1 code implementation • IWCS (ACL) 2021 • Aikaterini-Lida Kalouli, Rebecca Kehlbeck, Rita Sevastjanova, Oliver Deussen, Daniel Keim, Miriam Butt
Research in NLP has mainly focused on factoid questions, with the goal of finding quick and reliable ways of matching a query to an answer.
no code implementations • ACL 2021 • Rita Sevastjanova, Aikaterini-Lida Kalouli, Christin Beck, Hanna Sch{\"a}fer, Mennatallah El-Assady
Despite the success of contextualized language models on various NLP tasks, it is still unclear what these models really learn.
no code implementations • COLING 2020 • Aikaterini-Lida Kalouli, Rita Sevastjanova, Valeria de Paiva, Richard Crouch, Mennatallah El-Assady
Advances in Natural Language Inference (NLI) have helped us understand what state-of-the-art models really learn and what their generalization power is.
no code implementations • WS 2019 • Aikaterini-Lida Kalouli, Rebecca Kehlbeck, Rita Sevastjanova, Katharina Kaiser, Georg A. Kaiser, Miriam Butt
The study of language change through parallel corpora can be advantageous for the analysis of complex interactions between time, text domain and language.
no code implementations • 29 Jul 2019 • Fabian Sperrle, Rita Sevastjanova, Rebecca Kehlbeck, Mennatallah El-Assady
The results show that experts prefer our system over existing solutions due to the speedup provided by the automatic suggestions and the tight integration between text and graph views.
no code implementations • ACL 2019 • Mennatallah El-Assady, Wolfgang Jentner, Fabian Sperrle, Rita Sevastjanova, Annette Hautli-Janisz, Miriam Butt, Daniel Keim
We present a modular framework for the rapid-prototyping of linguistic, web-based, visual analytics applications.