{"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/contrastive-learning/papers/33","list_of":"/method/contrastive-learning","method":"Contrastive Learning","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":33,"pages_in_order":51,"rows_per_page":100,"rows":[3201,3300],"of":5057,"counts":{"archive_papers_tagged":5057,"with_a_code_link":2344,"where_syntology_ran_a_sample":654,"not_listed_spam_title":0,"listed":5057,"listed_where_code_ran":654,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":568,"every_run_a_failure_of_syntologys_instrument":86,"listed_with_a_run_with_no_instrument_failure":568,"listed_every_run_a_failure_of_syntologys_instrument":86,"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/contrastive-learning","prev":"/method/contrastive-learning/papers/32","next":"/method/contrastive-learning/papers/34","papers":[{"paper":"/paper/unsupervised-visible-infrared-person-re","slug":"unsupervised-visible-infrared-person-re","title":"Unsupervised Visible-Infrared Person Re-Identification via Progressive Graph Matching and Alternate Learning","date":"2023-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/vilem-visual-language-error-modeling-for","slug":"vilem-visual-language-error-modeling-for","title":"ViLEM: Visual-Language Error Modeling for Image-Text Retrieval","date":"2023-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"winner-weakly-supervised-hierarchical","title":"WINNER: Weakly-Supervised hIerarchical decompositioN and aligNment for Spatio-tEmporal Video gRounding","date":"2023-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"you-do-not-need-additional-priors-or","title":"You Do Not Need Additional Priors or Regularizers in Retinex-Based Low-Light Image Enhancement","date":"2023-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-temporal-contrastive-clustering","title":"Deep Temporal Contrastive Clustering","date":"2022-12-29","arxiv_id":"2212.14366","n_code_links":0,"syntology":null},{"paper":"/paper/heterogeneous-graph-contrastive-learning-with","slug":"heterogeneous-graph-contrastive-learning-with","title":"Heterogeneous Graph Contrastive Learning with Meta-path Contexts and Adaptively Weighted Negative Samples","date":"2022-12-28","arxiv_id":"2212.13847","n_code_links":1,"syntology":null},{"paper":"/paper/tempclr-temporal-alignment-representation","slug":"tempclr-temporal-alignment-representation","title":"TempCLR: Temporal Alignment Representation with Contrastive Learning","date":"2022-12-28","arxiv_id":"2212.13738","n_code_links":1,"syntology":{"ran":3,"of":5,"n_ran_checked":0,"n_instrument":3,"unverified":2,"pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 2 unverified","official":{"repos":["yyuncong/tempclr"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"truncate-split-contrast-a-framework-for","title":"Truncate-Split-Contrast: A Framework for Learning from Mislabeled Videos","date":"2022-12-27","arxiv_id":"2212.13495","n_code_links":0,"syntology":null},{"paper":"/paper/precise-location-matching-improves-dense","slug":"precise-location-matching-improves-dense","title":"Precise Location Matching Improves Dense Contrastive Learning in Digital Pathology","date":"2022-12-23","arxiv_id":"2212.12105","n_code_links":1,"syntology":null},{"paper":null,"slug":"restoring-vision-in-hazy-weather-with","title":"Restoring Vision in Hazy Weather with Hierarchical Contrastive Learning","date":"2022-12-22","arxiv_id":"2212.11473","n_code_links":0,"syntology":null},{"paper":null,"slug":"understanding-and-improving-the-role-of","title":"Understanding and Improving the Role of Projection Head in Self-Supervised Learning","date":"2022-12-22","arxiv_id":"2212.11491","n_code_links":0,"syntology":null},{"paper":null,"slug":"moquad-motion-focused-quadruple-construction","title":"MoQuad: Motion-focused Quadruple Construction for Video Contrastive Learning","date":"2022-12-21","arxiv_id":"2212.10870","n_code_links":0,"syntology":null},{"paper":"/paper/multi-modal-molecule-structure-text-model-for","slug":"multi-modal-molecule-structure-text-model-for","title":"Multi-modal Molecule Structure-text Model for Text-based Retrieval and Editing","date":"2022-12-21","arxiv_id":"2212.10789","n_code_links":1,"syntology":{"ran":2,"of":4,"n_ran_checked":1,"n_instrument":1,"unverified":2,"pointer_only":4,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","official":{"repos":["chao1224/moleculestm"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["official","unlocated"]}}},{"paper":"/paper/similarity-contrastive-estimation-for-image","slug":"similarity-contrastive-estimation-for-image","title":"Similarity Contrastive Estimation for Image and Video Soft Contrastive Self-Supervised Learning","date":"2022-12-21","arxiv_id":"2212.11187","n_code_links":2,"syntology":null},{"paper":"/paper/coco-coherence-enhanced-machine-generated","slug":"coco-coherence-enhanced-machine-generated","title":"CoCo: Coherence-Enhanced Machine-Generated Text Detection Under Data Limitation With Contrastive Learning","date":"2022-12-20","arxiv_id":"2212.10341","n_code_links":1,"syntology":null},{"paper":"/paper/contrastive-learning-reduces-hallucination-in","slug":"contrastive-learning-reduces-hallucination-in","title":"Contrastive Learning Reduces Hallucination in Conversations","date":"2022-12-20","arxiv_id":"2212.10400","n_code_links":1,"syntology":null},{"paper":"/paper/query-as-context-pre-training-for-dense","slug":"query-as-context-pre-training-for-dense","title":"Query-as-context Pre-training for Dense Passage Retrieval","date":"2022-12-19","arxiv_id":"2212.09598","n_code_links":2,"syntology":null},{"paper":"/paper/waco-word-aligned-contrastive-learning-for","slug":"waco-word-aligned-contrastive-learning-for","title":"WACO: Word-Aligned Contrastive Learning for Speech Translation","date":"2022-12-19","arxiv_id":"2212.09359","n_code_links":1,"syntology":null},{"paper":"/paper/wukong-reader-multi-modal-pre-training-for","slug":"wukong-reader-multi-modal-pre-training-for","title":"Wukong-Reader: Multi-modal Pre-training for Fine-grained Visual Document Understanding","date":"2022-12-19","arxiv_id":"2212.09621","n_code_links":1,"syntology":null},{"paper":null,"slug":"disentangling-learnable-and-memorizable-data","title":"Disentangling Learnable and Memorizable Data via Contrastive Learning for Semantic Communications","date":"2022-12-18","arxiv_id":"2212.09071","n_code_links":0,"syntology":null},{"paper":"/paper/on-isotropy-and-learning-dynamics-of","slug":"on-isotropy-and-learning-dynamics-of","title":"On Isotropy, Contextualization and Learning Dynamics of Contrastive-based Sentence Representation Learning","date":"2022-12-18","arxiv_id":"2212.09170","n_code_links":1,"syntology":null},{"paper":null,"slug":"hyperbolic-hierarchical-contrastive-hashing","title":"Hyperbolic Hierarchical Contrastive Hashing","date":"2022-12-17","arxiv_id":"2212.08904","n_code_links":0,"syntology":null},{"paper":"/paper/attentive-mask-clip","slug":"attentive-mask-clip","title":"Attentive Mask CLIP","date":"2022-12-16","arxiv_id":"2212.08653","n_code_links":1,"syntology":null},{"paper":"/paper/image-and-language-understanding-from-pixels","slug":"image-and-language-understanding-from-pixels","title":"CLIPPO: Image-and-Language Understanding from Pixels Only","date":"2022-12-15","arxiv_id":"2212.08045","n_code_links":1,"syntology":null},{"paper":"/paper/nerf-art-text-driven-neural-radiance-fields","slug":"nerf-art-text-driven-neural-radiance-fields","title":"NeRF-Art: Text-Driven Neural Radiance Fields Stylization","date":"2022-12-15","arxiv_id":"2212.08070","n_code_links":1,"syntology":{"ran":8,"of":9,"n_ran_checked":7,"n_instrument":1,"unverified":1,"pointer_only":0,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["cassiePython/NeRF-Art"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/establishing-a-stronger-baseline-for","slug":"establishing-a-stronger-baseline-for","title":"Establishing a stronger baseline for lightweight contrastive models","date":"2022-12-14","arxiv_id":"2212.07158","n_code_links":1,"syntology":null},{"paper":"/paper/ma-gcl-model-augmentation-tricks-for-graph","slug":"ma-gcl-model-augmentation-tricks-for-graph","title":"MA-GCL: Model Augmentation Tricks for Graph Contrastive Learning","date":"2022-12-14","arxiv_id":"2212.07035","n_code_links":1,"syntology":null},{"paper":"/paper/mitigating-negative-style-transfer-in-hybrid","slug":"mitigating-negative-style-transfer-in-hybrid","title":"Mitigating Negative Style Transfer in Hybrid Dialogue System","date":"2022-12-14","arxiv_id":"2212.07183","n_code_links":1,"syntology":null},{"paper":null,"slug":"significantly-improving-zero-shot-x-ray","title":"Significantly improving zero-shot X-ray pathology classification via fine-tuning pre-trained image-text encoders","date":"2022-12-14","arxiv_id":"2212.07050","n_code_links":0,"syntology":null},{"paper":"/paper/tailoring-visual-object-representations-to","slug":"tailoring-visual-object-representations-to","title":"Tailoring Visual Object Representations to Human Requirements: A Case Study with a Recycling Robot","date":"2022-12-14","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/understanding-zero-shot-adversarial","slug":"understanding-zero-shot-adversarial","title":"Understanding Zero-Shot Adversarial Robustness for Large-Scale Models","date":"2022-12-14","arxiv_id":"2212.07016","n_code_links":2,"syntology":null},{"paper":null,"slug":"a-machine-learning-enhanced-approach-for","title":"A Machine Learning Enhanced Approach for Automated Sunquake Detection in Acoustic Emission Maps","date":"2022-12-13","arxiv_id":"2212.06717","n_code_links":0,"syntology":null},{"paper":null,"slug":"boosting-semi-supervised-learning-with","title":"Boosting Semi-Supervised Learning with Contrastive Complementary Labeling","date":"2022-12-13","arxiv_id":"2212.06643","n_code_links":0,"syntology":null},{"paper":null,"slug":"coarse-to-fine-contrastive-learning-on-graphs","title":"Coarse-to-Fine Contrastive Learning on Graphs","date":"2022-12-13","arxiv_id":"2212.06423","n_code_links":0,"syntology":null},{"paper":null,"slug":"generative-artificial-intelligence-enabled","title":"Generative artificial intelligence-enabled dynamic detection of nicotine-related circuits","date":"2022-12-13","arxiv_id":"2212.06330","n_code_links":0,"syntology":null},{"paper":"/paper/on-the-evolution-of-hateful-memes-by-means-of","slug":"on-the-evolution-of-hateful-memes-by-means-of","title":"On the Evolution of (Hateful) Memes by Means of Multimodal Contrastive Learning","date":"2022-12-13","arxiv_id":"2212.06573","n_code_links":2,"syntology":null},{"paper":"/paper/also-automotive-lidar-self-supervision-by","slug":"also-automotive-lidar-self-supervision-by","title":"ALSO: Automotive Lidar Self-supervision by Occupancy estimation","date":"2022-12-12","arxiv_id":"2212.05867","n_code_links":1,"syntology":null},{"paper":"/paper/masked-autoencoders-is-an-effective-solution","slug":"masked-autoencoders-is-an-effective-solution","title":"Masked autoencoders are effective solution to transformer data-hungry","date":"2022-12-12","arxiv_id":"2212.05677","n_code_links":1,"syntology":{"ran":1,"of":2,"n_ran_checked":1,"n_instrument":0,"unverified":1,"pointer_only":1,"phrase":"1 ran (of which 0 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) · 1 unverified","official":{"repos":["talented-q/sdmae"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"momentum-contrastive-pre-training-for","title":"Momentum Contrastive Pre-training for Question Answering","date":"2022-12-12","arxiv_id":"2212.05762","n_code_links":0,"syntology":null},{"paper":"/paper/feature-level-debiased-natural-language","slug":"feature-level-debiased-natural-language","title":"Feature-Level Debiased Natural Language Understanding","date":"2022-12-11","arxiv_id":"2212.05421","n_code_links":1,"syntology":null},{"paper":"/paper/transductive-linear-probing-a-novel-framework","slug":"transductive-linear-probing-a-novel-framework","title":"Transductive Linear Probing: A Novel Framework for Few-Shot Node Classification","date":"2022-12-11","arxiv_id":"2212.05606","n_code_links":1,"syntology":null},{"paper":"/paper/untargeted-attack-against-federated","slug":"untargeted-attack-against-federated","title":"Untargeted Attack against Federated Recommendation Systems via Poisonous Item Embeddings and the Defense","date":"2022-12-11","arxiv_id":"2212.05399","n_code_links":1,"syntology":null},{"paper":null,"slug":"using-multiple-instance-learning-to-build","title":"Using Multiple Instance Learning to Build Multimodal Representations","date":"2022-12-11","arxiv_id":"2212.05561","n_code_links":0,"syntology":null},{"paper":"/paper/yolocurvseg-you-only-label-one-noisy-skeleton","slug":"yolocurvseg-you-only-label-one-noisy-skeleton","title":"YoloCurvSeg: You Only Label One Noisy Skeleton for Vessel-style Curvilinear Structure Segmentation","date":"2022-12-11","arxiv_id":"2212.05566","n_code_links":1,"syntology":null},{"paper":null,"slug":"contrastive-view-design-strategies-to-enhance","title":"Contrastive View Design Strategies to Enhance Robustness to Domain Shifts in Downstream Object Detection","date":"2022-12-09","arxiv_id":"2212.04613","n_code_links":0,"syntology":null},{"paper":null,"slug":"med-se-medical-entity-definition-based","title":"MED-SE: Medical Entity Definition-based Sentence Embedding","date":"2022-12-09","arxiv_id":"2212.04734","n_code_links":0,"syntology":null},{"paper":null,"slug":"object-goal-navigation-with-end-to-end-self","title":"Self-Supervised Object Goal Navigation with In-Situ Finetuning","date":"2022-12-09","arxiv_id":"2212.05923","n_code_links":0,"syntology":null},{"paper":"/paper/open-vocabulary-semantic-segmentation-with-2","slug":"open-vocabulary-semantic-segmentation-with-2","title":"Open Vocabulary Semantic Segmentation with Patch Aligned Contrastive Learning","date":"2022-12-09","arxiv_id":"2212.04994","n_code_links":1,"syntology":null},{"paper":"/paper/generating-and-weighting-semantically","slug":"generating-and-weighting-semantically","title":"Generating and Weighting Semantically Consistent Sample Pairs for Ultrasound Contrastive Learning","date":"2022-12-08","arxiv_id":"2212.04097","n_code_links":1,"syntology":null},{"paper":"/paper/graph-matching-with-bi-level-noisy","slug":"graph-matching-with-bi-level-noisy","title":"Graph Matching with Bi-level Noisy Correspondence","date":"2022-12-08","arxiv_id":"2212.04085","n_code_links":3,"syntology":{"ran":7,"of":7,"n_ran_checked":1,"n_instrument":6,"unverified":0,"pointer_only":7,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 6 where Syntology's instrument failed) · 0 unverified","official":{"repos":["Thinklab-SJTU/ThinkMatch","xlearning-scu/2023-iccv-common","Lin-Yijie/Graph-Matching-Networks"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"localized-contrastive-learning-on-graphs","title":"Localized Contrastive Learning on Graphs","date":"2022-12-08","arxiv_id":"2212.04604","n_code_links":0,"syntology":null},{"paper":"/paper/contrastive-deep-graph-clustering-with","slug":"contrastive-deep-graph-clustering-with","title":"GraphLearner: Graph Node Clustering with Fully Learnable Augmentation","date":"2022-12-07","arxiv_id":"2212.03559","n_code_links":2,"syntology":null},{"paper":"/paper/simvtp-simple-video-text-pre-training-with","slug":"simvtp-simple-video-text-pre-training-with","title":"SimVTP: Simple Video Text Pre-training with Masked Autoencoders","date":"2022-12-07","arxiv_id":"2212.03490","n_code_links":0,"syntology":null},{"paper":"/paper/internvideo-general-video-foundation-models","slug":"internvideo-general-video-foundation-models","title":"InternVideo: General Video Foundation Models via Generative and Discriminative Learning","date":"2022-12-06","arxiv_id":"2212.03191","n_code_links":2,"syntology":{"ran":3,"of":3,"n_ran_checked":0,"n_instrument":3,"unverified":0,"pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","official":{"repos":["opengvlab/internvideo"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/neural-machine-translation-with-contrastive","slug":"neural-machine-translation-with-contrastive","title":"Neural Machine Translation with Contrastive Translation Memories","date":"2022-12-06","arxiv_id":"2212.03140","n_code_links":1,"syntology":null},{"paper":null,"slug":"cross-domain-few-shot-relation-extraction-via","title":"Cross-Domain Few-Shot Relation Extraction via Representation Learning and Domain Adaptation","date":"2022-12-05","arxiv_id":"2212.02560","n_code_links":0,"syntology":null},{"paper":null,"slug":"land-use-prediction-using-electro-optical-to","title":"Land Use Prediction using Electro-Optical to SAR Few-Shot Transfer Learning","date":"2022-12-04","arxiv_id":"2212.03084","n_code_links":0,"syntology":null},{"paper":"/paper/cotmix-contrastive-domain-adaptation-for-time","slug":"cotmix-contrastive-domain-adaptation-for-time","title":"Contrastive Domain Adaptation for Time-Series via Temporal Mixup","date":"2022-12-03","arxiv_id":"2212.01555","n_code_links":1,"syntology":{"ran":0,"of":1,"n_ran_checked":0,"n_instrument":0,"unverified":1,"pointer_only":1,"phrase":"0 ran · 1 unverified","official":{"repos":["emadeldeen24/cotmix"],"state":"official: not harvested","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":[]}}},{"paper":null,"slug":"3d-togo-towards-text-guided-cross-category-3d","title":"3D-TOGO: Towards Text-Guided Cross-Category 3D Object Generation","date":"2022-12-02","arxiv_id":"2212.01103","n_code_links":0,"syntology":null},{"paper":"/paper/cross-domain-graph-anomaly-detection-via","slug":"cross-domain-graph-anomaly-detection-via","title":"Cross-Domain Graph Anomaly Detection via Anomaly-aware Contrastive Alignment","date":"2022-12-02","arxiv_id":"2212.01096","n_code_links":1,"syntology":null},{"paper":null,"slug":"fedcoco-a-memory-efficient-federated-self","title":"Self-supervised On-device Federated Learning from Unlabeled Streams","date":"2022-12-02","arxiv_id":"2212.01006","n_code_links":0,"syntology":null},{"paper":null,"slug":"few-shot-nested-named-entity-recognition","title":"Few-Shot Nested Named Entity Recognition","date":"2022-12-02","arxiv_id":"2212.00953","n_code_links":0,"syntology":null},{"paper":"/paper/mhccl-masked-hierarchical-cluster-wise","slug":"mhccl-masked-hierarchical-cluster-wise","title":"MHCCL: Masked Hierarchical Cluster-Wise Contrastive Learning for Multivariate Time Series","date":"2022-12-02","arxiv_id":"2212.01141","n_code_links":1,"syntology":null},{"paper":null,"slug":"spectral-feature-augmentation-for-graph","title":"Spectral Feature Augmentation for Graph Contrastive Learning and Beyond","date":"2022-12-02","arxiv_id":"2212.01026","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-general-purpose-supervisory-signal-for","title":"A General Purpose Supervisory Signal for Embodied Agents","date":"2022-12-01","arxiv_id":"2212.01186","n_code_links":0,"syntology":null},{"paper":"/paper/cl4ctr-a-contrastive-learning-framework-for","slug":"cl4ctr-a-contrastive-learning-framework-for","title":"CL4CTR: A Contrastive Learning Framework for CTR Prediction","date":"2022-12-01","arxiv_id":"2212.00522","n_code_links":1,"syntology":null},{"paper":null,"slug":"graph-anomaly-detection-via-multi-scale","title":"Graph Anomaly Detection via Multi-Scale Contrastive Learning Networks with Augmented View","date":"2022-12-01","arxiv_id":"2212.00535","n_code_links":0,"syntology":null},{"paper":"/paper/hyperbolic-contrastive-learning-for-visual","slug":"hyperbolic-contrastive-learning-for-visual","title":"Hyperbolic Contrastive Learning for Visual Representations beyond Objects","date":"2022-12-01","arxiv_id":"2212.00653","n_code_links":1,"syntology":null},{"paper":"/paper/learning-to-generate-text-grounded-mask-for","slug":"learning-to-generate-text-grounded-mask-for","title":"Learning to Generate Text-grounded Mask for Open-world Semantic Segmentation from Only Image-Text Pairs","date":"2022-12-01","arxiv_id":"2212.00785","n_code_links":1,"syntology":{"ran":5,"of":8,"n_ran_checked":4,"n_instrument":1,"unverified":3,"pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","official":{"repos":["kakaobrain/tcl"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":"/paper/one-shot-recognition-of-any-material-anywhere","slug":"one-shot-recognition-of-any-material-anywhere","title":"One-shot recognition of any material anywhere using contrastive learning with physics-based rendering","date":"2022-12-01","arxiv_id":"2212.00648","n_code_links":1,"syntology":null},{"paper":null,"slug":"research-on-the-application-of-contrastive","title":"An Effective Deployment of Contrastive Learning in Multi-label Text Classification","date":"2022-12-01","arxiv_id":"2212.00552","n_code_links":0,"syntology":null},{"paper":"/paper/gennape-towards-generalized-neural","slug":"gennape-towards-generalized-neural","title":"GENNAPE: Towards Generalized Neural Architecture Performance Estimators","date":"2022-11-30","arxiv_id":"2211.17226","n_code_links":1,"syntology":{"ran":6,"of":8,"n_ran_checked":6,"n_instrument":0,"unverified":2,"pointer_only":8,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["Ascend-Research/GENNAPE"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/normalized-contrastive-learning-for-text","slug":"normalized-contrastive-learning-for-text","title":"Normalized Contrastive Learning for Text-Video Retrieval","date":"2022-11-30","arxiv_id":"2212.11790","n_code_links":1,"syntology":null},{"paper":"/paper/textual-enhanced-contrastive-learning-for","slug":"textual-enhanced-contrastive-learning-for","title":"Textual Enhanced Contrastive Learning for Solving Math Word Problems","date":"2022-11-29","arxiv_id":"2211.16022","n_code_links":1,"syntology":null},{"paper":null,"slug":"gadmsl-graph-anomaly-detection-on-attributed","title":"ARISE: Graph Anomaly Detection on Attributed Networks via Substructure Awareness","date":"2022-11-28","arxiv_id":"2211.15255","n_code_links":0,"syntology":null},{"paper":"/paper/semi-supervised-confidence-level-based","slug":"semi-supervised-confidence-level-based","title":"Semi-Supervised Confidence-Level-based Contrastive Discrimination for Class-Imbalanced Semantic Segmentation","date":"2022-11-28","arxiv_id":"2211.15066","n_code_links":1,"syntology":null},{"paper":"/paper/task-aware-asynchronous-multi-task-model-with","slug":"task-aware-asynchronous-multi-task-model-with","title":"Task-Aware Asynchronous Multi-Task Model with Class Incremental Contrastive Learning for Surgical Scene Understanding","date":"2022-11-28","arxiv_id":"2211.15327","n_code_links":1,"syntology":null},{"paper":"/paper/a-knowledge-based-learning-framework-for-self","slug":"a-knowledge-based-learning-framework-for-self","title":"A Knowledge-based Learning Framework for Self-supervised Pre-training Towards Enhanced Recognition of Biomedical Microscopy Images","date":"2022-11-27","arxiv_id":"2211.14715","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-theoretical-study-of-inductive-biases-in","title":"A Theoretical Study of Inductive Biases in Contrastive Learning","date":"2022-11-27","arxiv_id":"2211.14699","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-unified-framework-for-contrastive-learning","title":"A Unified Framework for Contrastive Learning from a Perspective of Affinity Matrix","date":"2022-11-26","arxiv_id":"2211.14516","n_code_links":0,"syntology":null},{"paper":"/paper/progressive-disentangled-representation","slug":"progressive-disentangled-representation","title":"Progressive Disentangled Representation Learning for Fine-Grained Controllable Talking Head Synthesis","date":"2022-11-26","arxiv_id":"2211.14506","n_code_links":1,"syntology":null},{"paper":"/paper/residual-pattern-learning-for-pixel-wise-out","slug":"residual-pattern-learning-for-pixel-wise-out","title":"Residual Pattern Learning for Pixel-wise Out-of-Distribution Detection in Semantic Segmentation","date":"2022-11-26","arxiv_id":"2211.14512","n_code_links":2,"syntology":{"ran":7,"of":10,"n_ran_checked":6,"n_instrument":1,"unverified":3,"pointer_only":1,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","official":{"repos":["yyliu01/rpl"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":"/paper/slicematch-geometry-guided-aggregation-for","slug":"slicematch-geometry-guided-aggregation-for","title":"SliceMatch: Geometry-guided Aggregation for Cross-View Pose Estimation","date":"2022-11-26","arxiv_id":"2211.14651","n_code_links":1,"syntology":null},{"paper":null,"slug":"supervised-contrastive-prototype-learning","title":"Supervised Contrastive Prototype Learning: Augmentation Free Robust Neural Network","date":"2022-11-26","arxiv_id":"2211.14424","n_code_links":0,"syntology":null},{"paper":"/paper/towards-better-document-level-relation","slug":"towards-better-document-level-relation","title":"Towards Better Document-level Relation Extraction via Iterative Inference","date":"2022-11-26","arxiv_id":"2211.14470","n_code_links":1,"syntology":null},{"paper":"/paper/unsupervised-wildfire-change-detection-based","slug":"unsupervised-wildfire-change-detection-based","title":"Unsupervised Wildfire Change Detection based on Contrastive Learning","date":"2022-11-26","arxiv_id":"2211.14654","n_code_links":1,"syntology":null},{"paper":"/paper/copy-pasting-coherent-depth-regions-improves","slug":"copy-pasting-coherent-depth-regions-improves","title":"Copy-Pasting Coherent Depth Regions Improves Contrastive Learning for Urban-Scene Segmentation","date":"2022-11-25","arxiv_id":"2211.14074","n_code_links":1,"syntology":null},{"paper":null,"slug":"contrastive-pretraining-for-semantic","title":"Contrastive pretraining for semantic segmentation is robust to noisy positive pairs","date":"2022-11-24","arxiv_id":"2211.13756","n_code_links":0,"syntology":null},{"paper":null,"slug":"cross-domain-transfer-of-defect-features-in","title":"Cross-domain Transfer of defect features in technical domains based on partial target data","date":"2022-11-24","arxiv_id":"2211.13662","n_code_links":0,"syntology":null},{"paper":null,"slug":"few-shot-object-detection-with-refined","title":"Few-shot Object Detection with Refined Contrastive Learning","date":"2022-11-24","arxiv_id":"2211.13495","n_code_links":0,"syntology":null},{"paper":"/paper/hierarchical-consistent-contrastive-learning","slug":"hierarchical-consistent-contrastive-learning","title":"Hierarchical Consistent Contrastive Learning for Skeleton-Based Action Recognition with Growing Augmentations","date":"2022-11-24","arxiv_id":"2211.13466","n_code_links":1,"syntology":null},{"paper":"/paper/pose-disentangled-contrastive-learning-for","slug":"pose-disentangled-contrastive-learning-for","title":"Pose-disentangled Contrastive Learning for Self-supervised Facial Representation","date":"2022-11-24","arxiv_id":"2211.13490","n_code_links":1,"syntology":null},{"paper":"/paper/self-supervised-vision-language-pretraining","slug":"self-supervised-vision-language-pretraining","title":"Self-supervised vision-language pretraining for Medical visual question answering","date":"2022-11-24","arxiv_id":"2211.13594","n_code_links":2,"syntology":{"ran":6,"of":10,"n_ran_checked":1,"n_instrument":5,"unverified":4,"pointer_only":3,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 5 where Syntology's instrument failed) · 4 unverified","official":{"repos":["pengfeiliheu/m2i2"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":4,"ran_from_kinds":["official"]}}},{"paper":"/paper/contrastive-identity-aware-learning-for-multi","slug":"contrastive-identity-aware-learning-for-multi","title":"Contrastive Identity-Aware Learning for Multi-Agent Value Decomposition","date":"2022-11-23","arxiv_id":"2211.12712","n_code_links":1,"syntology":null},{"paper":null,"slug":"how-do-cross-view-and-cross-modal-alignment","title":"How do Cross-View and Cross-Modal Alignment Affect Representations in Contrastive Learning?","date":"2022-11-23","arxiv_id":"2211.13309","n_code_links":0,"syntology":null},{"paper":"/paper/mitigating-data-sparsity-for-short-text-topic","slug":"mitigating-data-sparsity-for-short-text-topic","title":"Mitigating Data Sparsity for Short Text Topic Modeling by Topic-Semantic Contrastive Learning","date":"2022-11-23","arxiv_id":"2211.12878","n_code_links":2,"syntology":{"ran":5,"of":6,"n_ran_checked":5,"n_instrument":0,"unverified":1,"pointer_only":3,"phrase":"5 ran (of which 4 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["bobxwu/tsctm"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":3,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"paper":null,"slug":"prototypical-contrastive-learning-and","title":"Prototypical Contrastive Learning and Adaptive Interest Selection for Candidate Generation in Recommendations","date":"2022-11-23","arxiv_id":"2211.12893","n_code_links":0,"syntology":null},{"paper":"/paper/robust-mean-teacher-for-continual-and-gradual","slug":"robust-mean-teacher-for-continual-and-gradual","title":"Robust Mean Teacher for Continual and Gradual Test-Time Adaptation","date":"2022-11-23","arxiv_id":"2211.13081","n_code_links":1,"syntology":null},{"paper":"/paper/texts-as-images-in-prompt-tuning-for-multi","slug":"texts-as-images-in-prompt-tuning-for-multi","title":"Texts as Images in Prompt Tuning for Multi-Label Image Recognition","date":"2022-11-23","arxiv_id":"2211.12739","n_code_links":1,"syntology":null},{"paper":"/paper/on-narrative-information-and-the-distillation","slug":"on-narrative-information-and-the-distillation","title":"On Narrative Information and the Distillation of Stories","date":"2022-11-22","arxiv_id":"2211.12423","n_code_links":1,"syntology":null}],"record_sha256":"41b7784aa271208669f12e76490e9c007b581fcac0a8b6903bbc1b1a29f43f08","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}