103 citations · 312 across the 26 of their papers we have counts for
29 papers
Self-Execution Simulation Improves Coding Models
Gallil Maimon, Ori Yoran, Felix Kreuk +4
A promising research direction in enabling LLMs to generate consistently correct code involves addressing their inability to properly estimate program execution, particularly for c…
Linguistically Informed Evaluation of Multilingual ASR for African Languages
Fei-Yueh Chen, Lateef Adeleke, C. M. Downey
Word Error Rate (WER) mischaracterizes ASR models' performance for African languages by combining phonological, tone, and other linguistic errors into a single lexical error. By co…
CWM: An Open-Weights LLM for Research on Code Generation with World Models
FAIR CodeGen team, Jade Copet, Quentin Carbonneaux +48
We release Code World Model (CWM), a 32-billion-parameter open-weights LLM, to advance research on code generation with world models. To improve code understanding beyond what can…
From KMMLU-Redux to KMMLU-Pro: A Professional Korean Benchmark Suite for LLM Evaluation
Seokhee Hong, Sunkyoung Kim, Guijin Son +3
The development of Large Language Models (LLMs) requires robust benchmarks that encompass not only academic domains but also industrial fields to effectively evaluate their applica…
Dialect Normalization using Large Language Models and Morphological Rules
Antonios Dimakis, John Pavlopoulos, Antonios Anastasopoulos
Natural language understanding systems struggle with low-resource languages, including many dialects of high-resource ones. Dialect-to-standard normalization attempts to tackle thi…
Auto-Regressive vs Flow-Matching: a Comparative Study of Modeling Paradigms for Text-to-Music Generation
Or Tal, Felix Kreuk, Yossi Adi
Recent progress in text-to-music generation has enabled models to synthesize high-quality musical segments, full compositions, and even respond to fine-grained control signals, e.g…
Multilingual Machine Translation with Open Large Language Models at Practical Scale: An Empirical Study
Menglong Cui, Pengzhi Gao, Wei Liu +2
Large language models (LLMs) have shown continuously improving multilingual capabilities, and even small-scale open-source models have demonstrated rapid performance enhancement. I…
When Every Token Counts: Optimal Segmentation for Low-Resource Language Models
Bharath Raj, Garvit Suri, Vikrant Dewangan +1
Traditional greedy tokenization methods have been a critical step in Natural Language Processing (NLP), influencing how text is converted into tokens and directly impacting model p…
The Llama 3 Herd of Models
Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri +556
Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models th…
Discrete Flow Matching
Itai Gat, Tal Remez, Neta Shaul +5
Despite Flow Matching and diffusion models having emerged as powerful generative paradigms for continuous variables such as images and videos, their application to high-dimensional…
Joint Audio and Symbolic Conditioning for Temporally Controlled Text-to-Music Generation
Or Tal, Alon Ziv, Itai Gat +2
We present JASCO, a temporally controlled text-to-music generation model utilizing both symbolic and audio-based conditions. JASCO can generate high-quality music samples condition…
Masked Audio Generation using a Single Non-Autoregressive Transformer
Alon Ziv, Itai Gat, Gael Le Lan +6
We introduce MAGNeT, a masked generative sequence modeling method that operates directly over several streams of audio tokens. Unlike prior work, MAGNeT is comprised of a single-st…
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…
Simple and Controllable Music Generation
Jade Copet, Felix Kreuk, Itai Gat +5
We tackle the task of conditional music generation. We introduce MusicGen, a single Language Model (LM) that operates over several streams of compressed discrete music representati…
Textually Pretrained Speech Language Models
Michael Hassid, Tal Remez, Tu Anh Nguyen +9
Speech language models (SpeechLMs) process and generate acoustic data only, without textual supervision. In this work, we propose TWIST, a method for training SpeechLMs using a war…
Audio Language Modeling using Perceptually-Guided Discrete Representations
Felix Kreuk, Yaniv Taigman, Adam Polyak +4
In this work, we study the task of Audio Language Modeling, in which we aim at learning probabilistic models for audio that can be used for generation and completion. We use a stat…
Augmentation Invariant Discrete Representation for Generative Spoken Language Modeling
Itai Gat, Felix Kreuk, Tu Anh Nguyen +5
Generative Spoken Language Modeling research focuses on optimizing speech Language Models (LMs) using raw audio recordings without accessing any textual supervision. Such speech LM…
AudioGen: Textually Guided Audio Generation
Felix Kreuk, Gabriel Synnaeve, Adam Polyak +6
We tackle the problem of generating audio samples conditioned on descriptive text captions. In this work, we propose AaudioGen, an auto-regressive generative model that generates a…
Formant Estimation and Tracking using Probabilistic Heat-Maps
Yosi Shrem, Felix Kreuk, Joseph Keshet
Formants are the spectral maxima that result from acoustic resonances of the human vocal tract, and their accurate estimation is among the most fundamental speech processing proble…
A Systematic Comparison of Phonetic Aware Techniques for Speech Enhancement
Or Tal, Moshe Mandel, Felix Kreuk +1
Speech enhancement has seen great improvement in recent years using end-to-end neural networks. However, most models are agnostic to the spoken phonetic content. Recently, several…
Self-supervised Speaker Diarization
Yehoshua Dissen, Felix Kreuk, Joseph Keshet
Over the last few years, deep learning has grown in popularity for speaker verification, identification, and diarization. Inarguably, a significant part of this success is due to t…
Correcting Mispronunciations in Speech using Spectrogram Inpainting
Talia Ben-Simon, Felix Kreuk, Faten Awwad +2
Learning a new language involves constantly comparing speech productions with reference productions from the environment. Early in speech acquisition, children make articulatory ad…
Textless Speech Emotion Conversion using Discrete and Decomposed Representations
Felix Kreuk, Adam Polyak, Jade Copet +7
Speech emotion conversion is the task of modifying the perceived emotion of a speech utterance while preserving the lexical content and speaker identity. In this study, we cast the…
Self-Supervised Contrastive Learning for Unsupervised Phoneme Segmentation
Felix Kreuk, Joseph Keshet, Yossi Adi
We propose a self-supervised representation learning model for the task of unsupervised phoneme boundary detection. The model is a convolutional neural network that operates direct…