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    ID-Forcing is claimed to enable minute-scale video generation without fine-tuning

    HuggingPapers says the method aligns KV caching and conditioning with training to address drift beyond autoregressive video models’ training horizon.

    AKAK
    DailyPapersDA
    2 Sources, 2h ago, first seen 2h ago

    TLDR

    HuggingPapers describes ID-Forcing as a way to keep long autoregressive video generation in-distribution. It says the models drift beyond their training horizon and claims that aligning KV caching and conditioning with training enables minute-scale videos without fine-tuning.

    Combined views

    2.8K

    2 Sources, first seen 2h ago

    Combined views

    2.8K

    2 Sources, first seen 2h ago

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    2 Sources

    DailyPapers@HuggingPapersID-Forcing: keeping long video generation in-distribution Autoregressive video models drift beyond their training horizon. ID-Forcing aligns KV caching and conditioning with training, enabling minute-scale videos with no fine-tuning.2h
    AK@_akhaliqRT @HuggingPapers: ID-Forcing: keeping long video generation in-distribution Autoregressive video models drift beyond their training horiz…2h

    2 Sources

    DailyPapers@HuggingPapersID-Forcing: keeping long video generation in-distribution Autoregressive video models drift beyond their training horizon. ID-Forcing aligns KV caching and conditioning with training, enabling minute-scale videos with no fine-tuning.2h
    AK@_akhaliqRT @HuggingPapers: ID-Forcing: keeping long video generation in-distribution Autoregressive video models drift beyond their training horiz…2h