6 papers · 1 filter
VibeVoice Technical Report
Zhiliang Peng, Jianwei Yu, Wenhui Wang +10
This report presents VibeVoice, a novel model designed to synthesize long-form speech with multiple speakers by employing next-token diffusion, which is a unified method for modeli…
Multimodal Latent Language Modeling with Next-Token Diffusion
Yutao Sun, Hangbo Bao, Wenhui Wang +5
Multimodal generative models require a unified approach to handle both discrete data (e.g., text and code) and continuous data (e.g., image, audio, video). In this work, we propose…
RedStone: Curating General, Code, Math, and QA Data for Large Language Models
Yaoyao Chang, Lei Cui, Li Dong +13
Pre-training Large Language Models (LLMs) on high-quality, meticulously curated datasets is widely recognized as critical for enhancing their performance and generalization capabil…
KOSMOS-2.5: A Multimodal Literate Model
Tengchao Lv, Yupan Huang, Jingye Chen +13
The automatic reading of text-intensive images represents a significant advancement toward achieving Artificial General Intelligence (AGI). In this paper we present KOSMOS-2.5, a m…
You Only Cache Once: Decoder-Decoder Architectures for Language Models
Yutao Sun, Li Dong, Yi Zhu +6
We introduce a decoder-decoder architecture, YOCO, for large language models, which only caches key-value pairs once. It consists of two components, i.e., a cross-decoder stacked u…
Multi-Head Mixture-of-Experts
Xun Wu, Shaohan Huang, Wenhui Wang +1
Sparse Mixtures of Experts (SMoE) scales model capacity without significant increases in training and inference costs, but exhibits the following two issues: (1) Low expert activat…