{"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/35","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":35,"pages_in_order":51,"rows_per_page":100,"rows":[3401,3500],"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/34","next":"/method/contrastive-learning/papers/36","papers":[{"paper":null,"slug":"self-supervised-training-of-speaker-encoder","title":"Self-Supervised Training of Speaker Encoder with Multi-Modal Diverse Positive Pairs","date":"2022-10-27","arxiv_id":"2210.15385","n_code_links":0,"syntology":null},{"paper":"/paper/supervised-contrastive-learning-for-3","slug":"supervised-contrastive-learning-for-3","title":"Pretraining Respiratory Sound Representations using Metadata and Contrastive Learning","date":"2022-10-27","arxiv_id":"2210.16192","n_code_links":1,"syntology":null},{"paper":null,"slug":"bi-link-bridging-inductive-link-predictions","title":"Bi-Link: Bridging Inductive Link Predictions from Text via Contrastive Learning of Transformers and Prompts","date":"2022-10-26","arxiv_id":"2210.14463","n_code_links":0,"syntology":null},{"paper":"/paper/boosting-semi-supervised-semantic","slug":"boosting-semi-supervised-semantic","title":"Boosting Semi-Supervised Semantic Segmentation with Probabilistic Representations","date":"2022-10-26","arxiv_id":"2210.14670","n_code_links":1,"syntology":null},{"paper":null,"slug":"learning-deep-sensorimotor-policies-for","title":"Learning Deep Sensorimotor Policies for Vision-based Autonomous Drone Racing","date":"2022-10-26","arxiv_id":"2210.14985","n_code_links":0,"syntology":null},{"paper":"/paper/mabel-attenuating-gender-bias-using-textual","slug":"mabel-attenuating-gender-bias-using-textual","title":"MABEL: Attenuating Gender Bias using Textual Entailment Data","date":"2022-10-26","arxiv_id":"2210.14975","n_code_links":2,"syntology":{"ran":3,"of":6,"n_ran_checked":1,"n_instrument":2,"unverified":3,"pointer_only":0,"phrase":"3 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; 2 where Syntology's instrument failed) · 3 unverified","official":{"repos":["princeton-nlp/mabel"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"meta-node-a-concise-approach-to-effectively","title":"Meta-node: A Concise Approach to Effectively Learn Complex Relationships in Heterogeneous Graphs","date":"2022-10-26","arxiv_id":"2210.14480","n_code_links":0,"syntology":null},{"paper":null,"slug":"multimodal-contrastive-learning-via-uni-modal","title":"Multimodal Contrastive Learning via Uni-Modal Coding and Cross-Modal Prediction for Multimodal Sentiment Analysis","date":"2022-10-26","arxiv_id":"2210.14556","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-chinese-spelling-check-framework-based-on","title":"A Chinese Spelling Check Framework Based on Reverse Contrastive Learning","date":"2022-10-25","arxiv_id":"2210.13823","n_code_links":0,"syntology":null},{"paper":"/paper/contrastive-search-is-what-you-need-for","slug":"contrastive-search-is-what-you-need-for","title":"Contrastive Search Is What You Need For Neural Text Generation","date":"2022-10-25","arxiv_id":"2210.14140","n_code_links":3,"syntology":{"ran":9,"of":9,"n_ran_checked":3,"n_instrument":6,"unverified":0,"pointer_only":4,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 3 honoured, 0 violated, 0 with no contract checked; 6 where Syntology's instrument failed) · 0 unverified","official":{"repos":["yxuansu/contrastive_search_is_what_you_need"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/line-graph-contrastive-learning-for-link","slug":"line-graph-contrastive-learning-for-link","title":"Line Graph Contrastive Learning for Link Prediction","date":"2022-10-25","arxiv_id":"2210.13795","n_code_links":1,"syntology":null},{"paper":null,"slug":"shared-manifold-learning-using-a-triplet","title":"Shared Manifold Learning Using a Triplet Network for Multiple Sensor Translation and Fusion with Missing Data","date":"2022-10-25","arxiv_id":"2210.17311","n_code_links":0,"syntology":null},{"paper":"/paper/unsupervised-anomaly-detection-for-auditing","slug":"unsupervised-anomaly-detection-for-auditing","title":"Unsupervised Anomaly Detection for Auditing Data and Impact of Categorical Encodings","date":"2022-10-25","arxiv_id":"2210.14056","n_code_links":1,"syntology":null},{"paper":"/paper/contrastive-representation-learning-for-gaze","slug":"contrastive-representation-learning-for-gaze","title":"Contrastive Representation Learning for Gaze Estimation","date":"2022-10-24","arxiv_id":"2210.13404","n_code_links":1,"syntology":{"ran":1,"of":3,"n_ran_checked":1,"n_instrument":0,"unverified":2,"pointer_only":3,"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) · 2 unverified; the one sample that ran constructed an object rather than computing a result","official":{"repos":["jswati31/gazeclr"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/event-centric-question-answering-via","slug":"event-centric-question-answering-via","title":"Event-Centric Question Answering via Contrastive Learning and Invertible Event Transformation","date":"2022-10-24","arxiv_id":"2210.12902","n_code_links":1,"syntology":null},{"paper":null,"slug":"heterogeneous-information-crossing-on-graphs","title":"Heterogeneous Information Crossing on Graphs for Session-based Recommender Systems","date":"2022-10-24","arxiv_id":"2210.12940","n_code_links":0,"syntology":null},{"paper":null,"slug":"adversarial-pretraining-of-self-supervised","title":"Adversarial Pretraining of Self-Supervised Deep Networks: Past, Present and Future","date":"2022-10-23","arxiv_id":"2210.13463","n_code_links":0,"syntology":null},{"paper":"/paper/neural-eigenfunctions-are-structured","slug":"neural-eigenfunctions-are-structured","title":"Neural Eigenfunctions Are Structured Representation Learners","date":"2022-10-23","arxiv_id":"2210.12637","n_code_links":1,"syntology":null},{"paper":"/paper/rethinking-rotation-in-self-supervised","slug":"rethinking-rotation-in-self-supervised","title":"Rethinking Rotation in Self-Supervised Contrastive Learning: Adaptive Positive or Negative Data Augmentation","date":"2022-10-23","arxiv_id":"2210.12681","n_code_links":1,"syntology":null},{"paper":"/paper/tail-batch-sampling-approximating-global","slug":"tail-batch-sampling-approximating-global","title":"Global Contrastive Batch Sampling via Optimization on Sample Permutations","date":"2022-10-23","arxiv_id":"2210.12874","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":0,"phrase":"1 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; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["vinayak1/gcbs"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/contrastive-prototypical-network-with","slug":"contrastive-prototypical-network-with","title":"Contrastive Prototypical Network with Wasserstein Confidence Penalty","date":"2022-10-21","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/exploring-representation-level-augmentation","slug":"exploring-representation-level-augmentation","title":"Exploring Representation-Level Augmentation for Code Search","date":"2022-10-21","arxiv_id":"2210.12285","n_code_links":1,"syntology":null},{"paper":null,"slug":"glcc-a-general-framework-for-graph-level","title":"GLCC: A General Framework for Graph-Level Clustering","date":"2022-10-21","arxiv_id":"2210.11879","n_code_links":0,"syntology":null},{"paper":null,"slug":"hcl-improving-graph-representation-with","title":"HCL: Improving Graph Representation with Hierarchical Contrastive Learning","date":"2022-10-21","arxiv_id":"2210.12020","n_code_links":0,"syntology":null},{"paper":"/paper/multi-view-reasoning-consistent-contrastive","slug":"multi-view-reasoning-consistent-contrastive","title":"Multi-View Reasoning: Consistent Contrastive Learning for Math Word Problem","date":"2022-10-21","arxiv_id":"2210.11694","n_code_links":1,"syntology":{"ran":9,"of":13,"n_ran_checked":8,"n_instrument":1,"unverified":4,"pointer_only":0,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 1 where Syntology's instrument failed) · 4 unverified","official":{"repos":["zwq2018/multi-view-consistency-for-mwp"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":4,"ran_from_kinds":["official"]}}},{"paper":"/paper/star-sql-guided-pre-training-for-context","slug":"star-sql-guided-pre-training-for-context","title":"STAR: SQL Guided Pre-Training for Context-dependent Text-to-SQL Parsing","date":"2022-10-21","arxiv_id":"2210.11888","n_code_links":1,"syntology":null},{"paper":"/paper/twin-contrastive-learning-for-online","slug":"twin-contrastive-learning-for-online","title":"Twin Contrastive Learning for Online Clustering","date":"2022-10-21","arxiv_id":"2210.11680","n_code_links":2,"syntology":null},{"paper":null,"slug":"apple-of-sodom-hidden-backdoors-in-superior","title":"Apple of Sodom: Hidden Backdoors in Superior Sentence Embeddings via Contrastive Learning","date":"2022-10-20","arxiv_id":"2210.11082","n_code_links":0,"syntology":null},{"paper":"/paper/balanced-adversarial-training-balancing-1","slug":"balanced-adversarial-training-balancing-1","title":"Balanced Adversarial Training: Balancing Tradeoffs between Fickleness and Obstinacy in NLP Models","date":"2022-10-20","arxiv_id":"2210.11498","n_code_links":1,"syntology":null},{"paper":"/paper/does-decentralized-learning-with-non-iid","slug":"does-decentralized-learning-with-non-iid","title":"Does Learning from Decentralized Non-IID Unlabeled Data Benefit from Self Supervision?","date":"2022-10-20","arxiv_id":"2210.10947","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":1,"n_instrument":1,"unverified":0,"pointer_only":0,"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) · 0 unverified","official":{"repos":["liruiw/dec-ssl"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/enhancing-out-of-distribution-detection-in","slug":"enhancing-out-of-distribution-detection-in","title":"Enhancing Out-of-Distribution Detection in Natural Language Understanding via Implicit Layer Ensemble","date":"2022-10-20","arxiv_id":"2210.11034","n_code_links":1,"syntology":{"ran":8,"of":9,"n_ran_checked":8,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["hyunsoocho77/lacl-official"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"mathematical-justification-of-hard-negative","title":"Mathematical Justification of Hard Negative Mining via Isometric Approximation Theorem","date":"2022-10-20","arxiv_id":"2210.11173","n_code_links":0,"syntology":null},{"paper":"/paper/ssit-saliency-guided-self-supervised-image","slug":"ssit-saliency-guided-self-supervised-image","title":"SSiT: Saliency-guided Self-supervised Image Transformer for Diabetic Retinopathy Grading","date":"2022-10-20","arxiv_id":"2210.10969","n_code_links":1,"syntology":null},{"paper":null,"slug":"towards-mitigating-the-problem-of","title":"Controller-Guided Partial Label Consistency Regularization with Unlabeled Data","date":"2022-10-20","arxiv_id":"2210.11194","n_code_links":0,"syntology":null},{"paper":null,"slug":"visual-semantic-contrastive-alignment-for-few","title":"Visual-Semantic Contrastive Alignment for Few-Shot Image Classification","date":"2022-10-20","arxiv_id":"2210.11000","n_code_links":0,"syntology":null},{"paper":null,"slug":"cpl-counterfactual-prompt-learning-for-vision","title":"CPL: Counterfactual Prompt Learning for Vision and Language Models","date":"2022-10-19","arxiv_id":"2210.10362","n_code_links":0,"syntology":null},{"paper":"/paper/dyted-disentangling-temporal-invariance-and","slug":"dyted-disentangling-temporal-invariance-and","title":"DyTed: Disentangled Representation Learning for Discrete-time Dynamic Graph","date":"2022-10-19","arxiv_id":"2210.10592","n_code_links":1,"syntology":null},{"paper":null,"slug":"havana-hard-negative-samples-aware-self","title":"HAVANA: Hard negAtiVe sAmples aware self-supervised coNtrastive leArning for Airborne laser scanning point clouds semantic segmentation","date":"2022-10-19","arxiv_id":"2210.10626","n_code_links":0,"syntology":null},{"paper":"/paper/qa-domain-adaptation-using-hidden-space","slug":"qa-domain-adaptation-using-hidden-space","title":"QA Domain Adaptation using Hidden Space Augmentation and Self-Supervised Contrastive Adaptation","date":"2022-10-19","arxiv_id":"2210.10861","n_code_links":1,"syntology":{"ran":12,"of":16,"n_ran_checked":8,"n_instrument":4,"unverified":4,"pointer_only":16,"phrase":"12 ran (of which 2 constructed an object rather than computing a result; 8 with no instrument failure: 5 honoured, 1 violated, 2 with no contract checked; 4 where Syntology's instrument failed) · 4 unverified","official":{"repos":["yueeeeeeee/self-supervised-qa"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":2,"n_ran_no_instrument_failure":5,"n_unverified":4,"ran_from_kinds":["official","unlocated"]}}},{"paper":null,"slug":"supervised-contrastive-learning-with-tpe","title":"Supervised Contrastive Learning with Tree-Structured Parzen Estimator Bayesian Optimization for Imbalanced Tabular Data","date":"2022-10-19","arxiv_id":"2210.10824","n_code_links":0,"syntology":null},{"paper":"/paper/uninl-aligning-representation-learning-with","slug":"uninl-aligning-representation-learning-with","title":"UniNL: Aligning Representation Learning with Scoring Function for OOD Detection via Unified Neighborhood Learning","date":"2022-10-19","arxiv_id":"2210.10722","n_code_links":1,"syntology":null},{"paper":"/paper/medclip-contrastive-learning-from-unpaired","slug":"medclip-contrastive-learning-from-unpaired","title":"MedCLIP: Contrastive Learning from Unpaired Medical Images and Text","date":"2022-10-18","arxiv_id":"2210.10163","n_code_links":1,"syntology":null},{"paper":null,"slug":"rethinking-prototypical-contrastive-learning","title":"Rethinking Prototypical Contrastive Learning through Alignment, Uniformity and Correlation","date":"2022-10-18","arxiv_id":"2210.10194","n_code_links":0,"syntology":null},{"paper":"/paper/sentiment-aware-word-and-sentence-level-pre","slug":"sentiment-aware-word-and-sentence-level-pre","title":"Sentiment-Aware Word and Sentence Level Pre-training for Sentiment Analysis","date":"2022-10-18","arxiv_id":"2210.09803","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":["xmudm/sentiwsp"],"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":"/paper/unsupervised-visualization-of-image-datasets","slug":"unsupervised-visualization-of-image-datasets","title":"Unsupervised visualization of image datasets using contrastive learning","date":"2022-10-18","arxiv_id":"2210.09879","n_code_links":1,"syntology":{"ran":30,"of":34,"n_ran_checked":18,"n_instrument":12,"unverified":4,"pointer_only":34,"phrase":"30 ran (of which 14 constructed an object rather than computing a result; 18 with no instrument failure: 0 honoured, 0 violated, 18 with no contract checked; 12 where Syntology's instrument failed) · 4 unverified","official":{"repos":["berenslab/t-simcne"],"state":"official (archive's flag): 30 ran","n_ran":30,"n_constructed":14,"n_ran_no_instrument_failure":18,"n_unverified":4,"ran_from_kinds":["official"]}}},{"paper":"/paper/correlation-between-alignment-uniformity-and","slug":"correlation-between-alignment-uniformity-and","title":"Correlation between Alignment-Uniformity and Performance of Dense Contrastive Representations","date":"2022-10-17","arxiv_id":"2210.08819","n_code_links":1,"syntology":null},{"paper":null,"slug":"hcl-tat-a-hybrid-contrastive-learning-method","title":"HCL-TAT: A Hybrid Contrastive Learning Method for Few-shot Event Detection with Task-Adaptive Threshold","date":"2022-10-17","arxiv_id":"2210.08806","n_code_links":0,"syntology":null},{"paper":null,"slug":"improving-contrastive-learning-on-visually","title":"Improving Contrastive Learning on Visually Homogeneous Mars Rover Images","date":"2022-10-17","arxiv_id":"2210.09234","n_code_links":0,"syntology":null},{"paper":"/paper/mars-semantic-aware-contrastive-learning-for","slug":"mars-semantic-aware-contrastive-learning-for","title":"Mars: Modeling Context & State Representations with Contrastive Learning for End-to-End Task-Oriented Dialog","date":"2022-10-17","arxiv_id":"2210.08917","n_code_links":1,"syntology":null},{"paper":"/paper/multiple-instance-learning-via-iterative-self","slug":"multiple-instance-learning-via-iterative-self","title":"Multiple Instance Learning via Iterative Self-Paced Supervised Contrastive Learning","date":"2022-10-17","arxiv_id":"2210.09452","n_code_links":2,"syntology":{"ran":3,"of":5,"n_ran_checked":3,"n_instrument":0,"unverified":2,"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) · 2 unverified","official":{"repos":["kangningthu/its2clr"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/supervised-prototypical-contrastive-learning","slug":"supervised-prototypical-contrastive-learning","title":"Supervised Prototypical Contrastive Learning for Emotion Recognition in Conversation","date":"2022-10-17","arxiv_id":"2210.08713","n_code_links":1,"syntology":null},{"paper":"/paper/unifying-graph-contrastive-learning-with","slug":"unifying-graph-contrastive-learning-with","title":"Unifying Graph Contrastive Learning with Flexible Contextual Scopes","date":"2022-10-17","arxiv_id":"2210.08792","n_code_links":1,"syntology":null},{"paper":"/paper/watch-the-neighbors-a-unified-k-nearest","slug":"watch-the-neighbors-a-unified-k-nearest","title":"Watch the Neighbors: A Unified K-Nearest Neighbor Contrastive Learning Framework for OOD Intent Discovery","date":"2022-10-17","arxiv_id":"2210.08909","n_code_links":1,"syntology":null},{"paper":"/paper/adaptive-contrastive-learning-with-dynamic","slug":"adaptive-contrastive-learning-with-dynamic","title":"Adaptive Contrastive Learning with Dynamic Correlation for Multi-Phase Organ Segmentation","date":"2022-10-16","arxiv_id":"2210.08652","n_code_links":1,"syntology":null},{"paper":"/paper/attention-based-audio-embeddings-for-query-by","slug":"attention-based-audio-embeddings-for-query-by","title":"Attention-Based Audio Embeddings for Query-by-Example","date":"2022-10-16","arxiv_id":"2210.08624","n_code_links":1,"syntology":null},{"paper":null,"slug":"indoor-smartphone-slam-with-learned-echoic","title":"Indoor Smartphone SLAM with Learned Echoic Location Features","date":"2022-10-16","arxiv_id":"2210.08493","n_code_links":0,"syntology":null},{"paper":null,"slug":"semantic-segmentation-with-active-semi-1","title":"Semantic Segmentation with Active Semi-Supervised Representation Learning","date":"2022-10-16","arxiv_id":"2210.08403","n_code_links":0,"syntology":null},{"paper":"/paper/towards-effective-image-manipulation","slug":"towards-effective-image-manipulation","title":"Towards Effective Image Manipulation Detection with Proposal Contrastive Learning","date":"2022-10-16","arxiv_id":"2210.08529","n_code_links":1,"syntology":null},{"paper":"/paper/augmentation-free-graph-contrastive-learning-1","slug":"augmentation-free-graph-contrastive-learning-1","title":"Augmentation-Free Graph Contrastive Learning of Invariant-Discriminative Representations","date":"2022-10-15","arxiv_id":"2210.08345","n_code_links":1,"syntology":null},{"paper":null,"slug":"improving-radiology-summarization-with","title":"Improving Radiology Summarization with Radiograph and Anatomy Prompts","date":"2022-10-15","arxiv_id":"2210.08303","n_code_links":0,"syntology":null},{"paper":"/paper/augmented-dual-contrastive-aggregation","slug":"augmented-dual-contrastive-aggregation","title":"Augmented Dual-Contrastive Aggregation Learning for Unsupervised Visible-Infrared Person Re-Identification","date":"2022-10-14","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"blind-super-resolution-for-remote-sensing","title":"Blind Super-Resolution for Remote Sensing Images via Conditional Stochastic Normalizing Flows","date":"2022-10-14","arxiv_id":"2210.07751","n_code_links":0,"syntology":null},{"paper":null,"slug":"instance-segmentation-with-cross-modal","title":"Instance Segmentation with Cross-Modal Consistency","date":"2022-10-14","arxiv_id":"2210.08113","n_code_links":0,"syntology":null},{"paper":null,"slug":"robust-preference-learning-for-storytelling","title":"Robust Preference Learning for Storytelling via Contrastive Reinforcement Learning","date":"2022-10-14","arxiv_id":"2210.07792","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-novel-supervised-contrastive-regression","title":"TractoSCR: A Novel Supervised Contrastive Regression Framework for Prediction of Neurocognitive Measures Using Multi-Site Harmonized Diffusion MRI Tractography","date":"2022-10-13","arxiv_id":"2210.07411","n_code_links":0,"syntology":null},{"paper":"/paper/closed-book-question-generation-via","slug":"closed-book-question-generation-via","title":"Closed-book Question Generation via Contrastive Learning","date":"2022-10-13","arxiv_id":"2210.06781","n_code_links":1,"syntology":null},{"paper":null,"slug":"invariance-adapted-decomposition-and-lasso","title":"Invariance-adapted decomposition and Lasso-type contrastive learning","date":"2022-10-13","arxiv_id":"2210.07413","n_code_links":0,"syntology":null},{"paper":null,"slug":"leaves-learning-views-for-time-series-data-in","title":"LEAVES: Learning Views for Time-Series Data in Contrastive Learning","date":"2022-10-13","arxiv_id":"2210.07340","n_code_links":0,"syntology":null},{"paper":"/paper/low-resource-neural-machine-translation-with","slug":"low-resource-neural-machine-translation-with","title":"Low-resource Neural Machine Translation with Cross-modal Alignment","date":"2022-10-13","arxiv_id":"2210.06716","n_code_links":1,"syntology":{"ran":1,"of":2,"n_ran_checked":1,"n_instrument":0,"unverified":1,"pointer_only":2,"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":["ictnlp/lnmt-ca"],"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":"/paper/language-agnostic-multilingual-information","slug":"language-agnostic-multilingual-information","title":"Language Agnostic Multilingual Information Retrieval with Contrastive Learning","date":"2022-10-12","arxiv_id":"2210.06633","n_code_links":1,"syntology":null},{"paper":"/paper/multi-granularity-cross-modal-alignment-for","slug":"multi-granularity-cross-modal-alignment-for","title":"Multi-Granularity Cross-modal Alignment for Generalized Medical Visual Representation Learning","date":"2022-10-12","arxiv_id":"2210.06044","n_code_links":2,"syntology":{"ran":0,"of":1,"n_ran_checked":0,"n_instrument":0,"unverified":1,"pointer_only":1,"phrase":"0 ran · 1 unverified","official":{"repos":["fuying-wang/mgca"],"state":"official: not harvested","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":[]}}},{"paper":"/paper/prepended-domain-transformer-heterogeneous","slug":"prepended-domain-transformer-heterogeneous","title":"Prepended Domain Transformer: Heterogeneous Face Recognition without Bells and Whistles","date":"2022-10-12","arxiv_id":"2210.06529","n_code_links":2,"syntology":null},{"paper":"/paper/self-attention-message-passing-for","slug":"self-attention-message-passing-for","title":"Self-Attention Message Passing for Contrastive Few-Shot Learning","date":"2022-10-12","arxiv_id":"2210.06339","n_code_links":1,"syntology":null},{"paper":null,"slug":"self-supervised-video-pretraining-yields","title":"Self-supervised video pretraining yields robust and more human-aligned visual representations","date":"2022-10-12","arxiv_id":"2210.06433","n_code_links":0,"syntology":null},{"paper":"/paper/adversarial-contrastive-learning-for-evidence","slug":"adversarial-contrastive-learning-for-evidence","title":"Adversarial Contrastive Learning for Evidence-aware Fake News Detection with Graph Neural Networks","date":"2022-10-11","arxiv_id":"2210.05498","n_code_links":1,"syntology":null},{"paper":null,"slug":"combo-pre-training-representations-of-binary","title":"Pre-Training Representations of Binary Code Using Contrastive Learning","date":"2022-10-11","arxiv_id":"2210.05102","n_code_links":0,"syntology":null},{"paper":"/paper/improving-long-tailed-object-detection-with","slug":"improving-long-tailed-object-detection-with","title":"Improving Long-tailed Object Detection with Image-Level Supervision by Multi-Task Collaborative Learning","date":"2022-10-11","arxiv_id":"2210.05568","n_code_links":1,"syntology":null},{"paper":"/paper/learning-to-locate-visual-answer-in-video","slug":"learning-to-locate-visual-answer-in-video","title":"Learning to Locate Visual Answer in Video Corpus Using Question","date":"2022-10-11","arxiv_id":"2210.05423","n_code_links":1,"syntology":null},{"paper":null,"slug":"legal-element-oriented-modeling-with-multi","title":"Legal Element-oriented Modeling with Multi-view Contrastive Learning for Legal Case Retrieval","date":"2022-10-11","arxiv_id":"2210.05188","n_code_links":0,"syntology":null},{"paper":"/paper/map-modality-agnostic-uncertainty-aware","slug":"map-modality-agnostic-uncertainty-aware","title":"MAP: Multimodal Uncertainty-Aware Vision-Language Pre-training Model","date":"2022-10-11","arxiv_id":"2210.05335","n_code_links":1,"syntology":null},{"paper":null,"slug":"vificon-vision-and-wireless-association-via","title":"ViFiCon: Vision and Wireless Association Via Self-Supervised Contrastive Learning","date":"2022-10-11","arxiv_id":"2210.05513","n_code_links":0,"syntology":null},{"paper":"/paper/contrastive-bayesian-analysis-for-deep-metric","slug":"contrastive-bayesian-analysis-for-deep-metric","title":"Contrastive Bayesian Analysis for Deep Metric Learning","date":"2022-10-10","arxiv_id":"2210.04402","n_code_links":1,"syntology":null},{"paper":"/paper/hico-hierarchical-contrastive-learning-for","slug":"hico-hierarchical-contrastive-learning-for","title":"HiCo: Hierarchical Contrastive Learning for Ultrasound Video Model Pretraining","date":"2022-10-10","arxiv_id":"2210.04477","n_code_links":1,"syntology":null},{"paper":null,"slug":"improving-continual-relation-extraction","title":"Improving Continual Relation Extraction through Prototypical Contrastive Learning","date":"2022-10-10","arxiv_id":"2210.04513","n_code_links":0,"syntology":null},{"paper":null,"slug":"learning-o-helps-for-learning-more-handling","title":"Learning \"O\" Helps for Learning More: Handling the Concealed Entity Problem for Class-incremental NER","date":"2022-10-10","arxiv_id":"2210.04676","n_code_links":0,"syntology":null},{"paper":null,"slug":"multilingual-representation-distillation-with","title":"Multilingual Representation Distillation with Contrastive Learning","date":"2022-10-10","arxiv_id":"2210.05033","n_code_links":0,"syntology":null},{"paper":"/paper/robust-diversified-graph-contrastive-network","slug":"robust-diversified-graph-contrastive-network","title":"Robust Diversified Graph Contrastive Network for Incomplete Multi-view Clustering","date":"2022-10-10","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/smile-schema-augmented-multi-level","slug":"smile-schema-augmented-multi-level","title":"SMiLE: Schema-augmented Multi-level Contrastive Learning for Knowledge Graph Link Prediction","date":"2022-10-10","arxiv_id":"2210.04870","n_code_links":1,"syntology":null},{"paper":"/paper/towards-robust-visual-question-answering","slug":"towards-robust-visual-question-answering","title":"Towards Robust Visual Question Answering: Making the Most of Biased Samples via Contrastive Learning","date":"2022-10-10","arxiv_id":"2210.04563","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":1,"n_instrument":1,"unverified":0,"pointer_only":2,"phrase":"2 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; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["phoebussi/mmbs"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official","unlocated"]}}},{"paper":null,"slug":"using-whole-slide-image-representations-from","title":"Using Whole Slide Image Representations from Self-Supervised Contrastive Learning for Melanoma Concordance Regression","date":"2022-10-10","arxiv_id":"2210.04803","n_code_links":0,"syntology":null},{"paper":"/paper/unsupervised-cross-modality-domain-adaptation-2","slug":"unsupervised-cross-modality-domain-adaptation-2","title":"Unsupervised Cross-Modality Domain Adaptation for Vestibular Schwannoma Segmentation and Koos Grade Prediction based on Semi-Supervised Contrastive Learning","date":"2022-10-09","arxiv_id":"2210.04255","n_code_links":1,"syntology":null},{"paper":"/paper/hierarchical-few-shot-object-detection","slug":"hierarchical-few-shot-object-detection","title":"Hierarchical Few-Shot Object Detection: Problem, Benchmark and Method","date":"2022-10-08","arxiv_id":"2210.03940","n_code_links":1,"syntology":null},{"paper":"/paper/infocse-information-aggregated-contrastive","slug":"infocse-information-aggregated-contrastive","title":"InfoCSE: Information-aggregated Contrastive Learning of Sentence Embeddings","date":"2022-10-08","arxiv_id":"2210.06432","n_code_links":2,"syntology":null},{"paper":"/paper/revisiting-self-supervised-contrastive","slug":"revisiting-self-supervised-contrastive","title":"Revisiting Self-Supervised Contrastive Learning for Facial Expression Recognition","date":"2022-10-08","arxiv_id":"2210.03853","n_code_links":1,"syntology":null},{"paper":"/paper/augmentations-in-hypergraph-contrastive","slug":"augmentations-in-hypergraph-contrastive","title":"Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative","date":"2022-10-07","arxiv_id":"2210.03801","n_code_links":1,"syntology":null},{"paper":null,"slug":"saicl-student-modelling-with-interaction","title":"SAICL: Student Modelling with Interaction-level Auxiliary Contrastive Tasks for Knowledge Tracing and Dropout Prediction","date":"2022-10-07","arxiv_id":"2210.09012","n_code_links":0,"syntology":null},{"paper":null,"slug":"unsupervised-semantic-representation-learning","title":"Unsupervised Semantic Representation Learning of Scientific Literature Based on Graph Attention Mechanism and Maximum Mutual Information","date":"2022-10-07","arxiv_id":"2210.03292","n_code_links":0,"syntology":null},{"paper":null,"slug":"zero-shot-stance-detection-based-on-cross","title":"Zero-shot stance detection based on cross-domain feature enhancement by contrastive learning","date":"2022-10-07","arxiv_id":"2210.03380","n_code_links":0,"syntology":null},{"paper":null,"slug":"brief-introduction-to-contrastive-learning","title":"Brief Introduction to Contrastive Learning Pretext Tasks for Visual Representation","date":"2022-10-06","arxiv_id":"2210.03163","n_code_links":0,"syntology":null},{"paper":"/paper/uncovering-the-structural-fairness-in-graph","slug":"uncovering-the-structural-fairness-in-graph","title":"Uncovering the Structural Fairness in Graph Contrastive Learning","date":"2022-10-06","arxiv_id":"2210.03011","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 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":null}}],"record_sha256":"115b1485c7b4b312732eed01a68ec247cae32ce14f7fbdcdc54aa6b612b0b920","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}