2.2k citations · 7.1k across the 72 of their papers we have counts for
11 papers · 1 filter
InstructRetro: Instruction Tuning post Retrieval-Augmented Pretraining
Boxin Wang, Wei Ping, Lawrence McAfee +4
Pretraining auto-regressive large language models~(LLMs) with retrieval demonstrates better perplexity and factual accuracy by leveraging external databases. However, the size of e…
Retrieval meets Long Context Large Language Models
Peng Xu, Wei Ping, Xianchao Wu +7
Extending the context window of large language models (LLMs) is getting popular recently, while the solution of augmenting LLMs with retrieval has existed for years. The natural qu…
CleanUNet 2: A Hybrid Speech Denoising Model on Waveform and Spectrogram
Zhifeng Kong, Wei Ping, Ambrish Dantrey +1
In this work, we present CleanUNet 2, a speech denoising model that combines the advantages of waveform denoiser and spectrogram denoiser and achieves the best of both worlds. Clea…
RAVEN: In-Context Learning with Retrieval-Augmented Encoder-Decoder Language Models
Jie Huang, Wei Ping, Peng Xu +3
In this paper, we investigate the in-context learning ability of retrieval-augmented encoder-decoder language models. We first conduct a comprehensive analysis of existing models a…
Progressive Learning of 3D Reconstruction Network from 2D GAN Data
Aysegul Dundar, Jun Gao, Andrew Tao +1
This paper presents a method to reconstruct high-quality textured 3D models from single images. Current methods rely on datasets with expensive annotations; multi-view images and t…
Preserve Your Own Correlation: A Noise Prior for Video Diffusion Models
Songwei Ge, Seungjun Nah, Guilin Liu +7
Despite tremendous progress in generating high-quality images using diffusion models, synthesizing a sequence of animated frames that are both photorealistic and temporally coheren…