"Evaluating the Construct Validity of Text Embeddings with Application to Survey Questions","date":"2022-02-18","arxiv_id":"2202.09166","repositories_listed":1,"syntology":null},{"url":"/paper/vlp-a-survey-on-vision-language-pre-training","slug":"vlp-a-survey-on-vision-language-pre-training","title":"VLP: A Survey on Vision-Language Pre-training","date":"2022-02-18","arxiv_id":"2202.09061","repositories_listed":1,"syntology":null},{"url":"/paper/graph-data-augmentation-for-graph-machine","slug":"graph-data-augmentation-for-graph-machine","title":"Graph Data Augmentation for Graph Machine Learning: A Survey","date":"2022-02-17","arxiv_id":"2202.08871","repositories_listed":1,"syntology":null},{"url":"/paper/data-augmentation-for-deep-graph-learning-a","slug":"data-augmentation-for-deep-graph-learning-a","title":"Data Augmentation for Deep Graph Learning: A Survey","date":"2022-02-16","arxiv_id":"2202.08235","repositories_listed":1,"syntology":null},{"url":"/paper/learning-transferrable-representations-of","slug":"learning-transferrable-representations-of","title":"CAREER: A Foundation Model for Labor Sequence Data","date":"2022-02-16","arxiv_id":"2202.08370","repositories_listed":1,"syntology":null},{"url":"/paper/out-of-distribution-generalization-on-graphs","slug":"out-of-distribution-generalization-on-graphs","title":"Out-Of-Distribution Generalization on Graphs: A Survey","date":"2022-02-16","arxiv_id":"2202.07987","repositories_listed":1,"syntology":null},{"url":"/paper/a-survey-of-visual-sensory-anomaly-detection","slug":"a-survey-of-visual-sensory-anomaly-detection","title":"A Survey of Visual Sensory Anomaly Detection","date":"2022-02-14","arxiv_id":"2202.07006","repositories_listed":1,"syntology":null},{"url":"/paper/a-survey-on-programmatic-weak-supervision","slug":"a-survey-on-programmatic-weak-supervision","title":"A Survey on Programmatic Weak Supervision","date":"2022-02-11","arxiv_id":"2202.05433","repositories_listed":1,"syntology":null},{"url":"/paper/3d-object-detection-from-images-for","slug":"3d-object-detection-from-images-for","title":"3D Object Detection from Images for Autonomous Driving: A Survey","date":"2022-02-07","arxiv_id":"2202.02980","repositories_listed":1,"syntology":null},{"url":"/paper/transformers-in-medical-imaging-a-survey","slug":"transformers-in-medical-imaging-a-survey","title":"Transformers in Medical Imaging: A Survey","date":"2022-01-24","arxiv_id":"2201.09873","repositories_listed":1,"syntology":null},{"url":"/paper/transferability-in-deep-learning-a-survey","slug":"transferability-in-deep-learning-a-survey","title":"Transferability in Deep Learning: A Survey","date":"2022-01-15","arxiv_id":"2201.05867","repositories_listed":1,"syntology":null},{"url":"/paper/what-is-event-knowledge-graph-a-survey","slug":"what-is-event-knowledge-graph-a-survey","title":"What is Event Knowledge Graph: A Survey","date":"2021-12-31","arxiv_id":"2112.15280","repositories_listed":1,"syntology":null},{"url":"/paper/is-count-large-scale-object-counting-from","slug":"is-count-large-scale-object-counting-from","title":"IS-COUNT: Large-scale Object Counting from Satellite Images with Covariate-based Importance Sampling","date":"2021-12-16","arxiv_id":"2112.09126","repositories_listed":1,"syntology":null},{"url":"/paper/measuring-fairness-with-biased-rulers-a","slug":"measuring-fairness-with-biased-rulers-a","title":"Measuring Fairness with Biased Rulers: A Survey on Quantifying Biases in Pretrained Language Models","date":"2021-12-14","arxiv_id":"2112.07447","repositories_listed":1,"syntology":null},{"url":"/paper/survey-on-english-entity-linking-on-wikidata","slug":"survey-on-english-entity-linking-on-wikidata","title":"Survey on English Entity Linking on Wikidata","date":"2021-12-03","arxiv_id":"2112.01989","repositories_listed":1,"syntology":null},{"url":"/paper/neural-image-beauty-predictor-based-on","slug":"neural-image-beauty-predictor-based-on","title":"Neural Image Beauty Predictor Based on Bradley-Terry Model","date":"2021-11-19","arxiv_id":"2111.10127","repositories_listed":1,"syntology":null},{"url":"/paper/attention-mechanisms-in-computer-vision-a","slug":"attention-mechanisms-in-computer-vision-a","title":"Attention Mechanisms in Computer Vision: A Survey","date":"2021-11-15","arxiv_id":"2111.07624","repositories_listed":1,"syntology":null},{"url":"/paper/a-survey-of-visual-transformers","slug":"a-survey-of-visual-transformers","title":"A Survey of Visual Transformers","date":"2021-11-11","arxiv_id":"2111.06091","repositories_listed":1,"syntology":null},{"url":"/paper/edge-cloud-polarization-and-collaboration-a","slug":"edge-cloud-polarization-and-collaboration-a","title":"Edge-Cloud Polarization and Collaboration: A Comprehensive Survey for AI","date":"2021-11-11","arxiv_id":"2111.06061","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":1,"n_honours":2,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/edge-cloud-polarization-and-collaboration-a#ran","syntology_url":"https://syntology.ai/paper/2111.06061","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.06061"}},"official":{"repos":["luoxi-model/luoxi_models"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/an-open-source-web-app-for-creating-and","slug":"an-open-source-web-app-for-creating-and","title":"An Open-Source Web App for Creating and Scoring Qualtrics-based Implicit Association Test","date":"2021-11-03","arxiv_id":"2111.02267","repositories_listed":1,"syntology":null},{"url":"/paper/constructing-a-psychometric-testbed-for-fair","slug":"constructing-a-psychometric-testbed-for-fair","title":"Constructing a Psychometric Testbed for Fair Natural Language Processing","date":"2021-11-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/a-survey-of-self-supervised-and-few-shot","slug":"a-survey-of-self-supervised-and-few-shot","title":"A Survey of Self-Supervised and Few-Shot Object Detection","date":"2021-10-27","arxiv_id":"2110.14711","repositories_listed":1,"syntology":null},{"url":"/paper/a-unified-survey-on-anomaly-novelty-open-set","slug":"a-unified-survey-on-anomaly-novelty-open-set","title":"A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future Challenges","date":"2021-10-26","arxiv_id":"2110.14051","repositories_listed":1,"syntology":null},{"url":"/paper/joint-gaussian-graphical-model-estimation-a","slug":"joint-gaussian-graphical-model-estimation-a","title":"Joint Gaussian Graphical Model Estimation: A Survey","date":"2021-10-19","arxiv_id":"2110.10281","repositories_listed":1,"syntology":null},{"url":"/paper/tell-me-how-to-survey-literature-review-made","slug":"tell-me-how-to-survey-literature-review-made","title":"Tell Me How to Survey: Literature Review Made Simple with Automatic Reading Path Generation","date":"2021-10-12","arxiv_id":"2110.06354","repositories_listed":1,"syntology":null},{"url":"/paper/pre-trained-language-models-in-biomedical","slug":"pre-trained-language-models-in-biomedical","title":"Pre-trained Language Models in Biomedical Domain: A Systematic Survey","date":"2021-10-11","arxiv_id":"2110.05006","repositories_listed":1,"syntology":null},{"url":"/paper/deep-long-tailed-learning-a-survey","slug":"deep-long-tailed-learning-a-survey","title":"Deep Long-Tailed Learning: A Survey","date":"2021-10-09","arxiv_id":"2110.04596","repositories_listed":1,"syntology":null},{"url":"/paper/data-augmentation-approaches-in-natural","slug":"data-augmentation-approaches-in-natural","title":"Data Augmentation Approaches in Natural Language Processing: A Survey","date":"2021-10-05","arxiv_id":"2110.01852","repositories_listed":1,"syntology":null},{"url":"/paper/optimization-with-constraint-learning-a","slug":"optimization-with-constraint-learning-a","title":"Optimization with Constraint Learning: A Framework and Survey","date":"2021-10-05","arxiv_id":"2110.02121","repositories_listed":1,"syntology":null},{"url":"/paper/a-survey-on-datasets-for-fairness-aware","slug":"a-survey-on-datasets-for-fairness-aware","title":"A survey on datasets for fairness-aware machine learning","date":"2021-10-01","arxiv_id":"2110.00530","repositories_listed":1,"syntology":null},{"url":"/paper/a-comprehensive-survey-and-performance","slug":"a-comprehensive-survey-and-performance","title":"Activation Functions in Deep Learning: A Comprehensive Survey and Benchmark","date":"2021-09-29","arxiv_id":"2109.14545","repositories_listed":1,"syntology":null},{"url":"/paper/from-beginner-to-master-a-survey-for-deep","slug":"from-beginner-to-master-a-survey-for-deep","title":"A Systematic Survey of Deep Learning-based Single-Image Super-Resolution","date":"2021-09-29","arxiv_id":"2109.14335","repositories_listed":1,"syntology":null},{"url":"/paper/named-entity-recognition-and-classification","slug":"named-entity-recognition-and-classification","title":"Named Entity Recognition and Classification on Historical Documents: A Survey","date":"2021-09-23","arxiv_id":"2109.11406","repositories_listed":1,"syntology":null},{"url":"/paper/ai-accelerator-survey-and-trends","slug":"ai-accelerator-survey-and-trends","title":"AI Accelerator Survey and Trends","date":"2021-09-18","arxiv_id":"2109.08957","repositories_listed":1,"syntology":null},{"url":"/paper/a-survey-on-automated-fact-checking","slug":"a-survey-on-automated-fact-checking","title":"A Survey on Automated Fact-Checking","date":"2021-08-26","arxiv_id":"2108.11896","repositories_listed":1,"syntology":null},{"url":"/paper/predicting-census-survey-response-rates-via","slug":"predicting-census-survey-response-rates-via","title":"Predicting Census Survey Response Rates With Parsimonious Additive Models and Structured Interactions","date":"2021-08-24","arxiv_id":"2108.11328","repositories_listed":1,"syntology":null},{"url":"/paper/complex-knowledge-base-question-answering-a","slug":"complex-knowledge-base-question-answering-a","title":"Complex Knowledge Base Question Answering: A Survey","date":"2021-08-15","arxiv_id":"2108.06688","repositories_listed":1,"syntology":null}],"record_sha256":"bf43530655dc2d401e4e5aeb77e13de0036307a955136628d99c9f0cb7cdfc79","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}