{"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/6","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":6,"pages_in_order":51,"rows_per_page":100,"rows":[501,600],"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/5","next":"/method/contrastive-learning/papers/7","papers":[{"paper":null,"slug":"accept-diagnostic-forecasting-of-battery","title":"ACCEPT: Diagnostic Forecasting of Battery Degradation Through Contrastive Learning","date":"2025-01-17","arxiv_id":"2501.10492","n_code_links":0,"syntology":null},{"paper":"/paper/airchitect-v2-learning-the-hardware","slug":"airchitect-v2-learning-the-hardware","title":"AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations","date":"2025-01-17","arxiv_id":"2501.09954","n_code_links":1,"syntology":null},{"paper":"/paper/a-simple-graph-contrastive-learning-framework","slug":"a-simple-graph-contrastive-learning-framework","title":"A Simple Graph Contrastive Learning Framework for Short Text Classification","date":"2025-01-16","arxiv_id":"2501.09219","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":["keaml-jlu/simstc"],"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/boosting-short-text-classification-with-multi","slug":"boosting-short-text-classification-with-multi","title":"Boosting Short Text Classification with Multi-Source Information Exploration and Dual-Level Contrastive Learning","date":"2025-01-16","arxiv_id":"2501.09214","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":2,"n_instrument":1,"unverified":0,"pointer_only":3,"phrase":"3 ran (of which 2 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["keaml-jlu/mi-delight"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"efficient-few-shot-medical-image-analysis-via","title":"Efficient Few-Shot Medical Image Analysis via Hierarchical Contrastive Vision-Language Learning","date":"2025-01-16","arxiv_id":"2501.09294","n_code_links":0,"syntology":null},{"paper":null,"slug":"soft-knowledge-distillation-with-multi","title":"Soft Knowledge Distillation with Multi-Dimensional Cross-Net Attention for Image Restoration Models Compression","date":"2025-01-16","arxiv_id":"2501.09321","n_code_links":0,"syntology":null},{"paper":null,"slug":"strategic-base-representation-learning-via","title":"Strategic Base Representation Learning via Feature Augmentations for Few-Shot Class Incremental Learning","date":"2025-01-16","arxiv_id":"2501.09361","n_code_links":0,"syntology":null},{"paper":"/paper/towards-robust-and-realistic-human-pose","slug":"towards-robust-and-realistic-human-pose","title":"Towards Robust and Realistic Human Pose Estimation via WiFi Signals","date":"2025-01-16","arxiv_id":"2501.09411","n_code_links":1,"syntology":null},{"paper":null,"slug":"benchmarking-robustness-of-contrastive","title":"Benchmarking Robustness of Contrastive Learning Models for Medical Image-Report Retrieval","date":"2025-01-15","arxiv_id":"2501.09134","n_code_links":0,"syntology":null},{"paper":null,"slug":"digital-phenotyping-for-adolescent-mental","title":"Digital Phenotyping for Adolescent Mental Health: A Feasibility Study Employing Machine Learning to Predict Mental Health Risk From Active and Passive Smartphone Data","date":"2025-01-15","arxiv_id":"2501.08851","n_code_links":0,"syntology":null},{"paper":null,"slug":"homophily-aware-heterogeneous-graph","title":"Homophily-aware Heterogeneous Graph Contrastive Learning","date":"2025-01-15","arxiv_id":"2501.08538","n_code_links":0,"syntology":null},{"paper":"/paper/molecular-graph-contrastive-learning-with","slug":"molecular-graph-contrastive-learning-with","title":"Molecular Graph Contrastive Learning with Line Graph","date":"2025-01-15","arxiv_id":"2501.08589","n_code_links":1,"syntology":null},{"paper":null,"slug":"shyi-action-support-for-contrastive-learning","title":"SHYI: Action Support for Contrastive Learning in High-Fidelity Text-to-Image Generation","date":"2025-01-15","arxiv_id":"2501.09055","n_code_links":0,"syntology":null},{"paper":"/paper/advancing-brainwave-based-biometrics-a-large","slug":"advancing-brainwave-based-biometrics-a-large","title":"Advancing Brainwave-Based Biometrics: A Large-Scale, Multi-Session Evaluation","date":"2025-01-14","arxiv_id":"2501.17866","n_code_links":1,"syntology":null},{"paper":null,"slug":"flavars-a-multimodal-foundational-language","title":"FLAVARS: A Multimodal Foundational Language and Vision Alignment Model for Remote Sensing","date":"2025-01-14","arxiv_id":"2501.08490","n_code_links":0,"syntology":null},{"paper":null,"slug":"accon-angle-compensated-contrastive","title":"ACCon: Angle-Compensated Contrastive Regularizer for Deep Regression","date":"2025-01-13","arxiv_id":"2501.07045","n_code_links":0,"syntology":null},{"paper":null,"slug":"code-and-pixels-multi-modal-contrastive-pre","title":"Code and Pixels: Multi-Modal Contrastive Pre-training for Enhanced Tabular Data Analysis","date":"2025-01-13","arxiv_id":"2501.07304","n_code_links":0,"syntology":null},{"paper":null,"slug":"graph-contrastive-learning-on-multi-label","title":"Graph Contrastive Learning on Multi-label Classification for Recommendations","date":"2025-01-13","arxiv_id":"2501.06985","n_code_links":0,"syntology":null},{"paper":null,"slug":"intent-interest-disentanglement-and-item","title":"Intent-Interest Disentanglement and Item-Aware Intent Contrastive Learning for Sequential Recommendation","date":"2025-01-13","arxiv_id":"2501.07096","n_code_links":0,"syntology":null},{"paper":null,"slug":"subject-representation-learning-from-eeg","title":"Subject Representation Learning from EEG using Graph Convolutional Variational Autoencoders","date":"2025-01-13","arxiv_id":"2501.16626","n_code_links":0,"syntology":null},{"paper":null,"slug":"language-inspired-relation-transfer-for-few","title":"Language-Inspired Relation Transfer for Few-shot Class-Incremental Learning","date":"2025-01-10","arxiv_id":"2501.05862","n_code_links":0,"syntology":null},{"paper":null,"slug":"fedsa-a-unified-representation-learning-via","title":"FedSA: A Unified Representation Learning via Semantic Anchors for Prototype-based Federated Learning","date":"2025-01-09","arxiv_id":"2501.05496","n_code_links":0,"syntology":null},{"paper":"/paper/focus-towards-universal-foreground","slug":"focus-towards-universal-foreground","title":"FOCUS: Towards Universal Foreground Segmentation","date":"2025-01-09","arxiv_id":"2501.05238","n_code_links":1,"syntology":null},{"paper":null,"slug":"learning-in-distribution-representations-for","title":"Learning Compact and Robust Representations for Anomaly Detection","date":"2025-01-09","arxiv_id":"2501.05130","n_code_links":0,"syntology":null},{"paper":"/paper/uncertainty-aware-knowledge-tracing","slug":"uncertainty-aware-knowledge-tracing","title":"Uncertainty-aware Knowledge Tracing","date":"2025-01-09","arxiv_id":"2501.05415","n_code_links":1,"syntology":null},{"paper":"/paper/are-they-the-same-exploring-visual","slug":"are-they-the-same-exploring-visual","title":"Are They the Same? Exploring Visual Correspondence Shortcomings of Multimodal LLMs","date":"2025-01-08","arxiv_id":"2501.04670","n_code_links":1,"syntology":null},{"paper":null,"slug":"medcodi-m-a-multi-prompt-foundation-model-for","title":"MedCoDi-M: A Multi-Prompt Foundation Model for Multimodal Medical Data Generation","date":"2025-01-08","arxiv_id":"2501.04614","n_code_links":0,"syntology":null},{"paper":null,"slug":"multimodal-graph-constrastive-learning-and","title":"Multimodal Graph Constrastive Learning and Prompt for ChartQA","date":"2025-01-08","arxiv_id":"2501.04303","n_code_links":0,"syntology":null},{"paper":"/paper/action-quality-assessment-via-hierarchical","slug":"action-quality-assessment-via-hierarchical","title":"Action Quality Assessment via Hierarchical Pose-guided Multi-stage Contrastive Regression","date":"2025-01-07","arxiv_id":"2501.03674","n_code_links":1,"syntology":null},{"paper":null,"slug":"cl3dor-contrastive-learning-for-3d-large","title":"CL3DOR: Contrastive Learning for 3D Large Multimodal Models via Odds Ratio on High-Resolution Point Clouds","date":"2025-01-07","arxiv_id":"2501.03879","n_code_links":0,"syntology":null},{"paper":"/paper/discriminative-representation-learning-via","slug":"discriminative-representation-learning-via","title":"Discriminative Representation learning via Attention-Enhanced Contrastive Learning for Short Text Clustering","date":"2025-01-07","arxiv_id":"2501.03584","n_code_links":1,"syntology":null},{"paper":"/paper/dual-level-adaptive-incongruity-enhanced","slug":"dual-level-adaptive-incongruity-enhanced","title":"Dual-level Adaptive Incongruity-enhanced Model for Multimodal Sarcasm Detection","date":"2025-01-07","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"largead-large-scale-cross-sensor-data","title":"LargeAD: Large-Scale Cross-Sensor Data Pretraining for Autonomous Driving","date":"2025-01-07","arxiv_id":"2501.04005","n_code_links":0,"syntology":null},{"paper":"/paper/taclr-a-scalable-and-efficient-retrieval","slug":"taclr-a-scalable-and-efficient-retrieval","title":"TACLR: A Scalable and Efficient Retrieval-based Method for Industrial Product Attribute Value Identification","date":"2025-01-07","arxiv_id":"2501.03835","n_code_links":1,"syntology":{"ran":1,"of":2,"n_ran_checked":1,"n_instrument":0,"unverified":1,"pointer_only":0,"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) · 1 unverified; the one sample that ran constructed an object rather than computing a result","official":null}},{"paper":"/paper/voila-complexity-aware-universal-segmentation","slug":"voila-complexity-aware-universal-segmentation","title":"VOILA: Complexity-Aware Universal Segmentation of CT images by Voxel Interacting with Language","date":"2025-01-07","arxiv_id":"2501.03482","n_code_links":1,"syntology":null},{"paper":null,"slug":"ccstereo-audio-visual-contextual-and","title":"CCStereo: Audio-Visual Contextual and Contrastive Learning for Binaural Audio Generation","date":"2025-01-06","arxiv_id":"2501.02786","n_code_links":0,"syntology":null},{"paper":null,"slug":"darkfarseer-inductive-spatio-temporal-kriging","title":"DarkFarseer: Inductive Spatio-temporal Kriging via Hidden Style Enhancement and Sparsity-Noise Mitigation","date":"2025-01-06","arxiv_id":"2501.02808","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhancing-contrastive-learning-for-retinal","title":"Enhancing Contrastive Learning for Retinal Imaging via Adjusted Augmentation Scales","date":"2025-01-05","arxiv_id":"2501.02451","n_code_links":0,"syntology":null},{"paper":"/paper/revolutionizing-encrypted-traffic","slug":"revolutionizing-encrypted-traffic","title":"Revolutionizing Encrypted Traffic Classification with MH-Net: A Multi-View Heterogeneous Graph Model","date":"2025-01-05","arxiv_id":"2501.03279","n_code_links":1,"syntology":null},{"paper":"/paper/watch-video-catch-keyword-context-aware","slug":"watch-video-catch-keyword-context-aware","title":"Watch Video, Catch Keyword: Context-aware Keyword Attention for Moment Retrieval and Highlight Detection","date":"2025-01-05","arxiv_id":"2501.02504","n_code_links":1,"syntology":{"ran":8,"of":10,"n_ran_checked":0,"n_instrument":8,"unverified":2,"pointer_only":10,"phrase":"8 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; 8 where Syntology's instrument failed) · 2 unverified","official":{"repos":["visualaikhu/keyword-detr"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"few-shot-implicit-function-generation-via","title":"Few-shot Implicit Function Generation via Equivariance","date":"2025-01-03","arxiv_id":"2501.01601","n_code_links":0,"syntology":null},{"paper":null,"slug":"from-age-estimation-to-age-invariant-face","title":"From Age Estimation to Age-Invariant Face Recognition: Generalized Age Feature Extraction Using Order-Enhanced Contrastive Learning","date":"2025-01-03","arxiv_id":"2501.01760","n_code_links":0,"syntology":null},{"paper":"/paper/madgen-mass-spec-attends-to-de-novo-molecular","slug":"madgen-mass-spec-attends-to-de-novo-molecular","title":"MADGEN: Mass-Spec attends to De Novo Molecular generation","date":"2025-01-03","arxiv_id":"2501.01950","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":0,"n_instrument":2,"unverified":0,"pointer_only":0,"phrase":"2 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; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["HassounLab/MADGEN"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/multimodal-contrastive-representation","slug":"multimodal-contrastive-representation","title":"Multimodal Contrastive Representation Learning in Augmented Biomedical Knowledge Graphs","date":"2025-01-03","arxiv_id":"2501.01644","n_code_links":1,"syntology":null},{"paper":"/paper/social-relation-meets-recommendation","slug":"social-relation-meets-recommendation","title":"Contrastive Learning Augmented Social Recommendations","date":"2025-01-03","arxiv_id":"2502.15695","n_code_links":1,"syntology":null},{"paper":"/paper/adacrossnet-adaptive-dynamic-loss-weighting","slug":"adacrossnet-adaptive-dynamic-loss-weighting","title":"AdaCrossNet: Adaptive Dynamic Loss Weighting for Cross-Modal Contrastive Point Cloud Learning","date":"2025-01-02","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"an-inclusive-theoretical-framework-of-robust","title":"An Inclusive Theoretical Framework of Robust Supervised Contrastive Loss against Label Noise","date":"2025-01-02","arxiv_id":"2501.01130","n_code_links":0,"syntology":null},{"paper":null,"slug":"contrastive-learning-from-exploratory-actions","title":"Contrastive Learning from Exploratory Actions: Leveraging Natural Interactions for Preference Elicitation","date":"2025-01-02","arxiv_id":"2501.01367","n_code_links":0,"syntology":null},{"paper":null,"slug":"understanding-difficult-to-learn-examples-in","title":"Understanding Difficult-to-learn Examples in Contrastive Learning: A Theoretical Framework for Spectral Contrastive Learning","date":"2025-01-02","arxiv_id":"2501.01317","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-tale-of-two-classes-adapting-supervised","title":"A Tale of Two Classes: Adapting Supervised Contrastive Learning to Binary Imbalanced Datasets","date":"2025-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"adapting-to-observation-length-of-trajectory","title":"Adapting to Observation Length of Trajectory Prediction via Contrastive Learning","date":"2025-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"alignment-mining-and-fusion-representation","title":"Alignment, Mining and Fusion: Representation Alignment with Hard Negative Mining and Selective Knowledge Fusion for Medical Visual Question Answering","date":"2025-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"bringing-clip-to-the-clinic-dynamic-soft","title":"Bringing CLIP to the Clinic: Dynamic Soft Labels and Negation-Aware Learning for Medical Analysis","date":"2025-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"cloc-contrastive-learning-for-ordinal","title":"CLOC: Contrastive Learning for Ordinal Classification with Multi-Margin N-pair Loss","date":"2025-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"dycon-dynamic-uncertainty-aware-consistency","title":"DyCON: Dynamic Uncertainty-aware Consistency and Contrastive Learning for Semi-supervised Medical Image Segmentation","date":"2025-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"dynamic-stereotype-theory-induced-micro","title":"Dynamic Stereotype Theory Induced Micro-expression Recognition with Oriented Deformation","date":"2025-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"easemvc-efficient-dual-selection-mechanism","title":"EASEMVC:Efficient Dual Selection Mechanism for Deep Multi-View Clustering","date":"2025-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"foley-flow-coordinated-video-to-audio","title":"Foley-Flow: Coordinated Video-to-Audio Generation with Masked Audio-Visual Alignment and Dynamic Conditional Flows","date":"2025-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"incorporating-dense-knowledge-alignment-into","title":"Incorporating Dense Knowledge Alignment into Unified Multimodal Representation Models","date":"2025-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"less-attention-is-more-prompt-transformer-for","title":"Less Attention is More: Prompt Transformer for Generalized Category Discovery","date":"2025-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"link-based-contrastive-learning-for-one-shot","title":"Link-based Contrastive Learning for One-Shot Unsupervised Domain Adaptation","date":"2025-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-modal-contrastive-learning-with","title":"Multi-modal Contrastive Learning with Negative Sampling Calibration for Phenotypic Drug Discovery","date":"2025-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-modal-contrastive-masked-autoencoders-a","title":"Multi-Modal Contrastive Masked Autoencoders: A Two-Stage Progressive Pre-training Approach for RGBD Datasets","date":"2025-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"oda-gan-orthogonal-decoupling-alignment-gan","title":"ODA-GAN: Orthogonal Decoupling Alignment GAN Assisted by Weakly-supervised Learning for Virtual Immunohistochemistry Staining","date":"2025-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/relation3d-enhancing-relation-modeling-for","slug":"relation3d-enhancing-relation-modeling-for","title":"Relation3D : Enhancing Relation Modeling for Point Cloud Instance Segmentation","date":"2025-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"revisiting-graph-neural-networks-on-graph","title":"Revisiting Graph Neural Networks on Graph-level Tasks: Comprehensive Experiments, Analysis, and Improvements","date":"2025-01-01","arxiv_id":"2501.00773","n_code_links":0,"syntology":null},{"paper":null,"slug":"roll-robust-noisy-pseudo-label-learning-for","title":"ROLL: Robust Noisy Pseudo-label Learning for Multi-View Clustering with Noisy Correspondence","date":"2025-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"self-supervised-controlnet-with-spatio","title":"Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution","date":"2025-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"ske-layout-spatial-knowledge-enhanced-layout","title":"SKE-Layout: Spatial Knowledge Enhanced Layout Generation with LLMs","date":"2025-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"slade-shielding-against-dual-exploits-in","title":"SLADE: Shielding against Dual Exploits in Large Vision-Language Models","date":"2025-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"umfn-unified-multi-domain-face-normalization","title":"UMFN: Unified Multi-Domain Face Normalization for Joint Cross-domain Prototype Learning and Heterogeneous Face Recognition","date":"2025-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"v-2dial-unification-of-video-and-visual","title":"V^2Dial: Unification of Video and Visual Dialog via Multimodal Experts","date":"2025-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"viewpoint-rosetta-stone-unlocking-unpaired","title":"Viewpoint Rosetta Stone: Unlocking Unpaired Ego-Exo Videos for View-invariant Representation Learning","date":"2025-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"make-domain-shift-a-catastrophic-forgetting","title":"Make Domain Shift a Catastrophic Forgetting Alleviator in Class-Incremental Learning","date":"2024-12-31","arxiv_id":"2501.00237","n_code_links":0,"syntology":null},{"paper":"/paper/frequency-masked-embedding-inference-a-non","slug":"frequency-masked-embedding-inference-a-non","title":"Frequency-Masked Embedding Inference: A Non-Contrastive Approach for Time Series Representation Learning","date":"2024-12-30","arxiv_id":"2412.20790","n_code_links":1,"syntology":null},{"paper":null,"slug":"phoneme-level-contrastive-learning-for-user","title":"Phoneme-Level Contrastive Learning for User-Defined Keyword Spotting with Flexible Enrollment","date":"2024-12-30","arxiv_id":"2412.20805","n_code_links":0,"syntology":null},{"paper":null,"slug":"defending-multimodal-backdoored-models-by","title":"Defending Multimodal Backdoored Models by Repulsive Visual Prompt Tuning","date":"2024-12-29","arxiv_id":"2412.20392","n_code_links":0,"syntology":null},{"paper":null,"slug":"injecting-explainability-and-lightweight","title":"Injecting Explainability and Lightweight Design into Weakly Supervised Video Anomaly Detection Systems","date":"2024-12-28","arxiv_id":"2412.20201","n_code_links":0,"syntology":null},{"paper":null,"slug":"self-calibrated-dual-contrasting-for","title":"Self-Calibrated Dual Contrasting for Annotation-Efficient Bacteria Raman Spectroscopy Clustering and Classification","date":"2024-12-28","arxiv_id":"2412.20060","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhancing-adversarial-robustness-of-deep","title":"Enhancing Adversarial Robustness of Deep Neural Networks Through Supervised Contrastive Learning","date":"2024-12-27","arxiv_id":"2412.19747","n_code_links":0,"syntology":null},{"paper":null,"slug":"neighbor-does-matter-density-aware","title":"Neighbor Does Matter: Density-Aware Contrastive Learning for Medical Semi-supervised Segmentation","date":"2024-12-27","arxiv_id":"2412.19871","n_code_links":0,"syntology":null},{"paper":null,"slug":"extended-cross-modality-united-learning-for","title":"Extended Cross-Modality United Learning for Unsupervised Visible-Infrared Person Re-identification","date":"2024-12-26","arxiv_id":"2412.19134","n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-view-fake-news-detection-model-based-on","title":"Multi-view Fake News Detection Model Based on Dynamic Hypergraph","date":"2024-12-26","arxiv_id":"2412.19227","n_code_links":0,"syntology":null},{"paper":"/paper/contrastive-representation-for-interactive","slug":"contrastive-representation-for-interactive","title":"Contrastive Representation for Interactive Recommendation","date":"2024-12-24","arxiv_id":"2412.18396","n_code_links":1,"syntology":null},{"paper":null,"slug":"fedvck-non-iid-robust-and-communication","title":"FedVCK: Non-IID Robust and Communication-Efficient Federated Learning via Valuable Condensed Knowledge for Medical Image Analysis","date":"2024-12-24","arxiv_id":"2412.18557","n_code_links":0,"syntology":null},{"paper":null,"slug":"text-driven-tumor-synthesis","title":"Text-Driven Tumor Synthesis","date":"2024-12-24","arxiv_id":"2412.18589","n_code_links":0,"syntology":null},{"paper":"/paper/efficient-fine-tuning-methodology-of-text","slug":"efficient-fine-tuning-methodology-of-text","title":"Efficient fine-tuning methodology of text embedding models for information retrieval: contrastive learning penalty (clp)","date":"2024-12-23","arxiv_id":"2412.17364","n_code_links":1,"syntology":null},{"paper":null,"slug":"enhancing-topic-interpretability-for-neural","title":"Enhancing Topic Interpretability for Neural Topic Modeling through Topic-wise Contrastive Learning","date":"2024-12-23","arxiv_id":"2412.17338","n_code_links":0,"syntology":null},{"paper":null,"slug":"multiple-consistency-guided-test-time","title":"Multiple Consistency-guided Test-Time Adaptation for Contrastive Audio-Language Models with Unlabeled Audio","date":"2024-12-23","arxiv_id":"2412.17306","n_code_links":0,"syntology":null},{"paper":null,"slug":"dcor-anomaly-detection-in-attributed-networks","title":"DCOR: Anomaly Detection in Attributed Networks via Dual Contrastive Learning Reconstruction","date":"2024-12-21","arxiv_id":"2412.16788","n_code_links":0,"syntology":null},{"paper":"/paper/enhancing-contrastive-learning-inspired-by","slug":"enhancing-contrastive-learning-inspired-by","title":"Enhancing Contrastive Learning Inspired by the Philosophy of \"The Blind Men and the Elephant\"","date":"2024-12-21","arxiv_id":"2412.16522","n_code_links":1,"syntology":null},{"paper":null,"slug":"fairdd-enhancing-fairness-with-domain","title":"FairDD: Enhancing Fairness with domain-incremental learning in dermatological disease diagnosis","date":"2024-12-21","arxiv_id":"2412.16542","n_code_links":0,"syntology":null},{"paper":"/paper/trusted-mamba-contrastive-network-for-multi","slug":"trusted-mamba-contrastive-network-for-multi","title":"Trusted Mamba Contrastive Network for Multi-View Clustering","date":"2024-12-21","arxiv_id":"2412.16487","n_code_links":1,"syntology":null},{"paper":"/paper/contrastive-learning-for-task-independent","slug":"contrastive-learning-for-task-independent","title":"Contrastive Learning for Task-Independent SpeechLLM-Pretraining","date":"2024-12-20","arxiv_id":"2412.15712","n_code_links":1,"syntology":null},{"paper":null,"slug":"graph-structure-refinement-with-energy-based","title":"Graph Structure Refinement with Energy-based Contrastive Learning","date":"2024-12-20","arxiv_id":"2412.17856","n_code_links":0,"syntology":null},{"paper":"/paper/personalized-representation-from-personalized","slug":"personalized-representation-from-personalized","title":"Personalized Representation from Personalized Generation","date":"2024-12-20","arxiv_id":"2412.16156","n_code_links":1,"syntology":{"ran":10,"of":15,"n_ran_checked":9,"n_instrument":1,"unverified":5,"pointer_only":1,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 1 where Syntology's instrument failed) · 5 unverified","official":{"repos":["ssundaram21/personalized-rep"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":5,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"saliencyi2ploc-saliency-guided-image-point","title":"SaliencyI2PLoc: saliency-guided image-point cloud localization using contrastive learning","date":"2024-12-20","arxiv_id":"2412.15577","n_code_links":0,"syntology":null},{"paper":null,"slug":"sgac-a-graph-neural-network-framework-for","title":"SGAC: A Graph Neural Network Framework for Imbalanced and Structure-Aware AMP Classification","date":"2024-12-20","arxiv_id":"2412.16276","n_code_links":0,"syntology":null},{"paper":null,"slug":"balanced-gradient-sample-retrieval-for","title":"Balanced Gradient Sample Retrieval for Enhanced Knowledge Retention in Proxy-based Continual Learning","date":"2024-12-19","arxiv_id":"2412.14430","n_code_links":0,"syntology":null},{"paper":"/paper/defeasible-visual-entailment-benchmark","slug":"defeasible-visual-entailment-benchmark","title":"Defeasible Visual Entailment: Benchmark, Evaluator, and Reward-Driven Optimization","date":"2024-12-19","arxiv_id":"2412.16232","n_code_links":1,"syntology":null}],"record_sha256":"e01a538c59d99d594c9b3c6a637a68d9248a21c58df2e8ead33fe7285d4f0f46","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}