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She literally tried to save tom 😹

🎉 Breaking Records with DESI! ✨ Last week, our survey achieved a groundbreaking milestone by observing a staggering 40 MILLION SPECTRA! 🔭 This marks the largest spectroscopic sample ever obtained, showcasing the power of DESI's capabilities. 🚀 1/5

Haha, Thanks! I enjoyed my unfortunately very short visit to USTC very much! Will be back!

LISA is now supported in LMFlow🚀 Check out our latest script for tuning 7B LLMs with LISA in one line🌟. Any feedback is highly appreciated 😄 github.com/OptimalScale/L…

Thank you, Yuan-Sen! Will AI lead to unique scientific discovery in astronomical discovery? How long will this happen? How to uncover those treasure of interdisciplinary idea lurking in the vast research literature? We will try to give you those answers in the future!

Josh Speagle (Toronto) kicks off the AstroAI workshop with a detailed talk on the inner workings of machine learning #AstroAIworkshop

Today marks the start of an important collaboration between EPFL and the Tsinghua University in the framework of the MUlti Spectroscopic Telescope (MUST) project, promising transformative discoveries in our understanding of the universe. go.epfl.ch/MUST

The Radio Galaxy Zoo: EMU is going live! Help us link radio sources to their parent galaxies and classify them with simple descriptive tags. Discover exciting and unknown objects waiting to be found. Can't wait to hear about your discoveries!

The Payne just got a major upgrade. Led by Tomasz Różański and his heroic and painstaking effort, the verdict is final -- Transformer-based emulators significantly outperform existing methods by capturing long-range spectral information. Bonus: We now include wavelength as input,

Exciting paper day! This is one of the works I'm most pumped about recently. How far can we push LLM agents to perform autonomous research in astronomy? arxiv.org/abs/2409.14807 Led by Zechang Sun 孙泽昌, and with many outstanding colleagues, including Song Huang, we've demonstrated

After a year of hard work and many failures along the way, AstroMLab is proud to present AstroSage-LLaMA-3.1-8b. Specifically designed for astronomical Q&A, this 8B parameter model achieves GPT-4o's performance level in astronomy-related question-answering tasks (with ~1/1000

New release: Astrobench, our astronomy benchmarking dataset, now available alongside Astrosage-8B: huggingface.co/datasets/Astro… Josh Nguyen's phenomenal effort has made this possible.

My textbook on statistical machine learning for astronomy is now on arXiv. arxiv.org/abs/2506.12230

Can an AI model predict perfectly and still have a terrible world model? What would that even mean? Our new ICML paper formalizes these questions One result tells the story: A transformer trained on 10M solar systems nails planetary orbits. But it botches gravitational laws 🧵