contrastive learning - Robuta Search

https://openreview.net/forum?id=KmykpuSrjcq Prototypical Contrastive Learning of Unsupervised Representations | OpenReview This paper presents Prototypical Contrastive Learning (PCL), an unsupervised representation learning method that bridges contrastive learning with clustering.... contrastive learning prototypical unsupervised representations openreview https://deepai.org/publication/end-to-end-supervised-multilabel-contrastive-learning End-to-End Supervised Multilabel Contrastive Learning | DeepAI Jul 8, 2023 - 07/08/23 - Multilabel representation learning is recognized as a challenging problem that can be associated with either label dependencies be... contrastive learning end supervised deepai https://openreview.net/forum?id=ioyq7NsR1KJ Adversarial Graph Augmentation to Improve Graph Contrastive Learning | OpenReview Adversarial training to learn augmentation strategies for better self-supervised graph representations. contrastive learning adversarial graph augmentation improve https://openreview.net/forum?id=LcSfRundgwI A Contrastive Learning Approach for Training Variational Autoencoder Priors | OpenReview We propose using energy-based prior, trained with noise contrastive estimation to tackle the prior hole problem in VAEs contrastive learning for training variational autoencoder approach priors https://arxiv.org/abs/2112.08679 [2112.08679] Are Graph Augmentations Necessary? Simple Graph Contrastive Learning for Recommendation Abstract page for arXiv paper 2112.08679: Are Graph Augmentations Necessary? Simple Graph Contrastive Learning for Recommendation contrastive learning graph augmentations https://deepai.org/publication/hard-negative-mixing-for-contrastive-learning Hard Negative Mixing for Contrastive Learning | DeepAI Oct 2, 2020 - 10/02/20 - Contrastive learning has become a key component of self-supervised learning approaches for computer vision. By learning to embed t... contrastive learning hard negative mixing deepai https://openreview.net/forum?id=CR1XOQ0UTh- Contrastive Learning with Hard Negative Samples | OpenReview We consider the question: how can you sample good negative examples for contrastive learning? We argue that, as with metric learning, learning contrastive... contrastive learning hard negative samples openreview https://openreview.net/forum?id=YIcb3pR8ld Contrastive Learning Meets Homophily: Two Birds with One Stone | OpenReview Graph Contrastive Learning (GCL) has recently enjoyed great success as an efficient self-supervised representation learning approach. However, the existing... contrastive learning two birds one stone meets openreview https://openreview.net/forum?id=SEef8wIj5lc The Optimal Noise in Noise-Contrastive Learning Is Not What You Think | OpenReview We exhibit the optimal noise for Noise-Contrastive Estimation. what you think contrastive learning https://openreview.net/forum?id=ijzm0EhAY_w Expectation-Maximization Contrastive Learning for Compact Video-and-Language Representations |... We propose Expectation-Maximization Contrastive Learning (EMCL) to learn compact video-and language representations. contrastive learning expectation maximization compact video https://openreview.net/forum?id=tfEylAl8vf FFCL: Forward-Forward Contrastive Learning for Improved Medical Image Classification | OpenReview We present a multistage (local, global) forward-forward contrastive pretraining strategy for state-of-the-art models demonstrating improved performance on... contrastive learning image classification forward improved medical https://deepai.org/publication/interpretable-contrastive-learning-for-networks Interpretable Contrastive Learning for Networks | DeepAI May 25, 2020 - 05/25/20 - Contrastive learning (CL) is an emerging analysis approach that aims to discover unique patterns in one dataset relative to anothe... contrastive learning for networks deepai https://openreview.net/forum?id=2XoCArKGj1&referrer=%5Bthe%20profile%20of%20Collin%20Stultz%5D(%2Fprofile%3Fid%3D~Collin_Stultz1) Event-Based Contrastive Learning for Medical Time Series | OpenReview In clinical practice, one often needs to identify whether a patient is at high risk of adverse outcomes after some key medical event; e.g., the short-term risk... event based contrastive learning for medical time series openreview https://www.amazon.science/publications/vision-language-pre-training-with-triple-contrastive-learning Vision-language pre-training with triple contrastive learning - Amazon Science Vision-language representation learning largely benefits from image-text alignment through contrastive losses (e.g., InfoNCE loss). The success of this... pre training contrastive learning vision language triple https://www.amazon.science/tag/contrastive-learning Contrastive learning - Amazon Science contrastive learning amazon science https://openreview.net/forum?id=k2uUeLCrQq RelCon: Relative Contrastive Learning for a Motion Foundation Model for Wearable Data | OpenReview We present RelCon, a novel self-supervised Relative Contrastive learning approach for training a motion foundation model from wearable accelerometry sensors.... contrastive learning https://openreview.net/forum?id=lVE1VeGQwg Manifold Contrastive Learning with Variational Lie Group Operators | OpenReview Self-supervised learning of deep neural networks has become a prevalent paradigm for learning representations that transfer to a variety of downstream tasks.... contrastive learning manifold lie group operators https://openreview.net/forum?id=Ph5cJSfD2XN Unbiased Supervised Contrastive Learning | OpenReview We introduce FairKL, a debiasing regularization technique along with a metric learning theoretical framework and a novel formulation of the supervised... contrastive learning unbiased supervised openreview https://aclanthology.org/2023.findings-acl.707/ Improving Contrastive Learning of Sentence Embeddings from AI Feedback - ACL Anthology Qinyuan Cheng, Xiaogui Yang, Tianxiang Sun, Linyang Li, Xipeng Qiu. Findings of the Association for Computational Linguistics: ACL 2023. 2023. contrastive learning ai feedback improving sentence https://openreview.net/forum?id=Gg7cXo3S8l Dictionary Contrastive Learning for Efficient Local Supervision without Auxiliary Networks |... While backpropagation (BP) has achieved widespread success in deep learning, it faces two prominent challenges: computational inefficiency and biological... contrastive learning dictionary efficient local supervision https://openreview.net/forum?id=NeQYi56MFj&referrer=%5Bthe%20profile%20of%20Raghav%20Singhal%5D(%2Fprofile%3Fid%3D~Raghav_Singhal2) M3CoL: Harnessing Shared Relations via Multimodal Mixup Contrastive Learning for Multimodal... Deep multimodal learning has shown remarkable success by leveraging contrastive learning to capture explicit one-to-one relations across modalities. However,... contrastive learning shared relations via multimodal https://www.iac.es/en/science-and-technology/publications/leveraging-movement-representation-contrastive-learning-asteroid-detection Leveraging Movement Representation from Contrastive Learning for Asteroid Detection | Instituto de... To support asteroid-related studies, current motion detectors are utilized to select moving object candidates based on their visualizations and movements in... contrastive learning leveraging movement representation https://deepai.org/publication/generalized-parametric-contrastive-learning Generalized Parametric Contrastive Learning | DeepAI Sep 26, 2022 - 09/26/22 - In this paper, we propose the Generalized Parametric Contrastive Learning (GPaCo/PaCo) which works well on both imbalanced and bal... contrastive learning generalized parametric deepai https://www.frontiersin.org/journals/neurorobotics/articles/10.3389/fnbot.2024.1428785/full Frontiers | Multi-granularity contrastive learning model for next POI recommendation Next Point-of-Interest (POI) recommendation aims to predict the next POI for users from their historical activities. Existing methods typically rely on locat... contrastive learning frontiers multi granularity model https://www.easychair.org/publications/preprint/VsWZ Hybrid Contrastive Learning with Cluster Ensemble for Unsupervised Person Re-Identification contrastive learning hybrid cluster https://deepai.org/publication/supervised-contrastive-learning-for-recommendation Supervised Contrastive Learning for Recommendation | DeepAI Jan 10, 2022 - 01/10/22 - Compared with the traditional collaborative filtering methods, the graph convolution network can explicitly model the interaction ... contrastive learning supervised recommendation deepai https://openreview.net/forum?id=u6FuiKzT1K Leveraging Contrastive Learning for Enhanced Node Representations in Tokenized Graph Transformers |... While tokenized graph Transformers have demonstrated strong performance in node classification tasks, their reliance on a limited subset of nodes with high... contrastive learning leveraging enhanced https://openreview.net/forum?id=_hszZbt46bT Anomaly Detection for Tabular Data with Internal Contrastive Learning | OpenReview We consider the task of finding out-of-class samples in tabular data, where little can be assumed on the structure of the data. In order to capture the... anomaly detection tabular data contrastive learning internal openreview https://jmlr.org/papers/v27/25-0376.html A Data-Augmented Contrastive Learning Approach to Nonparametric Density Estimation contrastive learning data augmented approach density https://www.simplilearn.com/contrastive-learning-article Contrastive Learning: Key Principles and Applications Mar 15, 2026 - Contrastive learning extracts meaningful representations by contrasting positive and negative pairs, helping models group similar instances and separate... contrastive learning key principles applications https://arxiv.org/abs/2101.06983v2 [2101.06983v2] Scaling Deep Contrastive Learning Batch Size under Memory Limited Setup Abstract page for arXiv paper 2101.06983v2: Scaling Deep Contrastive Learning Batch Size under Memory Limited Setup scaling deep contrastive learning https://www.mdpi.com/2072-4292/13/15/2893 Large-Scale River Mapping Using Contrastive Learning and Multi-Source Satellite Imagery River system is critical for the future sustainability of our planet but is always under the pressure of food, water and energy demands. Recent advances in... large scale contrastive learning https://aclanthology.org/2023.findings-emnlp.883/ IMU2CLIP: Language-grounded Motion Sensor Translation with Multimodal Contrastive Learning - ACL... Seungwhan Moon, Andrea Madotto, Zhaojiang Lin, Aparajita Saraf, Amy Bearman, Babak Damavandi. Findings of the Association for Computational Linguistics: EMNLP... motion sensor contrastive learning language grounded https://openreview.net/forum?id=Bvrc6kobWd&referrer=%5Bthe%20profile%20of%20Daniel%20Rho%5D(%2Fprofile%3Fid%3D~Daniel_Rho1) Understanding Contrastive Learning Through the Lens of Margins | OpenReview Contrastive learning, along with its variations, has been a highly effective self-supervised learning method across diverse domains. Contrastive learning... through the lens of contrastive learning understanding margins openreview https://openreview.net/forum?id=gqjT7g5ZRa&referrer=%5Bthe%20profile%20of%20Catherine%20Ji%5D(%2Fprofile%3Fid%3D~Catherine_Ji1) Curiosity-Driven Exploration via Temporal Contrastive Learning | OpenReview Effective exploration in reinforcement learning requires not only tracking where an agent has been, but also understanding how the agent perceives and... contrastive learning curiosity driven exploration via https://openreview.net/forum?id=1ODSsnoMBav CLDA: Contrastive Learning for Semi-Supervised Domain Adaptation | OpenReview A Novel Contrastive Learning approach for Semi-Supervised Domain Adaptation contrastive learning domain adaptation semi supervised openreview https://openreview.net/forum?id=p32U4ulksI SEGA: Structural Entropy Guided Anchor View for Graph Contrastive Learning | OpenReview In contrastive learning, the choice of "view" controls the information that the representation captures and influences the performance of the model. However,... view for contrastive learning sega structural entropy https://openreview.net/forum?id=BgjLy3chju&referrer=%5Bthe%20profile%20of%20Junru%20Zhang%5D(%2Fprofile%3Fid%3D~Junru_Zhang1) Multi-view Self-Supervised Contrastive Learning for Multivariate Time Series | OpenReview Learning semantic-rich representations from unlabeled time series data with intricate dynamics is a notable challenge. Traditional contrastive learning... multi view contrastive learning time series self supervised https://sparsecl.github.io/ SPARSECL: Sparse Contrastive Learning for Contradiction Retrieval Deformable Neural Radiance Fields creates free-viewpoint portraits (nerfies) from casually captured videos. contrastive learning sparse contradiction retrieval https://deepai.org/publication/contrastive-learning-of-emoji-based-representations-for-resource-poor-languages Contrastive Learning of Emoji-based Representations for Resource-Poor Languages | DeepAI Apr 3, 2018 - 04/03/18 - The introduction of emojis (or emoticons) in social media platforms has given the users an increased potential for expression. We ... contrastive learning emoji based https://arxiv.org/abs/2112.00847v2 [2112.00847v2] CLAWS: Contrastive Learning with hard Attention and Weak Supervision Abstract page for arXiv paper 2112.00847v2: CLAWS: Contrastive Learning with hard Attention and Weak Supervision contrastive learning claws https://aclanthology.org/2022.acl-long.216/ Improving Event Representation via Simultaneous Weakly Supervised Contrastive Learning and... Jun Gao, Wei Wang, Changlong Yu, Huan Zhao, Wilfred Ng, Ruifeng Xu. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics... contrastive learning improving event representation via https://openreview.net/forum?id=H4VuVGUSoV&referrer=%5Bthe%20profile%20of%20Yusuf%20Dalva%5D(%2Fprofile%3Fid%3D~Yusuf_Dalva1) NoiseCLR: A Contrastive Learning Approach for Unsupervised Discovery of Interpretable Directions in... Generative models have been very popular in the recent years for their image generation capabilities. GAN-based models are highly regarded for their... contrastive learning https://openreview.net/forum?id=zEHGSN8Hy8 SetCSE: Set Operations using Contrastive Learning of Sentence Embeddings | OpenReview Taking inspiration from Set Theory, we introduce SetCSE, an innovative information retrieval framework. SetCSE employs sets to represent complex semantics and... set operations contrastive learning using sentence embeddings https://openreview.net/forum?id=nBCuRzjqK7 Self-Supervised Contrastive Learning for Long-term Forecasting | OpenReview Long-term forecasting presents unique challenges due to the time and memory complexity of handling long sequences. Existing methods, which rely on sliding... contrastive learning long term self supervised forecasting https://deepai.org/publication/contrareg-contrastive-learning-of-multi-modality-unsupervised-deformable-image-registration ContraReg: Contrastive Learning of Multi-modality Unsupervised Deformable Image Registration |... Jun 27, 2022 - 06/27/22 - Establishing voxelwise semantic correspondence across distinct imaging modalities is a foundational yet formidable computer vision... contrastive learning multi modality unsupervised image https://openreview.net/forum?id=bF0Qsser5noO Graph Contrastive Learning with Cross-view Reconstruction | OpenReview Our paper propose a new contrastive learning framework to learn graph representation in accordance with the information bottleneck principle. contrastive learning graph cross view reconstruction https://openreview.net/forum?id=S-sYYe0P0Hd&referrer=%5Bthe%20profile%20of%20Dan%20Su%5D(%2Fprofile%3Fid%3D~Dan_Su3) SynCLR: A Synthesis Framework for Contrastive Learning of out-of-domain Speech Representations |... Learning generalizable speech representations for unseen samples in different domains has been a challenge with ever increasing importance to date. Although... contrastive learning https://deepai.org/publication/cl-xabsa-contrastive-learning-for-cross-lingual-aspect-based-sentiment-analysis CL-XABSA: Contrastive Learning for Cross-lingual Aspect-based Sentiment Analysis | DeepAI Apr 2, 2022 - 04/02/22 - As an extensive research in the field of Natural language processing (NLP), aspect-based sentiment analysis (ABSA) is the task of ... contrastive learning https://openreview.net/forum?id=ONfWFluZBI Self-supervised contrastive learning performs non-linear system identification | OpenReview Self-supervised learning (SSL) approaches have brought tremendous success across many tasks and domains. It has been argued that these successes can be... contrastive learning linear system self supervised performs https://openreview.net/forum?id=bSC_xo8VQ1b Contrastive Learning of Electrodermal Activity Representations for Stress Detection | OpenReview We design contrastive learning methods that are tailored to Electrodermal Activity (EDA) data, and examine how they perform on the downstream task of stress... contrastive learning for stress activity representations detection https://arxiv.org/abs/2506.15304 [2506.15304] ConLID: Supervised Contrastive Learning for Low-Resource Language Identification Abstract page for arXiv paper 2506.15304: ConLID: Supervised Contrastive Learning for Low-Resource Language Identification contrastive learning supervised https://deepai.org/publication/identifiability-results-for-multimodal-contrastive-learning Identifiability Results for Multimodal Contrastive Learning | DeepAI Mar 16, 2023 - 03/16/23 - Contrastive learning is a cornerstone underlying recent progress in multi-view and multimodal learning, e.g., in representation le... contrastive learning results multimodal deepai https://deepai.org/publication/supporting-analysis-of-dimensionality-reduction-results-with-contrastive-learning Supporting Analysis of Dimensionality Reduction Results with Contrastive Learning | DeepAI May 10, 2019 - 05/10/19 - Dimensionality reduction (DR) is frequently used for analyzing and visualizing high-dimensional data as it provides a good first g... dimensionality reduction contrastive learning supporting analysis results https://arxiv.org/abs/2206.01646 [2206.01646] Integrating Prior Knowledge in Contrastive Learning with Kernel Abstract page for arXiv paper 2206.01646: Integrating Prior Knowledge in Contrastive Learning with Kernel prior knowledge contrastive learning integrating kernel https://openreview.net/forum?id=0YeJyvv2rO MCGC: an MLP-based supervised Contrastive learning framework for Graph Classification | OpenReview Graph Neural Networks (GNNs) have been widely used for tasks involving graph-structured data. These networks create matrix representations of graphs by... contrastive learning https://openreview.net/forum?id=DMuNu28WQA Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift |... Self-training and contrastive learning have emerged as leading techniques for incorporating unlabeled data, both under distribution shift (unsupervised domain... benefits of contrastive learning self training complementary https://oecd.ai/en/catalogue/metric-use-cases/exploring-localization-for-self-supervised-fine-grained-contrastive-learning Exploring Localization for Self-supervised Fine-grained Contrastive Learning - OECD.AI Semi-supervised object detection (SSOD) has made significant progress with the development of pseudo-label-based end-to-end methods. However, many of these... contrastive learning exploring localization self supervised https://www.frontiersin.org/journals/physics/articles/10.3389/fphy.2024.1336795/full Frontiers | A dual contrastive learning-based graph convolutional network with syntax label... Aspect-based sentiment classification is a fine-grained sentiment classification task. State-of-the-art approaches in this field leverage graph neural networ... contrastive learning https://openreview.net/forum?id=B8a1FcY0vi From $t$-SNE to UMAP with contrastive learning | OpenReview We show that UMAP is effectively negative sampling applied to the t-SNE loss function. from t contrastive learning sne umap openreview https://arxiv.org/abs/2503.20839 [2503.20839] TAR: Teacher-Aligned Representations via Contrastive Learning for Quadrupedal... Abstract page for arXiv paper 2503.20839: TAR: Teacher-Aligned Representations via Contrastive Learning for Quadrupedal Locomotion contrastive learning tar teacher aligned https://openreview.net/forum?id=2m3AGIPhvjX Imitation from Observation With Bootstrapped Contrastive Learning | OpenReview Imitation from observation algorithm to train agents to perform tasks using only a limited number of pixel-based expert observations and based on a behavioral... contrastive learning imitation observation bootstrapped openreview https://aclanthology.org/2023.acl-long.339/ miCSE: Mutual Information Contrastive Learning for Low-shot Sentence Embeddings - ACL Anthology Tassilo Klein, Moin Nabi. Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2023. mutual information contrastive learning https://openreview.net/forum?id=6nKjdEHDDU&referrer=%5Bthe%20profile%20of%20Xiao%20Wang%5D(%2Fprofile%3Fid%3D~Xiao_Wang5) Three Towers: Flexible Contrastive Learning with Pretrained Image Models | OpenReview We introduce Three Towers (3T), a flexible method to improve the contrastive learning of vision-language models by incorporating pretrained image classifiers.... contrastive learning image models three towers flexible https://aclanthology.org/2023.acl-long.216/ WACO: Word-Aligned Contrastive Learning for Speech Translation - ACL Anthology Siqi Ouyang, Rong Ye, Lei Li. Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2023. word aligned contrastive learning speech translation waco acl https://huggingface.co/papers/2502.03664 Paper page - Contrastive Learning for Cold Start Recommendation with Adaptive Feature Fusion Join the discussion on this paper page paper page contrastive learning cold start https://www.easychair.org/publications/preprint/QlBs ITCONTRAST: Contrastive Learning with Hard Negative Synthesis for Image-Text Matching contrastive learning for image hard https://openreview.net/forum?id=RdWt-VDPZEG Compressed Video Contrastive Learning | OpenReview We propose an efficient and effective framework for self-supervised representation learning from compressed videos (without decompressing off-the-fly). contrastive learning compressed video openreview https://openreview.net/forum?id=5tjdRyqnSn PhiNets: Brain-inspired Non-contrastive Learning Based on Temporal Prediction Hypothesis |... Predictive coding has been established as a promising neuroscientific theory to describe the mechanism of information processing in the retina or cortex. This... brain inspired contrastive learning non https://aclanthology.org/2021.repl4nlp-1.31/ Scaling Deep Contrastive Learning Batch Size under Memory Limited Setup - ACL Anthology Luyu Gao, Yunyi Zhang, Jiawei Han, Jamie Callan. Proceedings of the 6th Workshop on Representation Learning for NLP (RepL4NLP-2021). 2021. scaling deep contrastive learning batch size https://openreview.net/forum?id=6LJvlAiD9z ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and... Deep neural networks (DNN) have shown great capacity of modeling a dynamical system; nevertheless, they usually do not obey physics constraints such as... contrastive learning https://aclanthology.org/2021.findings-emnlp.208/ Attention-based Contrastive Learning for Winograd Schemas - ACL Anthology Tassilo Klein, Moin Nabi. Findings of the Association for Computational Linguistics: EMNLP 2021. 2021. contrastive learning attention based winograd schemas https://openreview.net/forum?id=ud-WYSo9JSL Can contrastive learning avoid shortcut solutions? | OpenReview We study feature suppression in contrastive learning and develop a method to mitigate this effect and improve generalization. contrastive learning shortcut solutions avoid openreview https://openreview.net/forum?id=PLUXnnxUdr4 Graph Contrastive Learning for Skeleton-based Action Recognition | OpenReview For GCN-based methods in skeleton-based action recognition, this work extends the graph learning from using intra-sequence local context to exploring... contrastive learning graph skeleton based action https://deepai.org/publication/pointacl-adversarial-contrastive-learning-for-robust-point-clouds-representation-under-adversarial-attack PointACL:Adversarial Contrastive Learning for Robust Point Clouds Representation under Adversarial... Sep 14, 2022 - 09/14/22 - Despite recent success of self-supervised based contrastive learning model for 3D point clouds representation, the adversarial rob... contrastive learning point clouds adversarial robust representation https://deepai.org/publication/moquad-motion-focused-quadruple-construction-for-video-contrastive-learning MoQuad: Motion-focused Quadruple Construction for Video Contrastive Learning | DeepAI Dec 21, 2022 - 12/21/22 - Learning effective motion features is an essential pursuit of video representation learning. This paper presents a simple yet effe... for video contrastive learning motion focused quadruple https://openreview.net/forum?id=SXXOMpPh0u&referrer=%5Bthe%20profile%20of%20Bjoern%20Menze%5D(%2Fprofile%3Fid%3D~Bjoern_Menze3) Probabilistic Contrastive Learning with Explicit Concentration on the Hypersphere | OpenReview Contrastive learning is predominantly deterministic, limiting its effectiveness in noisy and uncertain environments. We propose a probabilistic approach... contrastive learning probabilistic explicit concentration hypersphere https://openreview.net/forum?id=cu7IUiOhujH Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning | OpenReview State-of-the-art natural language understanding classification models follow two-stages: pre-training a large language model on an auxiliary task, and then... contrastive learning language model fine tuning supervised pre https://openreview.net/forum?id=Grj9GJUcuZ&referrer=%5Bthe%20profile%20of%20Jiahao%20Xu%5D(%2Fprofile%3Fid%3D~Jiahao_Xu1) SimCSE++: Improving Contrastive Learning for Sentence Embeddings from Two Perspectives | OpenReview This paper improves contrastive learning for sentence embeddings from two perspectives: handling dropout noise and addressing feature corruption. Specifically,... contrastive learning two perspectives improving https://openreview.net/forum?id=VzFXb6Au58¬eId=41sXsWJGVw Contradiction Retrieval via Contrastive Learning with Sparsity | OpenReview Contradiction retrieval refers to identifying and extracting documents that explicitly disagree with or refute the content of a query, which is important to... contrastive learning contradiction retrieval via sparsity https://openreview.net/forum?id=k2uUeLCrQq&referrer=%5Bthe%20profile%20of%20Richard%20Andres%20Fineman%5D(%2Fprofile%3Fid%3D~Richard_Andres_Fineman1) RelCon: Relative Contrastive Learning for a Motion Foundation Model for Wearable Data | OpenReview We present RelCon, a novel self-supervised Relative Contrastive learning approach for training a motion foundation model from wearable accelerometry sensors.... contrastive learning https://deepai.org/publication/gradient-regularized-contrastive-learning-for-continual-domain-adaptation Gradient Regularized Contrastive Learning for Continual Domain Adaptation | DeepAI Jul 25, 2020 - 07/25/20 - Human beings can quickly adapt to environmental changes by leveraging learning experience. However, the poor ability of adapting t... contrastive learning domain adaptation gradient continual deepai https://aclanthology.org/2022.emnlp-main.686/ Adaptive Contrastive Learning on Multimodal Transformer for Review Helpfulness Prediction - ACL... Thong Nguyen, Xiaobao Wu, Anh Tuan Luu, Zhen Hai, Lidong Bing. Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. 2022. contrastive learning for review adaptive multimodal https://openreview.net/forum?id=FbUSCraXEB Efficient Availability Attacks against Supervised and Contrastive Learning Simultaneously |... Availability attacks provide a tool to prevent the unauthorized use of private data and commercial datasets by generating imperceptible noise and crafting... availability attacks contrastive learning efficient supervised simultaneously https://aclanthology.org/2022.coling-1.342/ ESimCSE: Enhanced Sample Building Method for Contrastive Learning of Unsupervised Sentence... Xing Wu, Chaochen Gao, Liangjun Zang, Jizhong Han, Zhongyuan Wang, Songlin Hu. Proceedings of the 29th International Conference on Computational Linguistics.... contrastive learning enhanced sample building method https://arxiv.org/abs/2305.10837 [2305.10837] Adaptive Graph Contrastive Learning for Recommendation Abstract page for arXiv paper 2305.10837: Adaptive Graph Contrastive Learning for Recommendation contrastive learning adaptive graph recommendation https://openreview.net/forum?id=7kpmIkHVpHu&referrer=%5Bthe%20profile%20of%20David%20Jacobs%5D(%2Fprofile%3Fid%3D~David_Jacobs1) Hyperbolic Contrastive Learning for Visual Representations beyond Objects | OpenReview We use hyperbolic objective to learn scene-object hypernymy, and show significant improvements for multiple datasets across multiple SSL tasks. contrastive learning hyperbolic visual representations beyond https://aclanthology.org/2024.lrec-main.766/ Improving Content Recommendation: Knowledge Graph-Based Semantic Contrastive Learning for Diversity... Yejin Kim, Scott Rome, Kevin Foley, Mayur Nankani, Rimon Melamed, Javier Morales, Abhay K. Yadav, Maria Peifer, Sardar Hamidian, H. Howie Huang. Proceedings of... content recommendation knowledge graph contrastive learning improving https://deepai.org/publication/bayesian-graph-contrastive-learning Bayesian Graph Contrastive Learning | DeepAI Dec 15, 2021 - 12/15/21 - Contrastive learning has become a key component of self-supervised learning approaches for graph-structured data. However, despite... contrastive learning bayesian graph deepai https://openreview.net/forum?id=SDCx6rQV2l Confidence-aware Contrastive Learning for Selective Classification | OpenReview Selective classification enables models to make predictions only when they are sufficiently confident, aiming to enhance safety and reliability, which is... contrastive learning confidence aware selective classification https://huggingface.co/papers/2402.17016 Paper page - Multi-Task Contrastive Learning for 8192-Token Bilingual Text Embeddings Join the discussion on this paper page paper page multi task contrastive learning https://aclanthology.org/2025.findings-emnlp.536/ VQA-Augmented Machine Translation with Cross-Modal Contrastive Learning - ACL Anthology Zhihui Zhang, Shiliang Sun, Jing Zhao, Tengfei Song, Hao Yang. Findings of the Association for Computational Linguistics: EMNLP 2025. 2025. machine translation contrastive learning vqa augmented https://deepai.org/publication/large-scale-hyperspectral-image-clustering-using-contrastive-learning Large-Scale Hyperspectral Image Clustering Using Contrastive Learning | DeepAI Nov 15, 2021 - 11/15/21 - Clustering of hyperspectral images is a fundamental but challenging task. The recent development of hyperspectral image clustering... large scale contrastive learning hyperspectral image clustering https://deepai.org/publication/multi-scale-and-cross-scale-contrastive-learning-for-semantic-segmentation Multi-scale and Cross-scale Contrastive Learning for Semantic Segmentation | DeepAI Mar 25, 2022 - 03/25/22 - This work considers supervised contrastive learning for semantic segmentation. Our approach is model agnostic. We apply contrastiv... contrastive learning semantic segmentation multi scale cross https://openreview.net/forum?id=UixzK8evk5&referrer=%5Bthe%20profile%20of%20Jiahao%20Xu%5D(%2Fprofile%3Fid%3D~Jiahao_Xu1) DistillCSE: Distilled Contrastive Learning for Sentence Embeddings | OpenReview This paper proposes the DistillCSE framework, which performs contrastive learning under the self-training paradigm with knowledge distillation. The potential... contrastive learning distilled sentence embeddings openreview https://velog.io/@dltpal07/SimCSE-Simple-Contrastive-Learning-of-Sentence-Embeddings-EMNLP2021-paper-review SimCSE: Simple Contrastive Learning of Sentence Embeddings (EMNLP / 2021) paper review contrastive learning simple https://openreview.net/forum?id=NU9AYHJvYe Optimal Sample Complexity of Contrastive Learning | OpenReview Contrastive learning is a highly successful technique for learning representations of data from labeled tuples, specifying the distance relations within the... contrastive learning optimal sample complexity openreview https://www.datacamp.com/tutorial/contrastive-learning Contrastive Learning: How Models Learn by Comparison | DataCamp Learn what contrastive learning is, how it works, and why it is used in modern machine learning for representation learning and self-supervised learning. contrastive learning by comparison models datacamp https://cohere.com/research/papers/studying-the-impact-of-magnitude-pruning-on-contrastive-learning-methods-2022-07-01 Studying the Impact of Magnitude Pruning on Contrastive Learning Methods We study the impact of different pruning techniques on the representation learned by deep neural networks trained with contrastive loss functions. Our work the impact contrastive learning studying magnitude pruning https://openreview.net/forum?id=BZQAC65qhPF Spectrum Guided Topology Augmentation for Graph Contrastive Learning | OpenReview Graph contrastive learning (GCL) is a major self-supervised graph learning technique that aims to capture invariant properties of graphs via instance... contrastive learning spectrum guided topology augmentation