From google gemini to openai q*(q-star): A survey of reshaping 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 …
[PDF][PDF] Efficient large language models: A survey
Abstract Large Language Models (LLMs) have demonstrated remarkable capabilities in
important tasks such as natural language understanding, language generation, and …
important tasks such as natural language understanding, language generation, and …
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 …
Trends and challenges of real-time learning in large language models: A critical review
M Jovanovic, P Voss - arXiv preprint arXiv:2404.18311, 2024 - arxiv.org
Real-time learning concerns the ability of learning systems to acquire knowledge over time,
enabling their adaptation and generalization to novel tasks. It is a critical ability for …
enabling their adaptation and generalization to novel tasks. It is a critical ability for …
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 …
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 …
[HTML][HTML] TeenyTinyLlama: open-source tiny language models trained in Brazilian Portuguese
NK Corrêa, S Falk, S Fatimah, A Sen… - Machine Learning with …, 2024 - Elsevier
Large language models (LLMs) have significantly advanced natural language processing,
but their progress has yet to be equal across languages. While most LLMs are trained in …
but their progress has yet to be equal across languages. While most LLMs are trained in …
Dense Training, Sparse Inference: Rethinking Training of Mixture-of-Experts Language Models
Mixture-of-Experts (MoE) language models can reduce computational costs by 2-4$\times $
compared to dense models without sacrificing performance, making them more efficient in …
compared to dense models without sacrificing performance, making them more efficient in …
Pushing The Limit of LLM Capacity for Text Classification
The value of text classification's future research has encountered challenges and
uncertainties, due to the extraordinary efficacy demonstrated by large language models …
uncertainties, due to the extraordinary efficacy demonstrated by large language models …
From Automation to Augmentation: Large Language Models Elevating Essay Scoring Landscape
Receiving immediate and personalized feedback is crucial for second-language learners,
and Automated Essay Scoring (AES) systems are a vital resource when human instructors …
and Automated Essay Scoring (AES) systems are a vital resource when human instructors …