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Zachary Novack

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#machine learning Preprint Aug 2026

Equilibrium Forcing: Adaptive Video Generation Without Noise Conditioning

Equilibrium Forcing is introduced, a simplified framework for video denoising generative models without noise level conditioning that pioneers modular training- and inference-time designs for noise-unconditional generation that decouple learning the denoising field from sampling.

H. Lillemark, Alex Rojas, Zachary Novack et al. · 0 citations
Preprint Aug 2026

Dialogue-Aware Video-to-Music Generation Using Public Domain Film Collections

This work introduces the Open Screen Soundtrack Library version 2 (OSSL-v2), a self-hosted corpus of 34,343 video clips totaling 246.4 hours, sourced from public-domain films, and uses this film-domain corpus to study dialogue as a conditioning signal for video-to-music generation, motivated by the close temporal coupl...

Haven Kim, Zachary Novack, Julian J. McAuley et al. · 1 citation
#artificial intelligence Preprint Dec 2025

Evaluating Music Context Preservation: A Multi-facet Framework for Music Editing Systems

The first MuseCP evaluation framework is introduced that covers four categories of music facets with fine-grained and well-tailored metrics to capture nuanced changes in music attributes and hopes it can offer practical guidance for developing more effective and reliable music editing strategies with strong MuseCP capa...

Yash Vishe, Eric Xue, Xunyi Jiang et al. · 1 citation

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