With the explosive growth of artificial intelligence (AI) and big data, it has become vitally
important to organize and represent the enormous volume of knowledge appropriately. As …

Large language models (LLMs), such as GPT4 and LLaMA, are creating significant
advancements in natural language processing, due to their strong text encoding/decoding …

Graph representation learning aims to effectively encode high-dimensional sparse graph-
structured data into low-dimensional dense vectors, which is a fundamental task that has …

The Internet has revolutionised the way information is retrieved, and the increase in the
number of users has resulted in a surge in the volume and heterogeneity of available data …

Large language models (LLMs), while exhibiting exceptional performance, suffer from
hallucinations, especially on knowledge-intensive tasks. Existing works propose to augment …

When reading a scholarly article, inline citations help researchers contextualize the current
article and discover relevant prior work. However, it can be challenging to prioritize and …

Citation recommendation describes the task of recommending citations for a given text. Due
to the overload of published scientific works in recent years on the one hand, and the need …

The huge amount of research papers on the web makes finding a relevant manuscript a
difficult task. In recent years many models were introduced to support researchers by …

Abstract Information extracted from social network services promise to improve the accuracy
of recommender systems in various domains. Against this background, community detection …

Social applications foster the involvement of end users in Web content creation, as a result
of which a new source of vast amounts of data about users and their likes and dislikes has …