Large language models (LLMs) are gaining increasing popularity in both academia and
industry, owing to their unprecedented performance in various applications. As LLMs …

Large language models (LLMs), such as OpenAI's GPT-4, Google's Bard or Meta's LLaMa,
have created unprecedented opportunities for analysing and generating language data on a …

Unlike previous studies on the Metaverse based on Second Life, the current Metaverse is
based on the social value of Generation Z that online and offline selves are not different …

Text generation has made significant advances in the last few years. Yet, evaluation metrics
have lagged behind, as the most popular choices (eg, BLEU and ROUGE) may correlate …

Existing question answering (QA) datasets fail to train QA systems to perform complex
reasoning and provide explanations for answers. We introduce HotpotQA, a new dataset …

We present Meena, a multi-turn open-domain chatbot trained end-to-end on data mined and
filtered from public domain social media conversations. This 2.6 B parameter neural network …

Text evaluation has historically posed significant challenges, often demanding substantial
labor and time cost. With the emergence of large language models (LLMs), researchers …

Human evaluations are typically considered the gold standard in natural language
generation, but as models' fluency improves, how well can evaluators detect and judge …

A robust evaluation metric has a profound impact on the development of text generation
systems. A desirable metric compares system output against references based on their …

Recommender systems exploit interaction history to estimate user preference, having been
heavily used in a wide range of industry applications. However, static recommendation …