Search Results for author: Tal Remez

Found 25 papers, 10 papers with code

The Larger the Better? Improved LLM Code-Generation via Budget Reallocation

no code implementations31 Mar 2024 Michael Hassid, Tal Remez, Jonas Gehring, Roy Schwartz, Yossi Adi

On the other hand, in scenarios where unit-tests are unavailable, a ranking-based selection of candidates from the smaller model falls short of the performance of a single output from larger ones.

Code Generation

Masked Audio Generation using a Single Non-Autoregressive Transformer

no code implementations9 Jan 2024 Alon Ziv, Itai Gat, Gael Le Lan, Tal Remez, Felix Kreuk, Alexandre Défossez, Jade Copet, Gabriel Synnaeve, Yossi Adi

We introduce MAGNeT, a masked generative sequence modeling method that operates directly over several streams of audio tokens.

Audio Generation

Code Llama: Open Foundation Models for Code

2 code implementations24 Aug 2023 Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, Sten Sootla, Itai Gat, Xiaoqing Ellen Tan, Yossi Adi, Jingyu Liu, Romain Sauvestre, Tal Remez, Jérémy Rapin, Artyom Kozhevnikov, Ivan Evtimov, Joanna Bitton, Manish Bhatt, Cristian Canton Ferrer, Aaron Grattafiori, Wenhan Xiong, Alexandre Défossez, Jade Copet, Faisal Azhar, Hugo Touvron, Louis Martin, Nicolas Usunier, Thomas Scialom, Gabriel Synnaeve

We release Code Llama, a family of large language models for code based on Llama 2 providing state-of-the-art performance among open models, infilling capabilities, support for large input contexts, and zero-shot instruction following ability for programming tasks.

16k Code Generation +1

EXPRESSO: A Benchmark and Analysis of Discrete Expressive Speech Resynthesis

no code implementations10 Aug 2023 Tu Anh Nguyen, Wei-Ning Hsu, Antony D'Avirro, Bowen Shi, Itai Gat, Maryam Fazel-Zarani, Tal Remez, Jade Copet, Gabriel Synnaeve, Michael Hassid, Felix Kreuk, Yossi Adi, Emmanuel Dupoux

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 fashion and can therefore capture expressive aspects of speech that are hard to transcribe (prosody, voice styles, non-verbal vocalization).

Resynthesis Speech Synthesis

AudioScopeV2: Audio-Visual Attention Architectures for Calibrated Open-Domain On-Screen Sound Separation

no code implementations20 Jul 2022 Efthymios Tzinis, Scott Wisdom, Tal Remez, John R. Hershey

We identify several limitations of previous work on audio-visual on-screen sound separation, including the coarse resolution of spatio-temporal attention, poor convergence of the audio separation model, limited variety in training and evaluation data, and failure to account for the trade off between preservation of on-screen sounds and suppression of off-screen sounds.

Improving On-Screen Sound Separation for Open-Domain Videos with Audio-Visual Self-Attention

no code implementations17 Jun 2021 Efthymios Tzinis, Scott Wisdom, Tal Remez, John R. Hershey

We introduce a state-of-the-art audio-visual on-screen sound separation system which is capable of learning to separate sounds and associate them with on-screen objects by looking at in-the-wild videos.

Unsupervised Pre-training

Into the Wild with AudioScope: Unsupervised Audio-Visual Separation of On-Screen Sounds

no code implementations ICLR 2021 Efthymios Tzinis, Scott Wisdom, Aren Jansen, Shawn Hershey, Tal Remez, Daniel P. W. Ellis, John R. Hershey

For evaluation and semi-supervised experiments, we collected human labels for presence of on-screen and off-screen sounds on a small subset of clips.

Scene Understanding

Class-Aware Fully-Convolutional Gaussian and Poisson Denoising

1 code implementation20 Aug 2018 Tal Remez, Or Litany, Raja Giryes, Alex M. Bronstein

We propose a fully-convolutional neural-network architecture for image denoising which is simple yet powerful.

Image Denoising

Efficient Deformable Shape Correspondence via Kernel Matching

1 code implementation25 Jul 2017 Zorah Lähner, Matthias Vestner, Amit Boyarski, Or Litany, Ron Slossberg, Tal Remez, Emanuele Rodolà, Alex Bronstein, Michael Bronstein, Ron Kimmel, Daniel Cremers

We present a method to match three dimensional shapes under non-isometric deformations, topology changes and partiality.

Deep Convolutional Denoising of Low-Light Images

2 code implementations6 Jan 2017 Tal Remez, Or Litany, Raja Giryes, Alex M. Bronstein

Poisson distribution is used for modeling noise in photon-limited imaging.

Astronomy Denoising

Deep Class Aware Denoising

1 code implementation6 Jan 2017 Tal Remez, Or Litany, Raja Giryes, Alex M. Bronstein

We further show that a significant boost in performance of up to $0. 4$ dB PSNR can be achieved by making our network class-aware, namely, by fine-tuning it for images belonging to a specific semantic class.

Image Denoising Image Enhancement

Cloud Dictionary: Sparse Coding and Modeling for Point Clouds

3 code implementations15 Dec 2016 Or Litany, Tal Remez, Alex Bronstein

With the development of range sensors such as LIDAR and time-of-flight cameras, 3D point cloud scans have become ubiquitous in computer vision applications, the most prominent ones being gesture recognition and autonomous driving.

Autonomous Driving Denoising +1

Image reconstruction from dense binary pixels

no code implementations6 Dec 2015 Or Litany, Tal Remez, Alex Bronstein

Recently, the dense binary pixel Gigavision camera had been introduced, emulating a digital version of the photographic film.

Image Reconstruction

ASIST: Automatic Semantically Invariant Scene Transformation

no code implementations4 Dec 2015 Or Litany, Tal Remez, Daniel Freedman, Lior Shapira, Alex Bronstein, Ran Gal

We present ASIST, a technique for transforming point clouds by replacing objects with their semantically equivalent counterparts.


Spatially Coherent Random Forests

no code implementations9 Nov 2015 Tal Remez, Shai Avidan

Each tree in the forest produces a segmentation of the image plane and the boundaries of the segmentations of all trees are aggregated to produce a final hierarchical contour map.


A Picture is Worth a Billion Bits: Real-Time Image Reconstruction from Dense Binary Pixels

no code implementations15 Oct 2015 Tal Remez, Or Litany, Alex Bronstein

In this work, we study a variant of a sensor with binary threshold pixels and propose a reconstruction algorithm combining an ML data fitting term with a sparse synthesis prior.

Image Reconstruction Quantization

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