Results 281 to 290 of about 4,189,347 (339)

Genome editing with CRISPR–Cas nucleases, base editors, transposases and prime editors

Nature Biotechnology, 2020
Andrew V Anzalone, Luke W Koblan, David R Liu   +2 more
exaly   +2 more sources

CRISPR technology: A decade of genome editing is only the beginning

Science, 2023
The advent of clustered regularly interspaced short palindromic repeat (CRISPR) genome editing, coupled with advances in computing and imaging capabilities, has initiated a new era in which genetic diseases and individual disease susceptibilities are ...
Joy Y Wang, Jennifer A Doudna
exaly   +2 more sources

FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space

arXiv.org
We present evaluation results for FLUX.1 Kontext, a generative flow matching model that unifies image generation and editing. The model generates novel output views by incorporating semantic context from text and image inputs.
Black Forest Labs, Stephen Batifol, A. Blattmann, Frederic Boesel, Saksham Consul, Cyril Diagne, Tim Dockhorn, Jack English, Zion English, Patrick Esser, Sumith Kulal, Kyle Lacey, Yam Levi, Cheng Li, Dominik Lorenz, Jonas Muller, Dustin Podell, Robin Rombach, Harry Saini, Axel Sauer, Luke Smith   +20 more
semanticscholar   +1 more source

VACE: All-in-One Video Creation and Editing

arXiv.org
Diffusion Transformer has demonstrated powerful capability and scalability in generating high-quality images and videos. Further pursuing the unification of generation and editing tasks has yielded significant progress in the domain of image content ...
Zeyinzi Jiang, Zhen Han, Chaojie Mao, Jingfeng Zhang, Yulin Pan, Yu Liu   +5 more
semanticscholar   +1 more source

Step1X-Edit: A Practical Framework for General Image Editing

arXiv.org
In recent years, image editing models have witnessed remarkable and rapid development. The recent unveiling of cutting-edge multimodal models such as GPT-4o and Gemini2 Flash has introduced highly promising image editing capabilities.
Shiyu Liu, Yucheng Han, Peng Xing, Fukun Yin, Rui Wang, Wei Cheng, Jiaqi Liao, Yingming Wang, Honghao Fu, Chunrui Han, Guopeng Li, Yuang Peng, Quan Sun, Jingwei Wu, Yan Cai, Zheng Ge, Ranchen Ming, Lei Xia, Xianfang Zeng, Yibo Zhu, Binxing Jiao, Xiangyu Zhang, Gang Yu, Daxin Jiang   +23 more
semanticscholar   +1 more source

AlphaEdit: Null-Space Constrained Knowledge Editing for Language Models

International Conference on Learning Representations
Large language models (LLMs) often exhibit hallucinations due to incorrect or outdated knowledge. Hence, model editing methods have emerged to enable targeted knowledge updates. To achieve this, a prevailing paradigm is the locating-then-editing approach,
Junfeng Fang, Houcheng Jiang, Kun Wang, Yunshan Ma, Xiang Wang, Xiangnan He, Tat-Seng Chua   +6 more
semanticscholar   +1 more source

UltraEdit: Instruction-based Fine-Grained Image Editing at Scale

Neural Information Processing Systems
This paper presents UltraEdit, a large-scale (approximately 4 million editing samples), automatically generated dataset for instruction-based image editing.
Haozhe Zhao, Xiaojian Ma, Liang Chen, Shuzheng Si, Rujie Wu, Kaikai An, Peiyu Yu, Minjia Zhang, Qing Li, Baobao Chang   +9 more
semanticscholar   +1 more source

Editing Modernism, Editing Theology:

The Journal of Modern Periodical Studies, 2012
In this essay, I trace the presence of Protestant neo-Orthodox theology within the pages of the Criterion. In particular, I show that Karl Barth, whose radical Protestantism would appear to be at odds with Eliot's orthodox Anglo-Catholicism, was in fact one of the Criterion's major theological interlocutors from 1934 onward. Recovering Barth's presence
openaire   +1 more source

HQ-Edit: A High-Quality Dataset for Instruction-based Image Editing

International Conference on Learning Representations
This study introduces HQ-Edit, a high-quality instruction-based image editing dataset with around 200,000 edits. Unlike prior approaches relying on attribute guidance or human feedback on building datasets, we devise a scalable data collection pipeline ...
Mude Hui, Siwei Yang, Bingchen Zhao, Yichun Shi, Heng Wang, Peng Wang, Yuyin Zhou, Cihang Xie   +7 more
semanticscholar   +1 more source

AnyEdit: Mastering Unified High-Quality Image Editing for Any Idea

Computer Vision and Pattern Recognition
Instruction-based image editing aims to modify specific image elements with natural language instructions. However, current models in this domain often struggle to execute complex user instructions accurately, as they are trained on low-quality data with
Qifan Yu, Wei Chow, Zhongqi Yue, Kaihang Pan, Yang Wu, Xiaoyang Wan, Juncheng Li, Siliang Tang, Hanwang Zhang, Yueting Zhuang   +9 more
semanticscholar   +1 more source