A Survey of Multimodel Large Language Models
Z Liang, Y Xu, Y Hong, P Shang, Q Wang… - Proceedings of the 3rd …, 2024 - dl.acm.org
With the widespread application of the Transformer architecture in various modalities,
including vision, the technology of large language models is evolving from a single modality …
including vision, the technology of large language models is evolving from a single modality …
From google gemini to openai q*(q-star): A survey of resha** the generative artificial intelligence (ai) research landscape
This comprehensive survey explored the evolving landscape of generative Artificial
Intelligence (AI), with a specific focus on the transformative impacts of Mixture of Experts …
Intelligence (AI), with a specific focus on the transformative impacts of Mixture of Experts …
Efficient large language models: A survey
Large Language Models (LLMs) have demonstrated remarkable capabilities in important
tasks such as natural language understanding and language generation, and thus have the …
tasks such as natural language understanding and language generation, and thus have the …
Llama-moe: Building mixture-of-experts from llama with continual pre-training
Abstract Mixture-of-Experts (MoE) has gained increasing popularity as a promising
framework for scaling up large language models (LLMs). However, training MoE from …
framework for scaling up large language models (LLMs). However, training MoE from …
A survey on mixture of experts
Large language models (LLMs) have garnered unprecedented advancements across
diverse fields, ranging from natural language processing to computer vision and beyond …
diverse fields, ranging from natural language processing to computer vision and beyond …
Scaling vision-language models with sparse mixture of experts
The field of natural language processing (NLP) has made significant strides in recent years,
particularly in the development of large-scale vision-language models (VLMs). These …
particularly in the development of large-scale vision-language models (VLMs). These …
Conpet: Continual parameter-efficient tuning for large language models
Continual learning necessitates the continual adaptation of models to newly emerging tasks
while minimizing the catastrophic forgetting of old ones. This is extremely challenging for …
while minimizing the catastrophic forgetting of old ones. This is extremely challenging for …
Dialogue summarization with mixture of experts based on large language models
Dialogue summarization is an important task that requires to generate highlights for a
conversation from different aspects (eg, content of various speakers). While several studies …
conversation from different aspects (eg, content of various speakers). While several studies …
Enable language models to implicitly learn self-improvement from data
Large Language Models (LLMs) have demonstrated remarkable capabilities in open-ended
text generation tasks. However, the inherent open-ended nature of these tasks implies that …
text generation tasks. However, the inherent open-ended nature of these tasks implies that …
Ai safety in generative ai large language models: A survey
Large Language Model (LLMs) such as ChatGPT that exhibit generative AI capabilities are
facing accelerated adoption and innovation. The increased presence of Generative AI (GAI) …
facing accelerated adoption and innovation. The increased presence of Generative AI (GAI) …