Add to ORKGLarge language models (LLMs) have garnered significant attention, but the definition of "large" lacks clarity. This paper focuses on medium-sized language models (MLMs), defined as having at least six billion parameters but less than 100 billion. The study evaluates MLMs regarding zero-shot generative question answering, which requires models to provide elaborate answers without external document retrieval. The paper introduces an own test dataset and presents results from human evaluation. Results show that combining the best answers from different MLMs yielded an overall correct answer rate of 82.7% which is better than the 60.9% of ChatGPT. The best MLM achieved 71.8% and has 33B parameters, which highlights the importance of using appro...
When scaled to hundreds of billions of parameters, pretrained language models such as GPT-3 (Brown e...
When scaled to hundreds of billions of parameters, pretrained language models such as GPT-3 (Brown e...
Pretrained large language models (LLMs) are widely used in many sub-fields of natural language proce...
Large Language Models (LLMs) have achieved significant success across various natural language proce...
Recent developments in large language models (LLMs) have shown promise in enhancing the capabilities...
Based on powerful Large Language Models (LLMs), recent generative Multimodal Large Language Models (...
Large language models (LLMs) are gaining increasing popularity in both academia and industry, owing ...
Large Language Models (LLMs) have demonstrated impressive performance on Natural Language Processing...
Multilingual pre-trained language models are incredibly effective at Question Answering (QA), a core...
Semantic consistency of a language model is broadly defined as the model's ability to produce semant...
We present an empirical evaluation of various outputs generated by nine of the most widely-available...
As large language models (LLMs) continue to advance, accurately and comprehensively evaluating their...
Topic models help make sense of large text collections. Automatically evaluating their output and de...
When scaled to hundreds of billions of parameters, pretrained language models such as GPT-3 (Brown e...
When scaled to hundreds of billions of parameters, pretrained language models such as GPT-3 (Brown e...
When scaled to hundreds of billions of parameters, pretrained language models such as GPT-3 (Brown e...
When scaled to hundreds of billions of parameters, pretrained language models such as GPT-3 (Brown e...
Pretrained large language models (LLMs) are widely used in many sub-fields of natural language proce...
Large Language Models (LLMs) have achieved significant success across various natural language proce...
Recent developments in large language models (LLMs) have shown promise in enhancing the capabilities...
Based on powerful Large Language Models (LLMs), recent generative Multimodal Large Language Models (...
Large language models (LLMs) are gaining increasing popularity in both academia and industry, owing ...
Large Language Models (LLMs) have demonstrated impressive performance on Natural Language Processing...
Multilingual pre-trained language models are incredibly effective at Question Answering (QA), a core...
Semantic consistency of a language model is broadly defined as the model's ability to produce semant...
We present an empirical evaluation of various outputs generated by nine of the most widely-available...
As large language models (LLMs) continue to advance, accurately and comprehensively evaluating their...
Topic models help make sense of large text collections. Automatically evaluating their output and de...
When scaled to hundreds of billions of parameters, pretrained language models such as GPT-3 (Brown e...
When scaled to hundreds of billions of parameters, pretrained language models such as GPT-3 (Brown e...
When scaled to hundreds of billions of parameters, pretrained language models such as GPT-3 (Brown e...
When scaled to hundreds of billions of parameters, pretrained language models such as GPT-3 (Brown e...
Pretrained large language models (LLMs) are widely used in many sub-fields of natural language proce...