2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CL2025
Factors affecting the in-context learning abilities of LLMs for dialogue state tracking
Pradyoth Hegde, Santosh Kesiraju, Jan Švec +5
This study explores the application of in-context learning (ICL) to the dialogue state tracking (DST) problem and investigates the factors that influence its effectiveness. We use…
eess.AS2025
Approaching Dialogue State Tracking via Aligning Speech Encoders and LLMs
Šimon Sedláček, Bolaji Yusuf, Ján Švec +4
In this work, we approach spoken Dialogue State Tracking (DST) by bridging the representation spaces of speech encoders and LLMs via a small connector module, with a focus on fully…
cs.CL2021★ 2 cited
Comparison of Czech Transformers on Text Classification Tasks
Jan Lehečka, Jan Švec
In this paper, we present our progress in pre-training monolingual Transformers for Czech and contribute to the research community by releasing our models for public. The need for…