ICLR Poster "contrastive learning" Papers
35 papers found
$\mathbb{X}$-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs
Vlad Sobal, Mark Ibrahim, Randall Balestriero et al.
Adversarially Robust Anomaly Detection through Spurious Negative Pair Mitigation
Hossein Mirzaei Sadeghlou, Mojtaba Nafez, Jafar Habibi et al.
Aligning Visual Contrastive learning models via Preference Optimization
Amirabbas Afzali, Borna khodabandeh, Ali Rasekh et al.
Analyzing and Boosting the Power of Fine-Grained Visual Recognition for Multi-modal Large Language Models
Hulingxiao He, Geng Li, Zijun Geng et al.
An Effective Manifold-based Optimization Method for Distributionally Robust Classification
Jiawei Huang, Hu Ding
ASTrA: Adversarial Self-supervised Training with Adaptive-Attacks
Prakash Chandra Chhipa, Gautam Vashishtha, Jithamanyu Settur et al.
A Theoretical Analysis of Self-Supervised Learning for Vision Transformers
Yu Huang, Zixin Wen, Yuejie Chi et al.
A Unifying Framework for Representation Learning
Shaden Alshammari, John Hershey, Axel Feldmann et al.
Captured by Captions: On Memorization and its Mitigation in CLIP Models
Wenhao Wang, Adam Dziedzic, Grace Kim et al.
CLIBD: Bridging Vision and Genomics for Biodiversity Monitoring at Scale
ZeMing Gong, Austin Wang, Xiaoliang Huo et al.
Compositional Entailment Learning for Hyperbolic Vision-Language Models
Avik Pal, Max van Spengler, Guido D'Amely di Melendugno et al.
ConMix: Contrastive Mixup at Representation Level for Long-tailed Deep Clustering
Zhixin Li, Yuheng Jia
ContraDiff: Planning Towards High Return States via Contrastive Learning
Yixiang Shan, Zhengbang Zhu, Ting Long et al.
Cross the Gap: Exposing the Intra-modal Misalignment in CLIP via Modality Inversion
Marco Mistretta, Alberto Baldrati, Lorenzo Agnolucci et al.
Dataset Ownership Verification in Contrastive Pre-trained Models
Yuechen Xie, Jie Song, Mengqi Xue et al.
DistillHGNN: A Knowledge Distillation Approach for High-Speed Hypergraph Neural Networks
Saman Forouzandeh, Parham Moradi Dowlatabadi, Mahdi Jalili
Finding Shared Decodable Concepts and their Negations in the Brain
Cory Efird, Alex Murphy, Joel Zylberberg et al.
Gramian Multimodal Representation Learning and Alignment
Giordano Cicchetti, Eleonora Grassucci, Luigi Sigillo et al.
ImpScore: A Learnable Metric For Quantifying The Implicitness Level of Sentences
Yuxin Wang, Xiaomeng Zhu, Weimin Lyu et al.
Learning Clustering-based Prototypes for Compositional Zero-Shot Learning
Hongyu Qu, Jianan Wei, Xiangbo Shu et al.
MOCA: Self-supervised Representation Learning by Predicting Masked Online Codebook Assignments
MATTHIEU CORD, Antonin Vobecky, Oriane Siméoni et al.
MolSpectra: Pre-training 3D Molecular Representation with Multi-modal Energy Spectra
Liang Wang, Shaozhen Liu, Yu Rong et al.
Neuron Platonic Intrinsic Representation From Dynamics Using Contrastive Learning
Wei Wu, Can Liao, Zizhen Deng et al.
Personalized Representation from Personalized Generation
Shobhita Sundaram, Julia Chae, Yonglong Tian et al.
PharmacoMatch: Efficient 3D Pharmacophore Screening via Neural Subgraph Matching
Daniel Rose, Oliver Wieder, Thomas Seidel et al.
PPT: Patch Order Do Matters In Time Series Pretext Task
Jaeho Kim, Kwangryeol Park, Sukmin Yun et al.
Progressive Compositionality in Text-to-Image Generative Models
Xu Han, Linghao Jin, Xiaofeng Liu et al.
Robots Pre-train Robots: Manipulation-Centric Robotic Representation from Large-Scale Robot Datasets
Guangqi Jiang, Yifei Sun, Tao Huang et al.
SEBRA : Debiasing through Self-Guided Bias Ranking
Adarsh Kappiyath, Abhra Chaudhuri, AJAY JAISWAL et al.
SiMHand: Mining Similar Hands for Large-Scale 3D Hand Pose Pre-training
Nie Lin, Takehiko Ohkawa, Yifei Huang et al.
SSOLE: Rethinking Orthogonal Low-rank Embedding for Self-Supervised Learning
Lun Huang, Qiang Qiu, Guillermo Sapiro
Subtask-Aware Visual Reward Learning from Segmented Demonstrations
Changyeon Kim, Minho Heo, Doohyun Lee et al.
Weighted Point Set Embedding for Multimodal Contrastive Learning Toward Optimal Similarity Metric
Toshimitsu Uesaka, Taiji Suzuki, Yuhta Takida et al.
What Do You See in Common? Learning Hierarchical Prototypes over Tree-of-Life to Discover Evolutionary Traits
Harish Babu Manogaran, M. Maruf, Arka Daw et al.
What Has Been Overlooked in Contrastive Source-Free Domain Adaptation: Leveraging Source-Informed Latent Augmentation within Neighborhood Context
JING WANG, Wonho Bae, Jiahong Chen et al.