Thibaut Thonet

FaST: Feature-aware Sampling and Tuning for Personalized Preference Alignment with Limited Data LLM-powered conversational assistants are often deployed in a one-size-fits-all manner, which fails to accommodate individual user preferences. Recently, LLM personalization -- tailoring models to ali...

🎉 Delighted to share that our work “FaST: Feature-aware Sampling and Tuning for Personalized Preference Alignment with Limited Data” has been accepted to #EMNLP2025 main!

🧑🏻‍💻 Joint work with @germank.bsky.social, Jos Rozen, Pierre Erbacher, Marc Dymetman

📄 Preprint: arxiv.org/abs/2508.04698

🚀 A powerful and easy-to-build constrained speech LLM model. For multilingual SQA, we beat Microsoft-Phi and all unconstrained submissions on the SHORT track at IWSLT 2025 instruction-following track!

Presented this Thursday at ACL 2025 by myself and @beomseok-lee.bsky.social 🧵👇

Still possible to join this shared task !

Join AutoMin 2025 - 3d Run of the Automatic Minuting Shared Task at #SIGDIAL2025 to push the limits of LLMs in
📌 Meeting Summarization
📌 Meeting Question Answering
📅 Workshop: Aug. 28, 2025
ufal.github.io/automin-2025/
#NLP #LLMs #AI #AutoMin

Ad on research positions and internships at NAVER LABS Europe, Grenoble, France in February 2025

Welcome to NAVER LABS Europe on Bluesky! We chose 'LABS blue' to kickoff our posts & we'd appreciate it if you could share this one widely tinyurl.com/2nt9jdnv 😊 #hiring #jobs #internships

Internship: Advanced Constraint Processing in LLMs The ability to control the outputs of Large Language Models is a central topic in NLP and Machine Learning, with applications to safety, trustworthiness, reasoning, etc. Following […]

🚨 Excited about ML/NLP and looking for a research internship on controlled text generation?
Come work with us on advanced constraint processing in large language models at NAVER LABS Europe!

✨ Learn more and apply here: europe.naverlabs.com/job/2-7/