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See everyone at MLSys 2025 in Santa Clara next week! Super excited to organize the Young Professional Symposium program on day one (May 12) and our invited speakers Soumith Chintala (keynote), Tim Dettmers, Wei-Lin Chiang, Simran Arora, Beidi Chen!

We are hosting a happy hour with LMSYS Org at #mlsys2025! Join us for engaging talks on SGLang, the structured generation library XGrammar, and the high-performance kernel library FlashInfer. Enjoy great food, lively discussions, and connect with the community! Click to join 👉

If you are around in the Bay Area, make sure to attend the #MLSys2025 keynote tomorrow by Soumith Chintala at the Santa Clara Convention Center. Checkout the full program at mlsys.org

Come and listen to Tim Dettmers 's talk at the #MLSys2025 young professional symposium!

#MLSys2025 day1 keynote. Extreme PyTorch from Soumith Chintala

The PyTorch Foundation is a Gold Sponsor of #MLSys2025 this week in Santa Clara. Visit the booth and explore talks from Soumith Chintala, Ion Stoica, and Exec Dir Matt White on open source AI and scalable ML systems. 🔗 hubs.la/Q03m5GKW0 #PyTorch #OpenSourceAI

#MLSys2025 make sure to attend 10:30am keynote Ion Stoica An AI stack: from scaling AI workloads to evaluating LLMs. Checkout full schedule at mlsys.org/virtual/2025/c…

🎉 Congratulations to the FlashInfer team – their technical paper, "FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving," just won best paper at #MLSys2025. 🏆 🙌 We are excited to share that we are now backing FlashInfer – a supporter and

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FlashInfer won #MLSys2025 best paper🏆, with backing from NVIDIA AI Developer to bring top LLM inference kernels to the community

Many congrats to Zihao Ye and the entire team for the best paper award 🏆! Excited to see that FlashInfer is getting wider support and is part of LLM engines that everyone uses.

We’re thrilled that FlashInfer won a Best Paper Award at MLSys 2025! 🎉 This wouldn’t have been possible without the community — huge thanks to LMSYS Org’s sglang for deep co-design (which is crtical for inference kernel evolution) and stress-testing over the years, and to

#MLSys2025 Prof. Anima Anandkumar will give a keynote Hardware-aware training and inference for large-scale AI at 10:30 today; make sure you don't miss it

Databricks 's Agent Bricks is powered by XGrammar for structured generation, and achieves high quality and efficiency. It helps you complete AI tasks without needing to worry about the algorithmic details. Give it a try!

🔥 We introduce Multiverse, a new generative modeling framework for adaptive and lossless parallel generation. 🚀 Multiverse is the first open-source non-AR model to achieve AIME24 and AIME25 scores of 54% and 46% 🌐 Website: multiverse4fm.github.io 🧵 1/n

Check out our work on parallel reasoning 🧠; We bring an AI-assisted curator that identifies parallel paths in sequential traces, then tune models into native parallel thinkers that runs efficiently with prefix sharing and batching. Really excited about this general direction

Say hello to Multiverse — the Everything Everywhere All At Once of generative modeling. 💥 Lossless, adaptive, and gloriously parallel 🌀 Now open-sourced: multiverse4fm.github.io I was amazed how easily we could extract the intrinsic parallelism of even SOTA autoregressive

🚀 Super excited to share Multiverse! 🏃 It’s been a long journey exploring the space between model design and hardware efficiency. What excites me most is realizing that, beyond optimizing existing models, we can discover better model architectures by embracing system-level

📢Exciting updates from #MLSys2025! All session recordings are now available and free to watch at mlsys.org. We’re also thrilled to announce that #MLSys2026 will be held in Seattle next May—submissions open next month with a deadline of Oct 30. We look forward to

#MLSys2026 will be led by the general chair Luis Ceze and PC chairs Zhihao Jia and Aakanksha Chowdhery. The conference will be held in Bellevue on Seattle's east side. Consider submitting and bringing your latest works in AI and systems—more details at mlsys.org.