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representation learning

6206 papers

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Also known as

RL

Co-occurring keywords

contrastive learning (4032) self-supervised learning (3777) transfer learning (5449) neural network (6616) unsupervised learning (3264) graph neural network (3962) multimodal learning (4645) domain adaptation (4595) feature learning (1311) language model (4599)

Papers

ContraSim – Analyzing Neural Representations Based on Contrastive Learning NAACL 2024
Language-Independent Representations Improve Zero-Shot Summarization NAACL 2024
Start Simple: Progressive Difficulty Multitask Learning NAACL 2024
Memorizing Documents with Guidance in Large Language Models IJCAI 2024
Large Language Model-Enhanced Algorithm Selection: Towards Comprehensive Algorithm Representation IJCAI 2024
Dynamic Weighted Graph Fusion for Deep Multi-View Clustering IJCAI 2024
Deep Embedding Clustering Driven by Sample Stability IJCAI 2024
Entity Disambiguation via Fusion Entity Decoding NAACL 2024
Capturing Perspectives of Crowdsourced Annotators in Subjective Learning Tasks NAACL 2024
Learning Deformable Hypothesis Sampling for Accurate PatchMatch Multi-View Stereo AAAI 2024
Contrastive Tuning: A Little Help to Make Masked Autoencoders Forget AAAI 2024
TagFog: Textual Anchor Guidance and Fake Outlier Generation for Visual Out-of-Distribution Detection AAAI 2024
Efficient Spiking Neural Networks with Sparse Selective Activation for Continual Learning AAAI 2024
MultiClimate: Multimodal Stance Detection on Climate Change Videos EMNLP 2024
Learning Place Cell Representations and Context-Dependent Remapping NIPS 2024
Refining Latent Homophilic Structures over Heterophilic Graphs for Robust Graph Convolution Networks AAAI 2024
Train Once, Deploy Anywhere: Matryoshka Representation Learning for Multimodal Recommendation EMNLP 2024
Identifiable Object-Centric Representation Learning via Probabilistic Slot Attention NIPS 2024
Enhancing Feature Diversity Boosts Channel-Adaptive Vision Transformers NIPS 2024
A Closer Look at the CLS Token for Cross-Domain Few-Shot Learning NIPS 2024
Preventing Model Collapse in Deep Canonical Correlation Analysis by Noise Regularization NIPS 2024
Generalizing CNNs to graphs with learnable neighborhood quantization NIPS 2024
Graph Neural Networks Need Cluster-Normalize-Activate Modules NIPS 2024
Dendritic Integration Inspired Artificial Neural Networks Capture Data Correlation NIPS 2024
Physical Consistency Bridges Heterogeneous Data in Molecular Multi-Task Learning NIPS 2024