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Scalable Vector Graphics (SVGs) are vital for modern image rendering due to their scalability and versatility.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Scalable vector graphics (SVG) 1.0 specification
Jon Ferraiolo, Fujisawa Jun, and Dean Jackson · 2000
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Scalable vector graphics
Antoine Quint · 2003
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Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli · 2004
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Bayesian Image Vectorization: the probabilistic inversion of vector image rasterization
James Richard Diebel · 2008
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Mean squared error: Love it or leave it? a new look at signal fidelity measures
Zhou Wang and Alan C Bovik · 2009
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Patch-based image vectorization with automatic curvilinear feature alignment
Tian Xia, Binbin Liao, and Yizhou Yu · 2009
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Understanding the difficulty of training deep feedforward neural networks
Xavier Glorot and Yoshua Bengio · 2010
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A subdivision-based representation for vector image editing
Zicheng Liao, Hugues Hoppe, David Forsyth, and Yizhou Yu · 2012
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
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Vqa: Visual question answering
Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C Lawrence Zitnick, and Devi Parikh · 2015
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A note on the evaluation of generative models
Lucas Theis, Aäron van den Oord, and Matthias Bethge · 2015
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Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton · 2016
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Layer normalization
Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton · 2016
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Diverse beam search: Decoding diverse solutions from neural sequence models
Ashwin K Vijayakumar, Michael Cogswell, Ramprasath R Selvaraju, Qing Sun, Stefan Lee, David Crandall, and Dhruv Batra · 2016
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
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Automatic differentiation in PyTorch
Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer · 2017
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Searching for activation functions
Prajit Ramachandran, Barret Zoph, and Quoc V Le · 2017
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Generating high-quality and informative conversation responses with sequence-to-sequence models
Louis Shao, Stephan Gouws, Denny Britz, Anna Goldie, Brian Strope, and Ray Kurzweil · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Correcting length bias in neural machine translation
Kenton Murray and David Chiang · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
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Google bigquery
Ekaba Bisong and Ekaba Bisong · 2019
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Figr: Few-shot image generation with reptile
Louis Clouâtre and Marc Demers · 2019
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The curious case of neural text degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi · 2019
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Codesearchnet challenge: Evaluating the state of semantic code search
Hamel Husain, Ho-Hsiang Wu, Tiferet Gazit, Miltiadis Allamanis, and Marc Brockschmidt · 2019
Cited alongside, same era.
A learned representation for scalable vector graphics
Raphael Gontijo Lopes, David Ha, Douglas Eck, and Jonathon Shlens · 2019
Cited alongside, same era.
Fast transformer decoding: One write-head is all you need
Noam Shazeer · 2019
Cited alongside, same era.
Huggingface’s transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, et al · 2019
Cited alongside, same era.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
Scaling autoregressive models for content-rich text-to-image generation
Jiahui Yu, Yuanzhong Xu, Jing Yu Koh, Thang Luong, Gunjan Baid, Zirui Wang, Vijay Vasudevan, Alexander Ku, Yinfei Yang, Burcu Karagol Ayan, et al · 2022
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Santacoder: don’t reach for the stars!
Loubna Ben Allal, Raymond Li, Denis Kocetkov, Chenghao Mou, Christopher Akiki, Carlos Munoz Ferrandis, Niklas Muennighoff, Mayank Mishra, Alex Gu, Manan Dey, et al · 2023
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Automatikz: Text-guided synthesis of scientific vector graphics with tikz
Jonas Belouadi, Anne Lauscher, and Steffen Eger · 2023
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Sparks of artificial general intelligence: Early experiments with gpt-4
Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott Lundberg, et al · 2023
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Cited alongside, same era.
Deepsvg: A hierarchical generative network for vector graphics animation
Alexandre Carlier, Martin Danelljan, Alexandre Alahi, and Radu Timofte · 2020
Cited alongside, same era.
An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
Cited alongside, same era.
The pile: An 800gb dataset of diverse text for language modeling
Leo Gao, Stella Biderman, Sid Black, Laurence Golding, Travis Hoppe, Charles Foster, Jason Phang, Horace He, Anish Thite, Noa Nabeshima, et al · 2020
Cited alongside, same era.
Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2020
Cited alongside, same era.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Cited alongside, same era.
Differentiable vector graphics rasterization for editing and learning
Tzu-Mao Li, Michal Lukáč, Michaël Gharbi, and Jonathan Ragan-Kelley · 2020
Cited alongside, same era.
Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al · 2021
Cited alongside, same era.
Mu Cai, Zeyi Huang, Yuheng Li, Haohan Wang, and Yong Jae Lee · 2023
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Svgformer: Representation learning for continuous vector graphics using transformers
Defu Cao, Zhaowen Wang, Jose Echevarria, and Yan Liu · 2023
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Github copilot ai pair programmer: Asset or liability?
Arghavan Moradi Dakhel, Vahid Majdinasab, Amin Nikanjam, Foutse Khomh, Michel C Desmarais, and Zhen Ming Jack Jiang · 2023
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Vectorfusion: Text-to-svg by abstracting pixel-based diffusion models
Ajay Jain, Amber Xie, and Pieter Abbeel · 2023
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Cairosvg
Kozea · 2023
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Efficient memory management for large language model serving with pagedattention
Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph Gonzalez, Hao Zhang, and Ion Stoica · 2023
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Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee · 2023
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Gpt-4 technical report, 2023
OpenAI · 2023
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GPT-4V(ision) System Card
OpenAI · 2023
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Dinov2: Learning robust visual features without supervision
Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, et al · 2023
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Beautifulsoup
Leonard Richardson · 2023
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svgpathtools
Andy S · 2023
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Accelerating llm inference with staged speculative decoding
Benjamin Spector and Chris Re · 2023
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Iconshop: Text-based vector icon synthesis with autoregressive transformers
Ronghuan Wu, Wanchao Su, Kede Ma, and Jing Liao · 2023
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Sigmoid loss for language image pre-training
Xiaohua Zhai, Basil Mustafa, Alexander Kolesnikov, and Lucas Beyer · 2023
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Beyond pixels: Exploring human-readable svg generation for simple images with vision language models, 2023
Tong Zhang, Haoyang Liu, Peiyan Zhang, Yuxuan Cheng, and Haohan Wang · 2023
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Detikzify: Synthesizing graphics programs for scientific figures and sketches with tikz
Jonas Belouadi, Simone Paolo Ponzetto, and Steffen Eger · 2024
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Scaling rectified flow transformers for high-resolution image synthesis
Patrick Esser, Sumith Kulal, Andreas Blattmann, Rahim Entezari, Jonas Müller, Harry Saini, Yam Levi, Dominik Lorenz, Axel Sauer, Frederic Boesel, et al · 2024
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Starcoder 2 and the stack v2: The next generation
Anton Lozhkov, Raymond Li, Loubna Ben Allal, Federico Cassano, Joel Lamy-Poirier, Nouamane Tazi, Ao Tang, Dmytro Pykhtar, Jiawei Liu, Yuxiang Wei, et al · 2024
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Autotrace
Martin Weber · 2024
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Svgeditbench: A benchmark dataset for quantitative assessment of llm’s svg editing capabilities
Kunato Nishina and Yusuke Matsui · 2024
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Intentgpt: Few-shot intent discovery with large language models
Juan A Rodriguez, Nicholas Botzer, David Vazquez, Christopher Pal, Marco Pedersoli, and Issam Laradji · 2024
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Qwen2-vl: Enhancing vision-language model’s perception of the world at any resolution
Peng Wang, Shuai Bai, Sinan Tan, Shijie Wang, Zhihao Fan, Jinze Bai, Keqin Chen, Xuejing Liu, Jialin Wang, Wenbin Ge, et al · 2024
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Comparison of raster-to-vector conversion software — Wikipedia, the free encyclopedia
Wikipedia · 2024
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Vgbench: Evaluating large language models on vector graphics understanding and generation
Bocheng Zou, Mu Cai, Jianrui Zhang, and Yong Jae Lee · 2024
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