Zachary Horvitz

Research Interests

I am excited about inference-time scaling, text diffusion models, building robust verifiers for text generation tasks, and improving language models with synthetic data!

Selected Publications

• A General Framework for Inference-time Scaling and Steering of Diffusion Models (ICML 2025)
  Raghav Singhal, Zachary Horvitz, et al. [arXiv]
• StyleDistance: Stronger Content-Independent Style Embeddings with Synthetic Parallel Examples (NAACL 2025)
  Ajay Patel, Jiacheng Zhu, Justin Qiu, Zachary Horvitz, et al. [Semantic Scholar]
• TinyStyler: Efficient Few-Shot Text Style Transfer with Authorship Embeddings (EMNLP 2024)
  Zachary Horvitz, et al. [ACL Anthology]
• ParaGuide: Guided Diffusion Paraphrasers for Plug-and-Play Textual Style Transfer (AAAI 2024)
  Zachary Horvitz, et al. [AAAI]
• Getting Serious about Humor: Crafting Humor Datasets with Unfunny Large Language Models (ACL 2024, Outstanding Paper Award)
  Zachary Horvitz, et al. [ACL Anthology]

Experience & Education

Prior to my PhD, I was a Machine Learning Engineer and then Research Lead at Rad AI.

I completed my ScM and AB at Brown University, where I studied Computer Science and Anthropology. During that time, I wrote for The Brown Noser, Brown's satirical newspaper.