34 citations · 58 across the 22 of their papers we have counts for
27 papers
PromptEvolver: Prompt Inversion through Evolutionary Optimization in Natural-Language Space
Asaf Buchnick, Aviv Shamsian, Aviv Navon +1
Text-to-image generation has progressed rapidly, but faithfully generating complex scenes requires extensive trial-and-error to find the exact prompt. In the prompt inversion task,…
Drax: Speech Recognition with Discrete Flow Matching
Aviv Navon, Aviv Shamsian, Neta Glazer +4
Diffusion and flow-based non-autoregressive (NAR) models have shown strong promise in large language modeling, however, their potential for automatic speech recognition (ASR) remai…
Beyond Transcription: Mechanistic Interpretability in ASR
Neta Glazer, Yael Segal-Feldman, Hilit Segev +6
Interpretability methods have recently gained significant attention, particularly in the context of large language models, enabling insights into linguistic representations, error…
UmbraTTS: Adapting Text-to-Speech to Environmental Contexts with Flow Matching
Neta Glazer, Aviv Navon, Yael Segal +6
Recent advances in Text-to-Speech (TTS) have enabled highly natural speech synthesis, yet integrating speech with complex background environments remains challenging. We introduce…
GradMetaNet: An Equivariant Architecture for Learning on Gradients
Yoav Gelberg, Yam Eitan, Aviv Navon +5
Gradients of neural networks encode valuable information for optimization, editing, and analysis of models. Therefore, practitioners often treat gradients as inputs to task-specifi…
FlowTSE: Target Speaker Extraction with Flow Matching
Aviv Navon, Aviv Shamsian, Yael Segal-Feldman +3
Target speaker extraction (TSE) aims to isolate a specific speaker's speech from a mixture using speaker enrollment as a reference. While most existing approaches are discriminativ…