461 citations · 674 across the 16 of their papers we have counts for
7 papers · 1 filter
RTTC: Reward-Guided Collaborative Test-Time Compute
J. Pablo Muñoz, Jinjie Yuan
Test-Time Compute (TTC) has emerged as a powerful paradigm for enhancing the performance of Large Language Models (LLMs) at inference, leveraging strategies such as Test-Time Train…
Inference-time sparse attention with asymmetric indexing
Pierre-Emmanuel Mazaré, Gergely Szilvasy, Maria Lomeli +4
Self-attention in transformer models is an incremental associative memory that maps key vectors to value vectors. One way to speed up self-attention is to employ GPU-compatible vec…
Libri-Light: A Benchmark for ASR with Limited or No Supervision
Jacob Kahn, Morgane Rivière, Weiyi Zheng +12
We introduce a new collection of spoken English audio suitable for training speech recognition systems under limited or no supervision. It is derived from open-source audio books f…
Reference-less Quality Estimation of Text Simplification Systems
Louis Martin, Samuel Humeau, Pierre-Emmanuel Mazaré +3
The evaluation of text simplification (TS) systems remains an open challenge. As the task has common points with machine translation (MT), TS is often evaluated using MT metrics su…
Learning from Dialogue after Deployment: Feed Yourself, Chatbot!
Braden Hancock, Antoine Bordes, Pierre-Emmanuel Mazaré +1
The majority of conversations a dialogue agent sees over its lifetime occur after it has already been trained and deployed, leaving a vast store of potential training signal untapp…
Training Millions of Personalized Dialogue Agents
Pierre-Emmanuel Mazaré, Samuel Humeau, Martin Raison +1
Current dialogue systems are not very engaging for users, especially when trained end-to-end without relying on proactive reengaging scripted strategies. Zhang et al. (2018) showed…
Weaver: Deep Co-Encoding of Questions and Documents for Machine Reading
Martin Raison, Pierre-Emmanuel Mazaré, Rajarshi Das +1
This paper aims at improving how machines can answer questions directly from text, with the focus of having models that can answer correctly multiple types of questions and from va…