collaborators

7 papers

cs.SD2026

MOSS-Audio Technical Report

Chen Yang, Chufan Yu, Hanfu Chen +27

MOSS-Audio is a unified audio-language model for speech, environmental sound, and music understanding, supporting audio captioning, time-aware question answering, timestamped trans…

cs.SD2026

MOSS-TTSD: Text to Spoken Dialogue Generation

Yuqian Zhang, Donghua Yu, Zhengyuan Lin +15

Spoken dialogue generation is crucial for applications like podcasts, dynamic commentary, and entertainment content, but poses significant challenges compared to single-utterance t…

cs.SD2026

MOSS-TTS Technical Report

Yitian Gong, Botian Jiang, Yiwei Zhao +23

This technical report presents MOSS-TTS, a speech generation foundation model built on a scalable recipe: discrete audio tokens, autoregressive modeling, and large-scale pretrainin…

cs.SD2026

MOSS-Audio-Tokenizer: Scaling Audio Tokenizers for Future Audio Foundation Models

Yitian Gong, Kuangwei Chen, Zhaoye Fei +9

Discrete audio tokenizers are fundamental to empowering large language models with native audio processing and generation capabilities. Despite recent progress, existing approaches…

cs.CV2026

MOVA: Towards Scalable and Synchronized Video-Audio Generation

OpenMOSS Team, Donghua Yu, Mingshu Chen +38

Audio is indispensable for real-world video, yet generation models have largely overlooked audio components. Current approaches to producing audio-visual content often rely on casc…

cs.LG2026

What Makes Position Zero Special? A Mechanistic Study of Position Zero Attention Sinks in LLMs

Runyu Peng, Ruixiao Li, Mingshu Chen +5

Transformers frequently allocate disproportionate attention to specific tokens, a phenomenon known as attention sinks. Causal large language models reliably form one at position ze…