[HTML][HTML] Pre-trained language models and their applications
Pre-trained language models have achieved striking success in natural language
processing (NLP), leading to a paradigm shift from supervised learning to pre-training …
processing (NLP), leading to a paradigm shift from supervised learning to pre-training …
Large-scale multi-modal pre-trained models: A comprehensive survey
With the urgent demand for generalized deep models, many pre-trained big models are
proposed, such as bidirectional encoder representations (BERT), vision transformer (ViT) …
proposed, such as bidirectional encoder representations (BERT), vision transformer (ViT) …
Qwen technical report
Large language models (LLMs) have revolutionized the field of artificial intelligence,
enabling natural language processing tasks that were previously thought to be exclusive to …
enabling natural language processing tasks that were previously thought to be exclusive to …
Uni-controlnet: All-in-one control to text-to-image diffusion models
Text-to-Image diffusion models have made tremendous progress over the past two years,
enabling the generation of highly realistic images based on open-domain text descriptions …
enabling the generation of highly realistic images based on open-domain text descriptions …
Deepseekmoe: Towards ultimate expert specialization in mixture-of-experts language models
In the era of large language models, Mixture-of-Experts (MoE) is a promising architecture for
managing computational costs when scaling up model parameters. However, conventional …
managing computational costs when scaling up model parameters. However, conventional …
Galip: Generative adversarial clips for text-to-image synthesis
Synthesizing high-fidelity complex images from text is challenging. Based on large
pretraining, the autoregressive and diffusion models can synthesize photo-realistic images …
pretraining, the autoregressive and diffusion models can synthesize photo-realistic images …
Towards open-world recommendation with knowledge augmentation from large language models
Recommender system plays a vital role in various online services. However, its insulated
nature of training and deploying separately within a specific closed domain limits its access …
nature of training and deploying separately within a specific closed domain limits its access …
Using deepspeed and megatron to train megatron-turing nlg 530b, a large-scale generative language model
Pretrained general-purpose language models can achieve state-of-the-art accuracies in
various natural language processing domains by adapting to downstream tasks via zero …
various natural language processing domains by adapting to downstream tasks via zero …
Vector quantized diffusion model for text-to-image synthesis
We present the vector quantized diffusion (VQ-Diffusion) model for text-to-image generation.
This method is based on a vector quantized variational autoencoder (VQ-VAE) whose latent …
This method is based on a vector quantized variational autoencoder (VQ-VAE) whose latent …
Filip: Fine-grained interactive language-image pre-training
Unsupervised large-scale vision-language pre-training has shown promising advances on
various downstream tasks. Existing methods often model the cross-modal interaction either …
various downstream tasks. Existing methods often model the cross-modal interaction either …