ServiceNow Research

Code Generation

WebMMU: A Benchmark for Multimodal Multilingual Website Understanding and Code Generation
WebMMU: A Benchmark for Multimodal Multilingual Website Understanding and Code Generation
Understanding diverse web data and automating web development presents an exciting challenge for agentic AI. While existing benchmarks …
Workshop at the Computer Vision and Pattern Recognition Conference (CVPR),  2025.
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WebMMU: A Benchmark for Multimodal Multilingual Website Understanding and Code Generation
WebMMU: A Benchmark for Multimodal Multilingual Website Understanding and Code Generation
Understanding diverse web data and automating web development presents an exciting challenge for agentic AI. While existing benchmarks …
Workshop at the International Conference of Learning Representation (ICLR),  2025.
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BigDocs: An Open and Permissively-Licensed Dataset for Training Multimodal Models on Document and Code Tasks
BigDocs: An Open and Permissively-Licensed Dataset for Training Multimodal Models on Document and Code Tasks
Multimodal AI has the potential to significantly enhance document-understanding tasks, such as processing receipts, understanding …
International Conference of Learning Representations (ICLR),  2025.
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Evaluating In-Context Learning of Libraries for Code Generation
Evaluating In-Context Learning of Libraries for Code Generation
Contemporary Large Language Models (LLMs) exhibit a high degree of code generation and comprehension capability. A particularly …
North American Chapter of the Association for Computational Linguistics (NAACL),  2024.
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InCoRo: In-Context Learning for Robotics Control with Feedback Loops
InCoRo: In-Context Learning for Robotics Control with Feedback Loops
One of the challenges in robotics is to enable robotic units with the reasoning capability that would be robust enough to execute …
ArXiv,  2024.
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StarCoder 2 and The Stack v2: The Next Generation
StarCoder 2 and The Stack v2: The Next Generation
The BigCode project, an open-scientific collaboration focused on the responsible development of Large Language Models for Code (Code …
Anton Lozhkov, Raymond Li, Loubna Ben Allal, Federico Cassano, Joel Lamy Poirier, Nouamane Tazi, Ao Tang, Dmytro Pykhtar, Jiawei Liu, Yuxiang Wei, Tianyang Liu, Max Tian, Denis Kocetkov, Arthur Zucker, Younes Belkada, Zijian Wang, Dmitry Abulkhanov, Indraneil Paul, Zhuang Li, Wen-Ding Li, Megan Risdal, Jia Li, Terry Yue Zhuo, Nii Osae Osae Dade, Lucas Krauß, Naman Jain, Yixuan Su, Xuanli He, Edoardo Abati, Yekun Chai, Xiangru Tang, Christopher Akiki, Chenghao Mou, Binyuan Hui, Nicolas Patry, Canwen Xu, Julian McAuley, Han Hu, Torsten Scholak, Sébastien Paquet, Jennifer Robinson, Carolyn Jane Anderson, Nicolas Chapados, Mostofa Patwary, Nima Tajbakhsh, Yacine Jernite, Carlos Muñoz Ferrandis, Lingming Zhang, Sean Hughes, Thomas Wolf , Arjun Guha, Leandro von Werra, Harm de Vries, Alex Gu, Armel Zebaze, Evgenii Zheltonozhskii, Jian Zhu, Manan Dey, Marc Marone, Mayank Mishra, Muhtasham Oblokulov, Olivier Dehaene, Qian Liu, Tri Dao, Wenhao Yu, Niklas Muennighoff
ArXiv,  2024.
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StarVector: Generating Scalable Vector Graphics Code from Images and Text
StarVector: Generating Scalable Vector Graphics Code from Images and Text
Scalable Vector Graphics (SVGs) have become integral in modern image rendering and graphic design applications due to their infinite …
ArXiv,  2024.
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The BigCode Project Governance Card
The BigCode Project Governance Card
This document serves as an overview of the different mechanisms and areas of governance in the BigCode project. It aims to support …
ArXiv,  2024.
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RepoFusion: Training Code Models to Understand Your Repository
RepoFusion: Training Code Models to Understand Your Repository
Despite the huge success of Large Language Models (LLMs) in coding assistants like GitHub Copilot, these models struggle to understand …
ArXiv,  2023.
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StarCoder: may the source be with you!
StarCoder: may the source be with you!
The BigCode community, an open-scientific collaboration working on the responsible development of Large Language Models for Code (Code …
Raymond Li, Loubna Ben Allal, Yangtian Zi, Denis Kocetkov, Chenghao Mou, Christopher Akiki, Jia Li, Jenny Chim, Terry Yue Zhuo, Thomas Wang, Mishig Davaadorj, João Monteiro, Oleh Shliazhko, Nicolas Gontier, Nicholas Meade, Ming-Ho Yee, Logesh Kumar Umapathi, Benjamin Lipkin, Zhiruo Wang, Rudra Murthy, Jason Stillerman, Siva Sankalp Patel, Dmitry Abulkhanov, Marco Zocca, Zhihan Zhang, Nour Fahmy, Urvashi Bhattacharyya, Swayam Singh, Sasha Luccioni, Paulo Villegas, Maxim Kunakov, Fedor Zhdanov, Manuel Romero, Tony Lee, Nadav Timor, Jennifer Ding, Claire Schlesinger, Hailey Schoelkopf, Jan Ebert, Jennifer Robinson, Carolyn Jane Anderson, Brendan Dolan-Gavitt, Danish Contractor, Siva Reddy, Daniel Fried, Dzmitry Bahdanau, Yacine Jernite, Carlos Muñoz Ferrandis, Sean Hughes, Thomas Wolf , Arjun Guha, Leandro von Werra, Harm de Vries, Joel Lamy Poirier, Alex Gu, Armel Zebaze, Jian Zhu, Manan Dey, Marc Marone, Mayank Mishra, Muhtasham Oblokulov, Olivier Dehaene, Qian Liu, Tri Dao, Wenhao Yu, Niklas Muennighoff
Transactions on Machine Learning Research (TMLR),  2023.
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