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UniBriVL: Robust Universal Representation and Generation of Audio Driven
  Diffusion Models

UniBriVL: Robust Universal Representation and Generation of Audio Driven Diffusion Models

29 July 2023
Sen Fang
Bowen Gao
Yangjian Wu
T. Teoh
    DiffM
ArXivPDFHTML

Papers citing "UniBriVL: Robust Universal Representation and Generation of Audio Driven Diffusion Models"

3 / 3 papers shown
Title
Bridging the Gap between Text, Audio, Image, and Any Sequence: A Novel
  Approach using Gloss-based Annotation
Bridging the Gap between Text, Audio, Image, and Any Sequence: A Novel Approach using Gloss-based Annotation
Sen Fang
Sizhou Chen
Yalin Feng
Xiaofeng Zhang
T. Teoh
23
0
0
04 Oct 2024
Scaling Up Visual and Vision-Language Representation Learning With Noisy
  Text Supervision
Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision
Chao Jia
Yinfei Yang
Ye Xia
Yi-Ting Chen
Zarana Parekh
Hieu H. Pham
Quoc V. Le
Yun-hsuan Sung
Zhen Li
Tom Duerig
VLM
CLIP
293
3,683
0
11 Feb 2021
Scaling Laws for Neural Language Models
Scaling Laws for Neural Language Models
Jared Kaplan
Sam McCandlish
T. Henighan
Tom B. Brown
B. Chess
R. Child
Scott Gray
Alec Radford
Jeff Wu
Dario Amodei
226
4,424
0
23 Jan 2020
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