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Found 7 papers, 1 papers with code
TriSampler: A Better Negative Sampling Principle for Dense Retrieval
Negative sampling stands as a pivotal technique in dense retrieval, essential for training effective retrieval models and significantly impacting retrieval performance.
A Roadmap for Big Model
With the rapid development of deep learning, training Big Models (BMs) for multiple downstream tasks becomes a popular paradigm.
A New Adaptive Gradient Method with Gradient Decomposition
Therefore, DecGD gets a rapid convergence in the early phases of training and controls the effective learning rates according to the loss based vectors which help lead to a better generalization.
Turing Award elites revisited: patterns of productivity, collaboration, authorship and impact
The Turing Award is recognized as the most influential and prestigious award in the field of computer science(CS).
CogView: Mastering Text-to-Image Generation via Transformers
Text-to-Image generation in the general domain has long been an open problem, which requires both a powerful generative model and cross-modal understanding.
Ranked #53 on
Text-to-Image Generation
on MS COCO
(using extra training data)
A New Variant of Stochastic Heavy ball Optimization Method for Deep Learning
Stochastic momentum optimization methods, also known as stochastic heavy ball (SHB) methods, are one of the most popular optimization methods for deep learning.
Attention: to Better Stand on the Shoulders of Giants
In the progress of science, the previously discovered knowledge principally inspires new scientific ideas, and citation is a reasonably good reflection of this cumulative nature of scientific research.
