27 citations · 35 across the 10 of their papers we have counts for
10 papers
Countering Reward Over-optimization in LLM with Demonstration-Guided Reinforcement Learning
Mathieu Rita, Florian Strub, Rahma Chaabouni +3
While Reinforcement Learning (RL) has been proven essential for tuning large language models (LLMs), it can lead to reward over-optimization (ROO). Existing approaches address ROO…
Language Evolution with Deep Learning
Mathieu Rita, Paul Michel, Rahma Chaabouni +3
Computational modeling plays an essential role in the study of language emergence. It aims to simulate the conditions and learning processes that could trigger the emergence of a s…
XLS-R fine-tuning on noisy word boundaries for unsupervised speech segmentation into words
Robin Algayres, Pablo Diego-Simon, Benoit Sagot +1
Due to the absence of explicit word boundaries in the speech stream, the task of segmenting spoken sentences into word units without text supervision is particularly challenging. I…
Generative Spoken Language Model based on continuous word-sized audio tokens
Robin Algayres, Yossi Adi, Tu Anh Nguyen +4
In NLP, text language models based on words or subwords are known to outperform their character-based counterparts. Yet, in the speech community, the standard input of spoken LMs a…
EXPRESSO: A Benchmark and Analysis of Discrete Expressive Speech Resynthesis
Tu Anh Nguyen, Wei-Ning Hsu, Antony D'Avirro +10
Recent work has shown that it is possible to resynthesize high-quality speech based, not on text, but on low bitrate discrete units that have been learned in a self-supervised fash…
ProsAudit, a prosodic benchmark for self-supervised speech models
Maureen de Seyssel, Marvin Lavechin, Hadrien Titeux +6
We present ProsAudit, a benchmark in English to assess structural prosodic knowledge in self-supervised learning (SSL) speech models. It consists of two subtasks, their correspondi…