24 papers
Post-Training Speech Enhancement Language Models with Perceptual Rewards
Frédéric Berdoz, Luca A. Lanzendörfer, Antonis Asonitis +1
Speech enhancement language models achieve strong results when trained on discrete audio tokens, but their optimization relies on token-level cross-entropy rather than the perceptu…
Data Attribution in Large Language Models via Bidirectional Gradient Optimization
Frédéric Berdoz, Luca A. Lanzendörfer, Kaan Bayraktar +1
Large Language Models (LLMs) are increasingly deployed across diverse applications, raising critical questions for governance, accountability, and data provenance. Understanding wh…
Reasoning Structure of Large Language Models
Frédéric Berdoz, Luca A. Lanzendörfer, Fabian Farestam +1
Large reasoning models (LRMs) are often evaluated using metrics such as final-answer accuracy or token count. However, identical scores on these metrics can hide fundamentally diff…
Alignment-Aware Decoding
Frédéric Berdoz, Luca A. Lanzendörfer, René Caky +1
Alignment of large language models remains a central challenge in natural language processing. Preference optimization has emerged as a popular and effective method for improving a…
WorldSpeech: A Multilingual Speech Corpus from Around the World
Antonis Asonitis, Luca A. Lanzendörfer, Frédéric Berdoz +1
Automatic speech recognition (ASR) performs well for high-resource languages with abundant paired audio-transcript data, but its accuracy degrades sharply for most languages due to…
Adapting Neural Audio Codecs to EEG
Ard Kastrati, Luca Lanzendörfer, Riccardo Rigoni +2
EEG and audio are inherently distinct modalities, differing in sampling rate, channel structure, and scale. Yet, we show that pretrained neural audio codecs can serve as effective…