知识图谱问答是通过处理用户提出的自然语言问题, 基于知识图谱的某种形式,
从中获取相关答案的过程. 由于知识规模, 计算能力及自然语言处理能力的制约 …

As Large Language Models (LLMs) become popular, there emerged an important trend of
using multimodality to augment the LLMs' generation ability, which enables LLMs to better …

Abstract Knowledge graph question answering (KGQA) is the procedure of processing
natural language questions posed by users to obtain relevant answers from knowledge …

Dual-encoder-based dense retrieval models have become the standard in IR. They employ
large Transformer-based language models, which are notoriously inefficient in terms of …

Literature search is a routine practice for scientific studies as new discoveries build on
knowledge from the past. Current tools (eg PubMed, PubMed Central), however, generally …

Abstract Question Answering over Knowledge Graphs (KGQA) blends natural language
processing with structured knowledge representation. While much attention of existing …

To improve the performance of knowledge graph-based question answering system
(KGQA), several approaches have been developed to construct a semantic parser based on …

Knowledge graph based simple question answering (KBSQA) is a major area of research
within question answering. Although only dealing with simple questions, ie, questions that …

Abstract Although Question Answering (QA) have advanced to the human-level language
skills in NLP tasks, there is still a problem: the QA model gets confused when there are …

Automatic API recommendation can accelerate developers' programming, and has been
studied for years. There are two orthogonal lines of approaches for this task, ie, information …