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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
Getting the Most out of AMR Parsing—0
Align-smatch: A Novel Evaluation Method for Chinese Abstract Meaning Representation Parsing based on Alignment of Concept and Relation—0
An Explanation of Intrinsic Self-Correction via Linear Representations and Latent Concepts—0
Concept Alignment—0
Concept Alignment as a Prerequisite for Value Alignment—0
Concept-Attention Whitening for Interpretable Skin Lesion Diagnosis—0
Enhancing Conceptual Understanding in Multimodal Contrastive Learning through Hard Negative Samples—0
3D Point Cloud Pre-training with Knowledge Distillation from 2D Images—0
Grammar-Based Concept Alignment for Domain-Specific Machine Translation—0
Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin—0
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