3 citations · 3 across the 5 of their papers we have counts for
6 papers
Equalized Generative Treatment: Matching f-divergences for Fairness in Generative Models
Alexandre Verine, Rafael Pinot, Florian Le Bronnec
Fairness is a crucial concern for generative models, which not only reflect but can also amplify societal and cultural biases. Existing fairness notions for generative models are l…
Improving Diversity in Language Models: When Temperature Fails, Change the Loss
Alexandre Verine, Florian Le Bronnec, Kunhao Zheng +3
Increasing diversity in language models is a challenging yet essential objective. A common approach is to raise the decoding temperature. In this work, we investigate this approach…
Improving Discriminator Guidance in Diffusion Models
Alexandre Verine, Ahmed Mehdi Inane, Florian Le Bronnec +2
Discriminator Guidance has become a popular method for efficiently refining pre-trained Score-Matching Diffusion models. However, in this paper, we demonstrate that the standard im…
SCOPE: A Self-supervised Framework for Improving Faithfulness in Conditional Text Generation
Song Duong, Florian Le Bronnec, Alexandre Allauzen +4
Large Language Models (LLMs), when used for conditional text generation, often produce hallucinations, i.e., information that is unfaithful or not grounded in the input context. Th…
Exploring Precision and Recall to assess the quality and diversity of LLMs
Florian Le Bronnec, Alexandre Verine, Benjamin Negrevergne +2
We introduce a novel evaluation framework for Large Language Models (LLMs) such as \textsc{Llama-2} and \textsc{Mistral}, focusing on importing Precision and Recall metrics from im…
LOCOST: State-Space Models for Long Document Abstractive Summarization
Florian Le Bronnec, Song Duong, Mathieu Ravaut +6
State-space models are a low-complexity alternative to transformers for encoding long sequences and capturing long-term dependencies. We propose LOCOST: an encoder-decoder architec…