Large pre-trained models, also known as foundation models (FMs), are trained in a task-
agnostic manner on large-scale data and can be adapted to a wide range of downstream …

Abstract Knowledge Graph (KG) provides high-quality structured knowledge for various
downstream knowledge-aware tasks (such as recommendation and intelligent question …

Abstract The Visual Question Answering (VQA) system is the process of finding useful
information from images related to the question to answer the question correctly. It can be …

Thepre-train, prompt, predict'paradigm of large language models (LLMs) has achieved
remarkable success in open-domain question answering (OD-QA). However, few works …

With the development of digital city and smart city construction, the City Information Model
(CIM) has played a critical role as a container of spatial–temporal data to establish the …

Estimating the semantic similarity between text data is one of the challenging and open
research problems in the field of Natural Language Processing (NLP). The versatility of …

Open-domain Question Answering (OpenQA) is an important task in Natural Language
Processing (NLP), which aims to answer a question in the form of natural language based …

The explosive growth in fake news and its erosion to democracy, justice, and public trust has
increased the demand for fake news detection and intervention. This survey reviews and …

We present the first comprehensive study on automatic knowledge base construction for two
prevalent commonsense knowledge graphs: ATOMIC (Sap et al., 2019) and ConceptNet …

Graphs arise naturally in many real-world applications including social networks,
recommender systems, ontologies, biology, and computational finance. Traditionally …