5 papers
What Matters in Preference Post-Training of Continuous Autoregressive Speech Language Models
Yingda Shen, Yao Qian, Dekun Chen +6
Continuous autoregressive speech language models combine an autoregressive (AR) backbone with a diffusion or flow-matching head. Preference post-training requires choosing how to c…
CPR: Combining global composing, local performing and full-sequence refining in piano rendering with continuous autoregressive modelling
Chong Jing, Junan Zhang, Zhizheng Wu
Prompt-conditioned piano MIDI-to-Music rendering aims to faithfully render target notes while reproducing the timbre of a reference recording. Existing approaches primarily follow…
P-MUSE: Prompt-MIDI-Optional Model for Unified Instrumental Music Synthesis and Editing
Chong Jing, Junan Zhang, Jing Yang +3
MIDI-to-Music system renders the melody and rhythm of a target MIDI sequence into musical segment while cloning instrument timbre from a prompt recording. Existing systems typicall…
Anysynth:Zero-Shot Instrument Cloning via In-Context Learning and Asymmetric Hierarchical Guidance
Chong Jing, Junan Zhang, Jing Yang +3
Zero-shot instrument cloning aims to render an arbitrary [Target MIDI] sequence with the acoustic identity of an unseen instrument given only a short [Reference Audio, Reference MI…
EigeNet: Geometry-Informed Multi-Modal Learning for Few-shot Novel View RIR Prediction
Chong Jing, Zitong Lan, Junan Zhang +1
Predicting spatially varying Room Impulse Response (RIR) from sparse observations is a critical but highly challenging inverse problem for immersive spatial audio rendering. In thi…