11 citations · 32 across the 8 of their papers we have counts for
5 papers · 1 filter
Temperature Matters: Enhancing Watermark Robustness Against Paraphrasing Attacks
Badr Youbi Idrissi, Monica Millunzi, Amelia Sorrenti +2
In the present-day scenario, Large Language Models (LLMs) are establishing their presence as powerful instruments permeating various sectors of society. While their utility offers…
From Bytes to Ideas: Language Modeling with Autoregressive U-Nets
Mathurin Videau, Badr Youbi Idrissi, Alessandro Leite +3
Tokenization imposes a fixed granularity on the input text, freezing how a language model operates on data and how far in the future it predicts. Byte Pair Encoding (BPE) and simil…
Better & Faster Large Language Models via Multi-token Prediction
Fabian Gloeckle, Badr Youbi Idrissi, Baptiste Rozière +2
Large language models such as GPT and Llama are trained with a next-token prediction loss. In this work, we suggest that training language models to predict multiple future tokens…
Masked Adversarial Generation for Neural Machine Translation
Badr Youbi Idrissi, Stéphane Clinchant
Attacking Neural Machine Translation models is an inherently combinatorial task on discrete sequences, solved with approximate heuristics. Most methods use the gradient to attack t…
VirAAL: Virtual Adversarial Active Learning For NLU
Gregory Senay, Badr Youbi Idrissi, Marine Haziza
This paper presents VirAAL, an Active Learning framework based on Adversarial Training. VirAAL aims to reduce the effort of annotation in Natural Language Understanding (NLU). VirA…