Yang Liu

76 posts

Yang Liu

Yang Liu

@nlpyang

#LLM Researcher @Microsoft; PhD @EdinburghNLP

Bellevue, WA Bergabung Aralık 2021
332 Mengikuti1.4K Pengikut
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Yang Liu
Yang Liu@nlpyang·
Missing coding data in your R1? 🔥 Introducing KodCode—the largest verified synthetic coding dataset for Code LLM training! • 447K question–solution–test triplets • 12 diverse subsets • 10-trial solution verification for rock-solid correctness kodcode-ai.github.io
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Liliang Ren
Liliang Ren@liliang_ren·
Introducing HyperP, a scaling framework gives you better compute efficiency & transferable stability. At 6e21 FLOPs, HyperP reaches 1.58× compute efficiency over a strong Muon baseline; +MoE further gets 3.38× over dense. Gains even grow with scale🤯 📖: arxiv.org/abs/2603.28743
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Zhangchen Xu
Zhangchen Xu@zhangchen_xu·
Missing coding data in your R1? Introducing KodCode 🐱: a diverse, challenging, and verifiable synthetic dataset for LLM coding! With 447K verified question-solution-test triplets, KodCode is designed for supervised fine-tuning (SFT) and reinforcement learning (RL). 💡Key Features ✨Diverse & Challenging: 5 synthesis methods, 12 subsets covering multiple domains (algorithms to package-specific knowledge) and difficulty levels (basic exercises to competitive programming tasks). ✨Verifiable Correctness: Question-solution-test triplets are systematically validated via a self-verification process with GPT-4o. ✨ Supports RL & SFT: Unit tests enable RL tuning, plus verified CoT responses generated by DeepSeek-R1 🐳 via reject sampling to support SFT. --------------- >> Project Page: kodcode-ai.github.io >> KodCode-V1 (for RL): huggingface.co/datasets/KodCo… >> KodCode-V1-SFT-R1 (for SFT): huggingface.co/datasets/KodCo… >> Paper: arxiv.org/abs/2503.02951 >> Codebase for creating this dataset: github.com/KodCode-AI/kod… Thanks to my great mentor @nlpyang for invaluable guidance and support on this project! 🤩 [1/5]
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Yang Liu
Yang Liu@nlpyang·
Missing coding data in your R1? 🔥 Introducing KodCode—the largest verified synthetic coding dataset for Code LLM training! • 447K question–solution–test triplets • 12 diverse subsets • 10-trial solution verification for rock-solid correctness kodcode-ai.github.io
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Yang Liu@nlpyang·
I don't really understand why people think RL takes less compute than pretrain.
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Yang Liu@nlpyang·
@kdcreer Ah, thank you for saving this post
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Yang Liu@nlpyang·
Microsoft GenAI is looking for a summer intern to work on Sparse LLMs, if you are interested, please DM me or send a resume to yaliu10 at microsoft dot com
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Yang Liu@nlpyang·
If you are at NeurIPS, you could check out our poster about Efficient Transformer this evening.
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Yang Liu@nlpyang·
Wow, google really cares a lot about MMLU 🧐
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Yang Liu@nlpyang·
I have to admit, writing ICLR meta reviews is much more fun than writing ARR ones. What happened here?
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Yang Liu@nlpyang·
After 1 year birthday of ChatGPT, you think it is a good thing or a bad thing for NLP research?
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Yang Liu@nlpyang·
Contact with AIG is only a symbol or a switch. Regardless of the content of the encounter, the results would be the same. The impact would be magnified by the lens of human mass psychology and culture until it resulted in substantive influences on the progress of civilization.
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Yang Liu
Yang Liu@nlpyang·
This madness should stop. And I hope that place is the same as it was last week.
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