58 citations · 120 across the 59 of their papers we have counts for
5 papers · 1 filter
LR-DWM: Efficient Watermarking for Diffusion Language Models
Ofek Raban, Ethan Fetaya, Gal Chechik
Watermarking (WM) is a critical mechanism for detecting and attributing AI-generated content. Current WM methods for Large Language Models (LLMs) are predominantly tailored for aut…
Knowing Before Saying: LLM Representations Encode Information About Chain-of-Thought Success Before Completion
Anum Afzal, Florian Matthes, Gal Chechik +1
We investigate whether the success of a zero-shot Chain-of-Thought (CoT) process can be predicted before completion. We discover that a probing classifier, based on LLM representat…
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…
Classifier-Guided Captioning Across Modalities
Ariel Shaulov, Tal Shaharabany, Eitan Shaar +2
Most current captioning systems use language models trained on data from specific settings, such as image-based captioning via Amazon Mechanical Turk, limiting their ability to gen…
Linguistic Binding in Diffusion Models: Enhancing Attribute Correspondence through Attention Map Alignment
Royi Rassin, Eran Hirsch, Daniel Glickman +3
Text-conditioned image generation models often generate incorrect associations between entities and their visual attributes. This reflects an impaired mapping between linguistic bi…