This paper presents a comprehensive survey of ChatGPT-related (GPT-3.5 and GPT-4)
research, state-of-the-art large language models (LLM) from the GPT series, and their …

In the rapidly evolving domain of Natural Language Generation (NLG) evaluation,
introducing Large Language Models (LLMs) has opened new avenues for assessing …

We introduce PaLM 2, a new state-of-the-art language model that has better multilingual and
reasoning capabilities and is more compute-efficient than its predecessor PaLM. PaLM 2 is …

Generative Pre-trained Transformer (GPT) models have shown remarkable capabilities for
natural language generation, but their performance for machine translation has not been …

We describe GEMBA, a GPT-based metric for assessment of translation quality, which works
both with a reference translation and without. In our evaluation, we focus on zero-shot …

ChatGPT shows remarkable capabilities for machine translation (MT). Several prior studies
have shown that it achieves comparable results to commercial systems for high-resource …

Natural language generation has witnessed significant advancements due to the training of
large language models on vast internet-scale datasets. Despite these advancements, there …

In this paper, we present the joint contribution of Unbabel and IST to the WMT 2022 Metrics
Shared Task. Our primary submission–dubbed COMET-22–is an ensemble between a …

Recent work in natural language processing (NLP) has yielded appealing results from
scaling model parameters and training data; however, using only scale to improve …

Large language models (LLMs) have demonstrated impressive capabilities in general
scenarios, exhibiting a level of aptitude that approaches, in some aspects even surpasses …