Research

In our research, we deal with large unstructured text data and work on topics from the fields of information retrieval and natural language processing.

In information retrieval, examples are query understanding, answering comparative or causal questions, known-item search, neural retrieval models, user simulation, and questions related to reproducible retrieval experiments.

In natural language processing, examples are the detection and spoiling of clickbait posts, the detection of (good) argumentation, and paraphrasing.

At the intersection of information retrieval and natural language processing, we work on mining information from large web archives and on questions related to the usage of large language models in conversational search systems or for generating direct answers on search queries.