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在机器学习中，生成模型可以用来直接对数据建模（例如根据某个变量的概率密度函数进行数据采样），也可以用来建立变量间的条件概率分布。条件概率分布可以由生成模型根据贝叶斯定理形成。
FastRM: An efficient and automatic explainability framework for multimodal generative models
FastRM: An efficient and automatic explainability framework for multimodal generative models
Arxiv
0+阅读 · 4月1日
Phaedrus: Predicting Dynamic Application Behavior with Lightweight Generative Models and LLMs
Arxiv
0+阅读 · 4月1日
TextCrafter: Accurately Rendering Multiple Texts in Complex Visual Scenes
Arxiv
0+阅读 · 4月1日
Local Information Matters: Inference Acceleration For Grounded Conversation Generation Models Through Adaptive Local-Aware Token Pruning
Arxiv
0+阅读 · 4月1日
Consistent Subject Generation via Contrastive Instantiated Concepts
Consistent Subject Generation via Contrastive Instantiated Concepts
Arxiv
0+阅读 · 3月31日
DICE: Discrete Inversion Enabling Controllable Editing for Multinomial Diffusion and Masked Generative Models
Arxiv
0+阅读 · 3月31日
Tackling Copyright Issues in AI Image Generation Through Originality Estimation and Genericization
Arxiv
0+阅读 · 3月31日
Pre-training with 3D Synthetic Data: Learning 3D Point Cloud Instance Segmentation from 3D Synthetic Scenes
Pre-training with 3D Synthetic Data: Learning 3D Point Cloud Instance Segmentation from 3D Synthetic Scenes
Arxiv
0+阅读 · 3月31日
Local Information Matters: Inference Acceleration For Grounded Conversation Generation Models Through Adaptive Local-Aware Token Pruning
Arxiv
0+阅读 · 3月31日
A Large Scale Analysis of Gender Biases in Text-to-Image Generative Models
Arxiv
0+阅读 · 3月30日
Gen-Swarms: Adapting Deep Generative Models to Swarms of Drones
Arxiv
0+阅读 · 3月29日
CoRPA: Adversarial Image Generation for Chest X-rays Using Concept Vector Perturbations and Generative Models
CoRPA: Adversarial Image Generation for Chest X-rays Using Concept Vector Perturbations and Generative Models
Arxiv
0+阅读 · 3月28日
GAITGen: Disentangled Motion-Pathology Impaired Gait Generative Model -- Bringing Motion Generation to the Clinical Domain
Arxiv
0+阅读 · 3月28日
De Novo Functional Protein Sequence Generation: Overcoming Data Scarcity through Regeneration and Large Models
Arxiv
0+阅读 · 3月27日
3DGen-Bench: Comprehensive Benchmark Suite for 3D Generative Models
Arxiv
0+阅读 · 3月27日
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