activity
20222025
most citedDiffusion Lens: Interpreting Text Encoders in Text-to-Image Pipelines

6 citations · 11 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2025

DeLeaker: Dynamic Inference-Time Reweighting For Semantic Leakage Mitigation in Text-to-Image Models

Mor Ventura, Michael Toker, Or Patashnik +2

Text-to-Image (T2I) models have advanced rapidly, yet they remain vulnerable to semantic leakage, the unintended transfer of semantically related features between distinct entities…

cs.CL2025

Follow the Flow: On Information Flow Across Textual Tokens in Text-to-Image Models

Guy Kaplan, Michael Toker, Yuval Reif +2

Text-to-image generation models suffer from alignment problems, where generated images fail to accurately capture the objects and relations in the text prompt. Prior work has focus…

cs.CL2025

Padding Tone: A Mechanistic Analysis of Padding Tokens in T2I Models

Michael Toker, Ido Galil, Hadas Orgad +4

Text-to-image (T2I) diffusion models rely on encoded prompts to guide the image generation process. Typically, these prompts are extended to a fixed length by adding padding tokens…

cs.CV2024★ 1 cited

NL-Eye: Abductive NLI for Images

Mor Ventura, Michael Toker, Nitay Calderon +3

Will a Visual Language Model (VLM)-based bot warn us about slipping if it detects a wet floor? Recent VLMs have demonstrated impressive capabilities, yet their ability to infer out…

cs.CL2024★ 4 cited

LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations

Hadas Orgad, Michael Toker, Zorik Gekhman +4

Large language models (LLMs) often produce errors, including factual inaccuracies, biases, and reasoning failures, collectively referred to as "hallucinations". Recent studies have…

cs.CV2024★ 6 cited

Diffusion Lens: Interpreting Text Encoders in Text-to-Image Pipelines

Michael Toker, Hadas Orgad, Mor Ventura +2

Text-to-image diffusion models (T2I) use a latent representation of a text prompt to guide the image generation process. However, the process by which the encoder produces the text…

cs.CL2022

TRBLLmaker -- Transformer Reads Between Lyrics Lines maker

Mor Ventura, Michael Toker

Even for us, it can be challenging to comprehend the meaning of songs. As part of this project, we explore the process of generating the meaning of songs. Despite the widespread us…