I am a member of technical staff at Microsoft Research. I work on language models (especially the Phi series of language models) and diffusion models theory.
Before, my research was mostly focused on sampling, optimization and proximal methods. Here is a paper at the intersection of these topics.
News
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I will talk about diffusion models at BIRS, Canada and IMS, Singapore. Thanks for the invitations!
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I am in Senegal for MLSS 2025. The energy is awesome!!!
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We released phi-4.
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I am a workshop chair at NeurIPS 2024.
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Anna Korba and I have presented a tutorial on Sampling as Optimization at ICML 2022. Here are our slides. You can watch the video here.
Some papers
LLMs
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Marah Abdin et al., “Phi-4 Technical Report”, December 2024.
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Marah Abdin et al., “Phi-3 Technical Report”, April 2024.
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Suriya Gunasekar, Yi Zhang et al., “Textbooks Are All You Need”, June 2023.
Diffusion models and sampling
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Sitan Chen, Sinho Chewi, Holden Lee, Yuanzhi Li, Jianfeng Lu and Adil Salim, “The probability flow ODE is provably fast”, NeurIPS 2023.
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Sitan Chen, Sinho Chewi, Jerry Li, Yuanzhi Li, Adil Salim and Anru R. Zhang, “Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions”, Notable top 5% paper @ ICLR 2023, Kigali, Rwanda.
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Adil Salim, Lukang Sun, Peter Richtárik, “A Convergence Theory for SVGD in the Population Limit under Talagrand’s Inequality T1”, ICML 2022.
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Anna Korba, Adil Salim, Michael Arbel, Giulia Luise and Arthur Gretton, “A Non-Asymptotic Analysis for Stein Variational Gradient Descent”, NeurIPS 2020.
Proximal methods in optimization and sampling
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Michael Diao, Krishnakumar Balasubramanian, Sinho Chewi, Adil Salim, “Forward-Backward Gaussian Variational Inference via JKO in the Bures–Wasserstein Space”, ICML 2023.
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Yongxin Chen, Sinho Chewi, Adil Salim, Andre Wibisono, “Improved analysis for a proximal algorithm for sampling”, COLT 2022.
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Adil Salim, Laurent Condat, Dmitry Kovalev and Peter Richtárik, “An Optimal Algorithm for Strongly Convex Minimization under Affine Constraints”, AISTATS 2022.
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Adil Salim and Peter Richtárik, “Primal Dual Interpretation of the Proximal Stochastic Gradient Langevin Algorithm”, NeurIPS 2020.
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Dmitry Kovalev, Adil Salim and Peter Richtárik, “Optimal and Practical Algorithms for Smooth and Strongly Convex Decentralized Optimization”, NeurIPS 2020.
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Adil Salim, Anna Korba and Giulia Luise, “The Wasserstein Proximal Gradient Algorithm”, NeurIPS 2020.