Knowledge Graphs (KGs) play a pivotal role in advancing various AI applications, with the
semantic web community's exploration into multi-modal dimensions unlocking new avenues …

Generating recommendation reasons for recommendation results is a long-standing
problem because it is challenging to explain the underlying reasons for recommending an …

Generating accurate SQL according to natural language questions (text-to-SQL) is a long-
standing problem since it is challenging in user question understanding, database schema …

Knowledge graph question answering (KGQA) involves answering natural language
questions by leveraging structured information stored in a knowledge graph. Typically …

大模型(LLM) 的兴起在自然语言处理领域引起了广泛关注, 其涌现能力在各个垂直领域(如金融,
医疗, 教育等) 也取得一定进展. 然而, 大模型自身面临解释性不足, 知识实时性差 …

Collaborative filtering (CF) models have demonstrated remarkable performance in
recommender systems, which represent users and items as embedding vectors. Recently …

Large language models (LLMs) are proficient in capturing factual knowledge across various
domains. However, refining their capabilities on previously seen knowledge or integrating …

Large language models (LLMs) have been demonstrated to possess the capabilities to
understand fundamental graph properties and address various graph reasoning tasks …

Large language models (LLMs) have been observed to occasionally exhibit hallucination, a
phenomenon where they generate statements unsupported by factual evidence, thereby …

Segment anything model (SAM) and its variants have recently shown promising
performance as foundation models. However, existing SAM-based models can only handle …