Overview - Interactive Knowledge Assistance Track (IKAT) 2025¶
Proceedings | Data | Runs | Participants
iKAT is the successor to the Conversational Assistance Track (CAsT). The fourth year of CAST aimed to add more conversational elements to the interaction streams, by introducing mixed initiatives (clarifications, and suggestions) to create multi-path, multi-turn conversations for each topic. TREC iKAT evolves CAsT into a new track to signal this new trajectory. iKAT aims to focus on supporting multi-path, multi-turn, multi-perspective conversations. That is for a given topic, the direction and the conversation that evolves depends not only on the prior responses but also on the user.
Track coordinator(s):
- Mohammad Aliannejadi, University of Amsterdam
- Simon Lupart, University of Amsterdam
- Marcel Gohsen, Bauhaus-Universität Weimar
- Zahra Abbasiantaeb, University of Amsterdam
- Nailia Mirzakhmedova, Bauhaus-Universität Weimar
- Johannes Kiesel, GESIS - Leibniz Institute for the Social Sciences
- Jeff Dalton, University of Edinburgh
Tasks:
trec2025-ikat-auto: Passage Ranking and Response Generationtrec2025-ikat-gen: Response Generation (only)trec2025-ikat-sim: Passage Ranking & Interactive Response Generation
Track Web Page: https://www.trecikat.com