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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 1–25 of 36 papers

TitleStatusHype
Roboflow100-VL: A Multi-Domain Object Detection Benchmark for Vision-Language ModelsCode2
λ-ECLIPSE: Multi-Concept Personalized Text-to-Image Diffusion Models by Leveraging CLIP Latent SpaceCode2
RadAlign: Advancing Radiology Report Generation with Vision-Language Concept AlignmentCode1
Lumen: Unleashing Versatile Vision-Centric Capabilities of Large Multimodal ModelsCode1
Expanding Scene Graph Boundaries: Fully Open-vocabulary Scene Graph Generation via Visual-Concept Alignment and RetentionCode1
FinTagging: An LLM-ready Benchmark for Extracting and Structuring Financial InformationCode1
Text-Video Retrieval with Global-Local Semantic Consistent LearningCode1
AltDiffusion: A Multilingual Text-to-Image Diffusion ModelCode1
ConceptBed: Evaluating Concept Learning Abilities of Text-to-Image Diffusion ModelsCode1
Concept Extraction Using Pointer-Generator NetworksCode1
ConceptCLIP: Towards Trustworthy Medical AI via Concept-Enhanced Contrastive Langauge-Image Pre-trainingCode1
MICA: Towards Explainable Skin Lesion Diagnosis via Multi-Level Image-Concept AlignmentCode1
3D Point Cloud Pre-training with Knowledge Distillation from 2D Images—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
Getting the Most out of AMR Parsing—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
Interpretable Concept-based Deep Learning Framework for Multimodal Human Behavior Modeling—0
Language-based Action Concept Spaces Improve Video Self-Supervised Learning—0
Natural Language Detectors Emerge in Individual Neurons—0
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