ServiceNow AI Research

Raymond Li

Raymond Li

AI Developer

Model Readiness

Raymond is a Research Engineer at ServiceNow AI Research. His research has focused on LLM-related topics such as summarization, text-to-SQL and code generation. He worked on model pretraining, continued-pretraining, SFT, and architectures for efficient inference. Raymond’s background is in Applied Mathematics and Computer Science. He holds a Master’s and engineering degree from École Polytechnique (France) as well as a MSc. in Computer Science from Polytechnique Montreal where he was supervised by Christopher Pal.

Interests
  • Large Language Models
  • Summarization
  • Large Code Models

Publications

Using Scaling Laws for Data Source Utility Estimation in Domain-Specific Pre-Training. Conference on Language Modeling Workshops,  2025.

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StarCoder 2 and The Stack v2: The Next Generation. ArXiv,  2024.

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StarCoder: may the source be with you!. Transactions on Machine Learning Research (TMLR),  2023.

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SantaCoder: don't reach for the stars!. Workshop at the International Conference on Learning Representations (ICLR),  2023.

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The Stack: 3 TB of permissively licensed source code. Transactions on Machine Learning Research (TMLR),  2022.

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DuoRAT: Towards Simpler Text-to-SQL Models. North American Chapter of the Association for Computational Linguistics (NAACL),  2021.

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On Extractive and Abstractive Neural Document Summarization with Transformer Language Models. Conference on Empirical Methods in Natural Language Processing (EMNLP),  2020.

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Towards Deep Conversational Recommendations. Conference on Neural Information Processing Systems (NeurIPS),  2018.

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