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    Sigma presented as a large-scale continuous diffusion language model

    A project lead says Sigma has 3B- and 8B-parameter versions trained with likelihood, with comparable math and coding results.

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    TLDR

    A project lead presents Sigma as a continuous diffusion language model with 3B- and 8B-parameter versions. The team says its math and coding results are comparable to those of discrete diffusion and autoregressive models, and that Sigma enables study of inference-time interventions. Co-lead Wei Guo says the work, done during an NVIDIA internship, matched or exceeded masked diffusion language models trained under aligned budgets.

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    Combined views

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    3 Sources, first seen 3h ago

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    3 Sources

    @WeiGuo01Excited to share my work during summer internship at NVIDIA! We build the first large-scale continuous dLLM, reaching comparable and even better performance compared with masked dLLM trained under aligned budgets, and discover interesting properties its continuous dynamics!3h
    @ArashVahdatRT @zhihanyang_: 💫 Large Language Continuous Diffusion Models Presenting Sigma, the first large-scale (3B/8B) continuous diffusion LM (dLM…1h

    3 Sources

    @WeiGuo01Excited to share my work during summer internship at NVIDIA! We build the first large-scale continuous dLLM, reaching comparable and even better performance compared with masked dLLM trained under aligned budgets, and discover interesting properties its continuous dynamics!3h
    @ArashVahdatRT @zhihanyang_: 💫 Large Language Continuous Diffusion Models Presenting Sigma, the first large-scale (3B/8B) continuous diffusion LM (dLM…1h