We are excited to announce that our paper, "Adapting Sequential Recommender Models to Content Recommendation in Chat Data using Non-Item Page-Models", has been accepted at the KARS Workshop at the RecSys 24. In our work, we adapt sequential recommender models for content recommendation in twitch and multiple other chat systems by modeling messages as non-item pages with pretrained embeddings.

We are proud to announce that our chair will be presenting their research with three papers at the ECML PKDD 2024 conference in Vilnius.

Our paper proposes a novel adapter-based approach to integrate knowledge from knowledge graphs into large language models (LLMs).