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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
Concept Alignment—0
Expanding Scene Graph Boundaries: Fully Open-vocabulary Scene Graph Generation via Visual-Concept Alignment and RetentionCode1
Concept Alignment as a Prerequisite for Value Alignment—0
NEUCORE: Neural Concept Reasoning for Composed Image Retrieval—0
AltDiffusion: A Multilingual Text-to-Image Diffusion ModelCode1
Language-based Action Concept Spaces Improve Video Self-Supervised Learning—0
ConceptBed: Evaluating Concept Learning Abilities of Text-to-Image Diffusion ModelsCode1
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
Joint covariate-alignment and concept-alignment: a framework for domain generalizationCode0
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