3 papers
cs.CL2025
Factors affecting the in-context learning abilities of LLMs for dialogue state tracking
Pradyoth Hegde, Santosh Kesiraju, Jan Å vec +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
Å imon SedláÄek, Bolaji Yusuf, Ján Å vec +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…
eess.AS2024
The Second DISPLACE Challenge : DIarization of SPeaker and LAnguage in Conversational Environments
Shareef Babu Kalluri, Prachi Singh, Pratik Roy Chowdhuri +8
The DIarization of SPeaker and LAnguage in Conversational Environments (DISPLACE) 2024 challenge is the second in the series of DISPLACE challenges, which involves tasks of speaker…