collaborators

11 papers

cs.SD2026

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

Haven Kim, Zachary Novack, Julian McAuley +1

Video-to-music generation has drawn growing interest for its role in conveying the emotion of visual media, including film. Progress in the field, however, is hampered by a reprodu…

cs.CV2026

Equilibrium Forcing: Adaptive Video Generation Without Noise Conditioning

Hansen Jin Lillemark, Alex Rojas, Zachary Novack +5

Standard autoregressive video generation algorithms based on Diffusion and Flow Matching rely on rigid training objectives and static sampling schedules, limiting inference procedu…

cs.SD2026

Benchmarking Language Modeling for Lossless Compression of Full-Fidelity Audio

Phillip Long, Zachary Novack, Chris Donahue

Autoregressive "language" models (LMs) trained on raw waveforms can be repurposed for lossless audio compression, but prior work is limited to 8-bit audio, leaving open whether suc…

cs.SD2026

Live Music Diffusion Models: Efficient Fine-Tuning and Post-Training of Interactive Diffusion Music Generators

Zachary Novack, Stephen Brade, Haven Kim +8

Interactive streaming music generation promises the use of generative models for live performance and co-creation that is impossible with offline models. However, SOTA models exist…

cs.SD2026

Break-the-Beat! Controllable MIDI-to-Drum Audio Synthesis

Shuyang Cui, Zhi Zhong, Qiyu Wu +9

Current methods for creating drum loop audio in digital music production, such as using one-shot samples or resampling, often demand non-trivial efforts of creators. While recent g…

cs.SD2026

Low-Resource Guidance for Controllable Latent Audio Diffusion

Zachary Novack, Zack Zukowski, CJ Carr +6

Generative audio requires fine-grained controllable outputs, yet most existing methods require model retraining on specific controls or inference-time controls (\textit{e.g.}, guid…