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Concept Alignment

Concept Alignment aims to align the learned representations or concepts within a model with the intended or target concepts. It involves adjusting the model's parameters or training process to ensure that the learned concepts accurately reflect the underlying patterns in the data.

Papers

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Showing 21–30 of 36 papers

TitleStatusHype
A Self-explaining Neural Architecture for Generalizable Concept LearningCode0
Concept-Attention Whitening for Interpretable Skin Lesion Diagnosis—0
Enhancing Conceptual Understanding in Multimodal Contrastive Learning through Hard Negative Samples—0
SNIFFER: Multimodal Large Language Model for Explainable Out-of-Context Misinformation Detection—0
Concept Alignment—0
Concept Alignment as a Prerequisite for Value Alignment—0
NEUCORE: Neural Concept Reasoning for Composed Image Retrieval—0
Language-based Action Concept Spaces Improve Video Self-Supervised Learning—0
3D Point Cloud Pre-training with Knowledge Distillation from 2D Images—0
CapEnrich: Enriching Caption Semantics for Web Images via Cross-modal Pre-trained KnowledgeCode0
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