930 citations · 2.5k across the 19 of their papers we have counts for
10 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…
s2s-ft: Fine-Tuning Pretrained Transformer Encoders for Sequence-to-Sequence Learning
Hangbo Bao, Li Dong, Wenhui Wang +2
Pretrained bidirectional Transformers, such as BERT, have achieved significant improvements in a wide variety of language understanding tasks, while it is not straightforward to di…
Learning to Sample Replacements for ELECTRA Pre-Training
Yaru Hao, Li Dong, Hangbo Bao +2
ELECTRA pretrains a discriminator to detect replaced tokens, where the replacements are sampled from a generator trained with masked language modeling. Despite the compelling perfo…
Attention Temperature Matters in Abstractive Summarization Distillation
Shengqiang Zhang, Xingxing Zhang, Hangbo Bao +1
Recent progress of abstractive text summarization largely relies on large pre-trained sequence-to-sequence Transformer models, which are computationally expensive. This paper aims…
MiniLMv2: Multi-Head Self-Attention Relation Distillation for Compressing Pretrained Transformers
Wenhui Wang, Hangbo Bao, Shaohan Huang +2
We generalize deep self-attention distillation in MiniLM (Wang et al., 2020) by only using self-attention relation distillation for task-agnostic compression of pretrained Transfor…
UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training
Hangbo Bao, Li Dong, Furu Wei +8
We propose to pre-train a unified language model for both autoencoding and partially autoregressive language modeling tasks using a novel training procedure, referred to as a pseud…
MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers
Wenhui Wang, Furu Wei, Li Dong +3
Pre-trained language models (e.g., BERT (Devlin et al., 2018) and its variants) have achieved remarkable success in varieties of NLP tasks. However, these models usually consist of…
Neural Melody Composition from Lyrics
Hangbo Bao, Shaohan Huang, Furu Wei +5
In this paper, we study a novel task that learns to compose music from natural language. Given the lyrics as input, we propose a melody composition model that generates lyrics-cond…
Neural Question Generation from Text: A Preliminary Study
Qingyu Zhou, Nan Yang, Furu Wei +3
Automatic question generation aims to generate questions from a text passage where the generated questions can be answered by certain sub-spans of the given passage. Traditional me…