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Concept Alignment
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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.
논문
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FinTagging: An LLM-ready Benchmark for Extracting and Structuring Financial Information
Replace in Translation: Boost Concept Alignment in Counterfactual Text-to-Image
An Explanation of Intrinsic Self-Correction via Linear Representations and Latent Concepts
Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin
Training-free Dense-Aligned Diffusion Guidance for Modular Conditional Image Synthesis
Enhancing Domain-Specific Retrieval-Augmented Generation: Synthetic Data Generation and Evaluation using Reasoning Models
Interpretable Concept-based Deep Learning Framework for Multimodal Human Behavior Modeling
ConceptCLIP: Towards Trustworthy Medical AI via Concept-Enhanced Contrastive Langauge-Image Pre-training
RadAlign: Advancing Radiology Report Generation with Vision-Language Concept Alignment
Text-Video Retrieval with Global-Local Semantic Consistent Learning
Improving Concept Alignment in Vision-Language Concept Bottleneck Models
A Self-explaining Neural Architecture for Generalizable Concept Learning
Concept-Attention Whitening for Interpretable Skin Lesion Diagnosis
Lumen: Unleashing Versatile Vision-Centric Capabilities of Large Multimodal Models
Enhancing Conceptual Understanding in Multimodal Contrastive Learning through Hard Negative Samples
SNIFFER: Multimodal Large Language Model for Explainable Out-of-Context Misinformation Detection
$λ$-ECLIPSE: Multi-Concept Personalized Text-to-Image Diffusion Models by Leveraging CLIP Latent Space
MICA: Towards Explainable Skin Lesion Diagnosis via Multi-Level Image-Concept Alignment
Concept Alignment
Expanding Scene Graph Boundaries: Fully Open-vocabulary Scene Graph Generation via Visual-Concept Alignment and Retention
Concept Alignment as a Prerequisite for Value Alignment
NEUCORE: Neural Concept Reasoning for Composed Image Retrieval
AltDiffusion: A Multilingual Text-to-Image Diffusion Model
Language-based Action Concept Spaces Improve Video Self-Supervised Learning
ConceptBed: Evaluating Concept Learning Abilities of Text-to-Image Diffusion Models
3D Point Cloud Pre-training with Knowledge Distillation from 2D Images
CapEnrich: Enriching Caption Semantics for Web Images via Cross-modal Pre-trained Knowledge
Joint covariate-alignment and concept-alignment: a framework for domain generalization
Concept Extraction Using Pointer-Generator Networks
Discovery of Natural Language Concepts in Individual Units of CNNs
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