5 papers · 1 filter
Ready to Speak: Aligning LLMs for TTS-Friendly Text Generation
Thibaut Thonet, Jos Rozen, Laurent Besacier
Current Large Language Models (LLMs) are primarily optimized for written text, often producing outputs that are grammatically correct and helpful yet poorly suited for spoken deliv…
Findings of the Third Automatic Minuting (AutoMin) Challenge
Kartik Shinde, Laurent Besacier, Ondrej Bojar +2
This paper presents the third edition of AutoMin, a shared task on automatic meeting summarization into minutes. In 2025, AutoMin featured the main task of minuting, the creation o…
FaST: Feature-aware Sampling and Tuning for Personalized Preference Alignment with Limited Data
Thibaut Thonet, Germán Kruszewski, Jos Rozen +2
LLM-powered conversational assistants are often deployed in a one-size-fits-all manner, which fails to accommodate individual user preferences. Recently, LLM personalization -- tai…
Guaranteed Generation from Large Language Models
Minbeom Kim, Thibaut Thonet, Jos Rozen +3
As large language models (LLMs) are increasingly used across various applications, there is a growing need to control text generation to satisfy specific constraints or requirement…
ELITR-Bench: A Meeting Assistant Benchmark for Long-Context Language Models
Thibaut Thonet, Jos Rozen, Laurent Besacier
Research on Large Language Models (LLMs) has recently witnessed an increasing interest in extending the models' context size to better capture dependencies within long documents. W…