Large, pre-trained language models (PLMs) such as BERT and GPT have drastically
changed the Natural Language Processing (NLP) field. For numerous NLP tasks …

Automatic knowledge graph construction aims at manufacturing structured human
knowledge. To this end, much effort has historically been spent extracting informative fact …

Large language models (LLMs), such as ChatGPT and GPT4, are making new waves in the
field of natural language processing and artificial intelligence, due to their emergent ability …

Human Intelligence (HI) excels at combining basic skills to solve complex tasks. This
capability is vital for Artificial Intelligence (AI) and should be embedded in comprehensive AI …

The Internet contains a wealth of knowledge—from the birthdays of historical figures to
tutorials on how to code—all of which may be learned by language models. However, while …

Large language models have shown impressive few-shot results on a wide range of tasks.
However, when knowledge is key for such results, as is the case for tasks such as question …

In this paper, we present empirical studies on conversational recommendation tasks using
representative large language models in a zero-shot setting with three primary …

Knowledge-intensive tasks, such as open-domain question answering (QA), require access
to a large amount of world or domain knowledge. A common approach for knowledge …

Text retrieval is a long-standing research topic on information seeking, where a system is
required to return relevant information resources to user's queries in natural language. From …

Modern recommender systems perform large-scale retrieval by embedding queries and item
candidates in the same unified space, followed by approximate nearest neighbor search to …