{"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":"/method/aware/papers/19","list_of":"/method/aware","method":"AWARE","archive":{"snapshot":"2025-07-28"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"date (newest first), then slug","page":19,"pages_in_order":19,"rows_per_page":100,"rows":[1801,1883],"of":1883,"counts":{"archive_papers_tagged":1883,"with_a_code_link":618,"where_syntology_ran_a_sample":145,"not_listed_spam_title":0,"listed":1883,"listed_where_code_ran":145,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":121,"every_run_a_failure_of_syntologys_instrument":24,"listed_with_a_run_with_no_instrument_failure":121,"listed_every_run_a_failure_of_syntologys_instrument":24,"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":"/method/aware","prev":"/method/aware/papers/18","next":null,"papers":[{"paper":null,"slug":"temporal-spatial-adaptive-interpolation-with","title":"Temporal Spatial-Adaptive Interpolation with Deformable Refinement for Electron Microscopic Images","date":"2021-01-17","arxiv_id":"2101.06771","n_code_links":0,"syntology":null},{"paper":null,"slug":"semi-supervised-deep-quick-instance-detection","title":"Semi Supervised Deep Quick Instance Detection and Segmentation","date":"2021-01-16","arxiv_id":"2101.06405","n_code_links":0,"syntology":null},{"paper":"/paper/controlling-the-risk-of-conversational-search","slug":"controlling-the-risk-of-conversational-search","title":"Controlling the Risk of Conversational Search via Reinforcement Learning","date":"2021-01-15","arxiv_id":"2101.06327","n_code_links":1,"syntology":null},{"paper":"/paper/a-har-a-new-benchmark-towards-semi-supervised","slug":"a-har-a-new-benchmark-towards-semi-supervised","title":"A*HAR: A New Benchmark towards Semi-supervised learning for Class-imbalanced Human Activity Recognition","date":"2021-01-13","arxiv_id":"2101.04859","n_code_links":1,"syntology":null},{"paper":null,"slug":"formalising-concepts-as-grounded-abstractions","title":"Formalising Concepts as Grounded Abstractions","date":"2021-01-13","arxiv_id":"2101.05125","n_code_links":0,"syntology":null},{"paper":null,"slug":"quantify-change-of-inertia-and-its","title":"Quantify Change of Inertia and Its Distribution in High Renewable Power Grids Using PMU","date":"2021-01-12","arxiv_id":"2101.04593","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-domain-invariant-single-image","title":"Towards Domain Invariant Single Image Dehazing","date":"2021-01-09","arxiv_id":"2101.10449","n_code_links":0,"syntology":null},{"paper":"/paper/scan-sequence-character-aware-network-for","slug":"scan-sequence-character-aware-network-for","title":"SCAN: Sequence-character Aware Network for Text Recognition","date":"2021-01-08","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"attitudes-toward-open-access-open-peer-review","title":"Attitudes toward Open Access, Open Peer Review, and Altmetrics among Contributors to Spanish Scholarly Journals","date":"2021-01-07","arxiv_id":"2101.02488","n_code_links":0,"syntology":null},{"paper":null,"slug":"adaptive-synthetic-characters-for-military","title":"Adaptive Synthetic Characters for Military Training","date":"2021-01-06","arxiv_id":"2101.02185","n_code_links":0,"syntology":null},{"paper":null,"slug":"political-depolarization-of-news-articles","title":"Political Depolarization of News Articles Using Attribute-aware Word Embeddings","date":"2021-01-05","arxiv_id":"2101.01391","n_code_links":0,"syntology":null},{"paper":null,"slug":"federated-learning-based-risk-aware-decision","title":"Federated Learning-Based Risk-Aware Decision toMitigate Fake Task Impacts on CrowdsensingPlatforms","date":"2021-01-04","arxiv_id":"2101.01266","n_code_links":0,"syntology":null},{"paper":null,"slug":"active-learning-for-lane-detection-a","title":"Active Learning for Lane Detection: A Knowledge Distillation Approach","date":"2021-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"amending-mistakes-post-hoc-in-deep-networks","title":"Amending Mistakes Post-hoc in Deep Networks by Leveraging Class Hierarchies","date":"2021-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"beyond-covid-19-diagnosis-prognosis-with","title":"Beyond COVID-19 Diagnosis: Prognosis with Hierarchical Graph Representation Learning","date":"2021-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"clothing-status-awareness-for-long-term","title":"Clothing Status Awareness for Long-Term Person Re-Identification","date":"2021-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"dense-global-context-aware-rcnn-for-object","title":"Dense Global Context Aware RCNN for Object Detection","date":"2021-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"feature-interactive-representation-for-point","title":"Feature Interactive Representation for Point Cloud Registration","date":"2021-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"geometric-deep-neural-network-using-rigid-and","title":"Geometric Deep Neural Network Using Rigid and Non-Rigid Transformations for Human Action Recognition","date":"2021-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"hybrid-and-non-uniform-dnn-quantization","title":"Hybrid and Non-Uniform DNN quantization methods using Retro Synthesis data for efficient inference","date":"2021-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/improving-neural-network-efficiency-via-post","slug":"improving-neural-network-efficiency-via-post","title":"Improving Neural Network Efficiency via Post-Training Quantization With Adaptive Floating-Point","date":"2021-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/k-plug-knowledge-injected-pre-trained","slug":"k-plug-knowledge-injected-pre-trained","title":"K-PLUG: KNOWLEDGE-INJECTED PRE-TRAINED LANGUAGE MODEL FOR NATURAL LANGUAGE UNDERSTANDING AND GENERATION","date":"2021-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"learning-without-forgetting-task-aware","title":"Learning without Forgetting: Task Aware Multitask Learning for Multi-Modality Tasks","date":"2021-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/light-source-guided-single-image-flare","slug":"light-source-guided-single-image-flare","title":"Light Source Guided Single-Image Flare Removal From Unpaired Data","date":"2021-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"motion-guided-region-message-passing-for","title":"Motion Guided Region Message Passing for Video Captioning","date":"2021-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/perceptual-variousness-motion-deblurring-with","slug":"perceptual-variousness-motion-deblurring-with","title":"Perceptual Variousness Motion Deblurring With Light Global Context Refinement","date":"2021-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"development-and-evaluation-of-a-3d-annotation","title":"Development and evaluation of a 3D annotation software for interactive COVID-19 lesion segmentation in chest CT","date":"2020-12-29","arxiv_id":"2012.14752","n_code_links":0,"syntology":null},{"paper":null,"slug":"hybrid-and-non-uniform-quantization-methods","title":"Hybrid and Non-Uniform quantization methods using retro synthesis data for efficient inference","date":"2020-12-26","arxiv_id":"2012.13716","n_code_links":0,"syntology":null},{"paper":null,"slug":"granet-global-relation-aware-attentional","title":"GraNet: Global Relation-aware Attentional Network for ALS Point Cloud Classification","date":"2020-12-24","arxiv_id":"2012.13466","n_code_links":0,"syntology":null},{"paper":null,"slug":"improving-the-certified-robustness-of-neural","title":"Improving the Certified Robustness of Neural Networks via Consistency Regularization","date":"2020-12-24","arxiv_id":"2012.13103","n_code_links":0,"syntology":null},{"paper":null,"slug":"fines-and-progressive-ideology-promote-social","title":"Social distancing in networks: A web-based interactive experiment","date":"2020-12-22","arxiv_id":"2012.12118","n_code_links":0,"syntology":null},{"paper":null,"slug":"generalized-relation-learning-with-semantic","title":"Generalized Relation Learning with Semantic Correlation Awareness for Link Prediction","date":"2020-12-22","arxiv_id":"2012.11957","n_code_links":0,"syntology":null},{"paper":null,"slug":"out-distribution-aware-self-training-in-an","title":"Out-distribution aware Self-training in an Open World Setting","date":"2020-12-21","arxiv_id":"2012.12372","n_code_links":0,"syntology":null},{"paper":"/paper/high-fidelity-neural-human-motion-transfer","slug":"high-fidelity-neural-human-motion-transfer","title":"High-Fidelity Neural Human Motion Transfer from Monocular Video","date":"2020-12-20","arxiv_id":"2012.10974","n_code_links":1,"syntology":null},{"paper":"/paper/consolidated-dataset-and-metrics-for-high","slug":"consolidated-dataset-and-metrics-for-high","title":"Consolidated Dataset and Metrics for High-Dynamic-Range Image Quality","date":"2020-12-19","arxiv_id":"2012.10758","n_code_links":0,"syntology":null},{"paper":"/paper/model-free-and-bayesian-ensembling-model","slug":"model-free-and-bayesian-ensembling-model","title":"Model-free and Bayesian Ensembling Model-based Deep Reinforcement Learning for Particle Accelerator Control Demonstrated on the FERMI FEL","date":"2020-12-17","arxiv_id":"2012.09737","n_code_links":1,"syntology":null},{"paper":"/paper/research-reproducibility-as-a-survival","slug":"research-reproducibility-as-a-survival","title":"Research Reproducibility as a Survival Analysis","date":"2020-12-17","arxiv_id":"2012.09932","n_code_links":1,"syntology":null},{"paper":null,"slug":"interpretable-image-clustering-via","title":"Interpretable Image Clustering via Diffeomorphism-Aware K-Means","date":"2020-12-16","arxiv_id":"2012.09743","n_code_links":0,"syntology":null},{"paper":null,"slug":"query-free-black-box-adversarial-attacks-on","title":"Blindfolded Attackers Still Threatening: Strict Black-Box Adversarial Attacks on Graphs","date":"2020-12-12","arxiv_id":"2012.06757","n_code_links":0,"syntology":null},{"paper":null,"slug":"dependency-decomposition-and-a-reject-option","title":"Dependency Decomposition and a Reject Option for Explainable Models","date":"2020-12-11","arxiv_id":"2012.06523","n_code_links":0,"syntology":null},{"paper":null,"slug":"using-affective-aware-pseudo-association","title":"Making Cross-Domain Recommendations by Associating Disjoint Users and Items Through the Affective Aware Pseudo Association Method","date":"2020-12-10","arxiv_id":"2012.05982","n_code_links":0,"syntology":null},{"paper":null,"slug":"mo-ltr-multiple-object-localization-tracking","title":"MOLTR: Multiple Object Localisation, Tracking, and Reconstruction from Monocular RGB Videos","date":"2020-12-09","arxiv_id":"2012.05360","n_code_links":0,"syntology":null},{"paper":null,"slug":"setting-the-record-straighter-on-shadow","title":"Setting the Record Straighter on Shadow Banning","date":"2020-12-09","arxiv_id":"2012.05101","n_code_links":0,"syntology":null},{"paper":"/paper/scale-aware-adaptation-for-land-cover","slug":"scale-aware-adaptation-for-land-cover","title":"Scale Aware Adaptation for Land-Cover Classification in Remote Sensing Imagery","date":"2020-12-08","arxiv_id":"2012.04222","n_code_links":1,"syntology":null},{"paper":"/paper/stacmr-scene-text-aware-cross-modal-retrieval","slug":"stacmr-scene-text-aware-cross-modal-retrieval","title":"StacMR: Scene-Text Aware Cross-Modal Retrieval","date":"2020-12-08","arxiv_id":"2012.04329","n_code_links":1,"syntology":null},{"paper":null,"slug":"generating-unseen-complex-scenes-are-we-there-1","title":"Generating unseen complex scenes: are we there yet?","date":"2020-12-07","arxiv_id":"2012.04027","n_code_links":0,"syntology":null},{"paper":null,"slug":"privacy-and-robustness-in-federated-learning","title":"Privacy and Robustness in Federated Learning: Attacks and Defenses","date":"2020-12-07","arxiv_id":"2012.06337","n_code_links":0,"syntology":null},{"paper":"/paper/katrec-knowledge-aware-attentive-sequential","slug":"katrec-knowledge-aware-attentive-sequential","title":"KATRec: Knowledge Aware aTtentive Sequential Recommendations","date":"2020-12-06","arxiv_id":"2012.03323","n_code_links":1,"syntology":null},{"paper":null,"slug":"quality-of-transmission-estimation-in","title":"Quality-of-Transmission Estimation in Physical Impairment Aware Flexible Optical Networks","date":"2020-12-06","arxiv_id":"2012.06477","n_code_links":0,"syntology":null},{"paper":null,"slug":"visual-aware-hierarchy-based-food-recognition","title":"Visual Aware Hierarchy Based Food Recognition","date":"2020-12-06","arxiv_id":"2012.03368","n_code_links":0,"syntology":null},{"paper":null,"slug":"global-context-aware-rcnn-for-object","title":"Global Context Aware RCNN for Object Detection","date":"2020-12-04","arxiv_id":"2012.02637","n_code_links":0,"syntology":null},{"paper":"/paper/attributes-aware-face-generation-with","slug":"attributes-aware-face-generation-with","title":"Attributes Aware Face Generation with Generative Adversarial Networks","date":"2020-12-03","arxiv_id":"2012.01782","n_code_links":1,"syntology":null},{"paper":null,"slug":"predicting-misinformation-and-engagement-in","title":"People Still Care About Facts: Twitter Users Engage More with Factual Discourse than Misinformation--A Comparison Between COVID and General Narratives on Twitter","date":"2020-12-03","arxiv_id":"2012.02164","n_code_links":0,"syntology":null},{"paper":"/paper/saying-no-is-an-art-contextualized-fallback","slug":"saying-no-is-an-art-contextualized-fallback","title":"Saying No is An Art: Contextualized Fallback Responses for Unanswerable Dialogue Queries","date":"2020-12-03","arxiv_id":"2012.01873","n_code_links":1,"syntology":null},{"paper":null,"slug":"adversarial-bandits-with-corruptions-regret","title":"Adversarial Bandits with Corruptions: Regret Lower Bound and No-regret Algorithm","date":"2020-12-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/classifier-probes-may-just-learn-from-linear","slug":"classifier-probes-may-just-learn-from-linear","title":"Classifier Probes May Just Learn from Linear Context Features","date":"2020-12-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/jointly-learning-aspect-focused-and-inter","slug":"jointly-learning-aspect-focused-and-inter","title":"Jointly Learning Aspect-Focused and Inter-Aspect Relations with Graph Convolutional Networks for Aspect Sentiment Analysis","date":"2020-12-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"knowledge-aware-emotion-recognition-in","title":"Knowledge Aware Emotion Recognition in Textual Conversations via Multi-Task Incremental Transformer","date":"2020-12-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/retrieving-skills-from-job-descriptions-a","slug":"retrieving-skills-from-job-descriptions-a","title":"Retrieving Skills from Job Descriptions: A Language Model Based Extreme Multi-label Classification Framework","date":"2020-12-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"sasake-syntax-and-semantics-aware-keyphrase","title":"SaSAKE: Syntax and Semantics Aware Keyphrase Extraction from Research Papers","date":"2020-12-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"schema-aware-semantic-reasoning-for","title":"Schema Aware Semantic Reasoning for Interpreting Natural Language Queries in Enterprise Settings","date":"2020-12-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/swafn-sentimental-words-aware-fusion-network","slug":"swafn-sentimental-words-aware-fusion-network","title":"SWAFN: Sentimental Words Aware Fusion Network for Multimodal Sentiment Analysis","date":"2020-12-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"task-allocation-for-asynchronous-mobile-edge","title":"Task Allocation for Asynchronous Mobile Edge Learning with Delay and Energy Constraints","date":"2020-11-30","arxiv_id":"2012.00143","n_code_links":0,"syntology":null},{"paper":"/paper/a-targeted-universal-attack-on-graph","slug":"a-targeted-universal-attack-on-graph","title":"A Targeted Universal Attack on Graph Convolutional Network","date":"2020-11-29","arxiv_id":"2011.14365","n_code_links":1,"syntology":null},{"paper":null,"slug":"robust-correlation-tracking-via-multi-channel","title":"Robust Correlation Tracking via Multi-channel Fused Features and Reliable Response Map","date":"2020-11-25","arxiv_id":"2011.12550","n_code_links":0,"syntology":null},{"paper":null,"slug":"sensorimotor-representation-learning-for-an","title":"Sensorimotor representation learning for an \"active self\" in robots: A model survey","date":"2020-11-25","arxiv_id":"2011.12860","n_code_links":0,"syntology":null},{"paper":null,"slug":"kshapenet-riemannian-network-on-kendall-shape","title":"KShapeNet: Riemannian network on Kendall shape space for Skeleton based Action Recognition","date":"2020-11-24","arxiv_id":"2011.12004","n_code_links":0,"syntology":null},{"paper":"/paper/inverse-constrained-reinforcement-learning","slug":"inverse-constrained-reinforcement-learning","title":"Inverse Constrained Reinforcement Learning","date":"2020-11-19","arxiv_id":"2011.09999","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified; the one sample that ran constructed an object rather than computing a result","official":{"repos":["shehryar-malik/icrl"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"locally-aware-constrained-games-on-networks","title":"Locally-Aware Constrained Games on Networks","date":"2020-11-19","arxiv_id":"2011.10095","n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-modal-subjective-context-modelling-and","title":"Multi-Modal Subjective Context Modelling and Recognition","date":"2020-11-19","arxiv_id":"2011.09671","n_code_links":0,"syntology":null},{"paper":null,"slug":"cgap2-context-and-gap-aware-predictive-pose","title":"CGAP2: Context and gap aware predictive pose framework for early detection of gestures","date":"2020-11-18","arxiv_id":"2011.09216","n_code_links":0,"syntology":null},{"paper":null,"slug":"passgoodpool-joint-passengers-and-goods-fleet","title":"PassGoodPool: Joint Passengers and Goods Fleet Management with Reinforcement Learning aided Pricing, Matching, and Route Planning","date":"2020-11-17","arxiv_id":"2011.08999","n_code_links":0,"syntology":null},{"paper":null,"slug":"raist-learning-risk-aware-traffic","title":"RAIST: Learning Risk Aware Traffic Interactions via Spatio-Temporal Graph Convolutional Networks","date":"2020-11-17","arxiv_id":"2011.08722","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-spatial-variability-aware-deep-neural","title":"Towards Spatial Variability Aware Deep Neural Networks (SVANN): A Summary of Results","date":"2020-11-17","arxiv_id":"2011.08992","n_code_links":0,"syntology":null},{"paper":"/paper/samwalker-recommendation-with-informative","slug":"samwalker-recommendation-with-informative","title":"SamWalker++: recommendation with informative sampling strategy","date":"2020-11-16","arxiv_id":"2011.07734","n_code_links":1,"syntology":null},{"paper":null,"slug":"morphologically-aware-word-level-translation","title":"Morphologically Aware Word-Level Translation","date":"2020-11-15","arxiv_id":"2011.07593","n_code_links":0,"syntology":null},{"paper":"/paper/actbert-learning-global-local-video-text-1","slug":"actbert-learning-global-local-video-text-1","title":"ActBERT: Learning Global-Local Video-Text Representations","date":"2020-11-14","arxiv_id":"2011.07231","n_code_links":1,"syntology":null},{"paper":"/paper/enabling-the-sense-of-self-in-a-dual-arm","slug":"enabling-the-sense-of-self-in-a-dual-arm","title":"Enabling the Sense of Self in a Dual-Arm Robot","date":"2020-11-13","arxiv_id":"2011.07026","n_code_links":1,"syntology":null},{"paper":null,"slug":"domain-generalization-in-biosignal","title":"Domain Generalization in Biosignal Classification","date":"2020-11-12","arxiv_id":"2011.06207","n_code_links":0,"syntology":null},{"paper":null,"slug":"identifying-depressive-symptoms-from-tweets","title":"Identifying Depressive Symptoms from Tweets: Figurative Language Enabled Multitask Learning Framework","date":"2020-11-12","arxiv_id":"2011.06149","n_code_links":0,"syntology":null},{"paper":null,"slug":"unsupervised-multimodal-image-registration","title":"Unsupervised Multimodal Image Registration with Adaptative Gradient Guidance","date":"2020-11-12","arxiv_id":"2011.06216","n_code_links":0,"syntology":null},{"paper":"/paper/noise-conscious-training-of-non-local-neural","slug":"noise-conscious-training-of-non-local-neural","title":"Noise Conscious Training of Non Local Neural Network powered by Self Attentive Spectral Normalized Markovian Patch GAN for Low Dose CT Denoising","date":"2020-11-11","arxiv_id":"2011.05684","n_code_links":1,"syntology":null},{"paper":null,"slug":"transformers-for-one-shot-visual-imitation","title":"Transformers for One-Shot Visual Imitation","date":"2020-11-11","arxiv_id":"2011.05970","n_code_links":0,"syntology":null}],"record_sha256":"9fd050d15f4e76de7a5aae062d79d3b5e0ca9659c1300c8714bb1e4bdb3507b9","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}