34 citations · 75 across the 8 of their papers we have counts for
8 papers
LLM-grounded Video Diffusion Models
Long Lian, Baifeng Shi, Adam Yala +2
Text-conditioned diffusion models have emerged as a promising tool for neural video generation. However, current models still struggle with intricate spatiotemporal prompts and oft…
Conformal Language Modeling
Victor Quach, Adam Fisch, Tal Schuster +4
We propose a novel approach to conformal prediction for generative language models (LMs). Standard conformal prediction produces prediction sets -- in place of single predictions -…
LLM-grounded Diffusion: Enhancing Prompt Understanding of Text-to-Image Diffusion Models with Large Language Models
Long Lian, Boyi Li, Adam Yala +1
Recent advancements in text-to-image diffusion models have yielded impressive results in generating realistic and diverse images. However, these models still struggle with complex…
PEOPL: Characterizing Privately Encoded Open Datasets with Public Labels
Homa Esfahanizadeh, Adam Yala, Rafael G. L. D'Oliveira +8
Allowing organizations to share their data for training of machine learning (ML) models without unintended information leakage is an open problem in practice. A promising technique…
AI Gone Astray: Technical Supplement
Janice Yang, Ludvig Karstens, Casey Ross +1
This study is a technical supplement to "AI gone astray: How subtle shifts in patient data send popular algorithms reeling, undermining patient safety." from STAT News, which inves…
Syfer: Neural Obfuscation for Private Data Release
Adam Yala, Victor Quach, Homa Esfahanizadeh +5
Balancing privacy and predictive utility remains a central challenge for machine learning in healthcare. In this paper, we develop Syfer, a neural obfuscation method to protect aga…
NeuraCrypt: Hiding Private Health Data via Random Neural Networks for Public Training
Adam Yala, Homa Esfahanizadeh, Rafael G. L. D' Oliveira +6
Balancing the needs of data privacy and predictive utility is a central challenge for machine learning in healthcare. In particular, privacy concerns have led to a dearth of public…
Improving Information Extraction by Acquiring External Evidence with Reinforcement Learning
Karthik Narasimhan, Adam Yala, Regina Barzilay
Most successful information extraction systems operate with access to a large collection of documents. In this work, we explore the task of acquiring and incorporating external evi…