Information Access and Artificial Intelligence (IAI)

About us

Our current projects can be broadly classified into the following areas:

• Intelligent information access systems (search engines, recommender systems, conversational assistants)
• Trustworthy and transparent AI (fact-checking, explainability)
• LLMs and knowledge-driven NLP (representation learning, retrieval-augmented generation)
• Evaluation methodology and resources (benchmark collections, user simulation, LLM-as-a-judge)

Our research tackles the challenges posed by large-scale data, including text, semi-structured documents, and graphs. However, we are equally intrigued by the complexities of human-AI interaction. We observe and understand how users engage with these systems and utilize the information they receive, from search engines, recommender systems, and conversational agents. We specialize in cutting-edge AI methods at the intersection of Information Retrieval and Natural Language Processing. By combining these powerful data-driven approaches with human-centered design, we aim to build systems that provide truly intuitive access to trustworthy knowledge.

We are at the forefront of the international research scene and publish regularly at top conferences, such as SIGIR, WWW, WSDM, CIKM, and ECIR. We hosted the 10th International Conference on the Theory of Information Retrieval (ICTIR) in 2020 and will be hosting the 44th European Conference on Information Retrieval (ECIR) in 2022.

IAI is part of the UiS artificial intelligence initiative, Stavanger AI Lab.