Large language models (LLMs) have demonstrated extraordinary capabilities and
contributed to multiple fields, such as generating and summarizing text, language …

Abstract Pretrained Foundation Models (PFMs) are regarded as the foundation for various
downstream tasks across different data modalities. A PFM (eg, BERT, ChatGPT, GPT-4) is …

Ever since the Turing Test was proposed in the 1950s, humans have explored the mastering
of language intelligence by machine. Language is essentially a complex, intricate system of …

With the prevalence of pre-trained language models (PLMs) and the pre-training–fine-tuning
paradigm, it has been continuously shown that larger models tend to yield better …

Humans possess an extraordinary ability to create and utilize tools. With the advent of
foundation models, artificial intelligence systems have the potential to be equally adept in …

Large language models (LLMs) are a special class of pretrained language models (PLMs)
obtained by scaling model size, pretraining corpus and computation. LLMs, because of their …

Knowledge Distillation (KD) is a promising technique for reducing the high computational
demand of large language models (LLMs). However, previous KD methods are primarily …

Fine-tuning on instruction data has been widely validated as an effective practice for
implementing chat language models like ChatGPT. Scaling the diversity and quality of such …

In the past decades, recommender systems have attracted much attention in both research
and industry communities. Existing recommendation models mainly learn the underlying …

Artificial intelligence technologies are rapidly advancing. As part of this development, large
language models (LLMs) are increasingly being used when humans interact with systems …