10 citations · 15 across the 6 of their papers we have counts for
6 papers
ASSERT: Automated Safety Scenario Red Teaming for Evaluating the Robustness of Large Language Models
Alex Mei, Sharon Levy, William Yang Wang
As large language models are integrated into society, robustness toward a suite of prompts is increasingly important to maintain reliability in a high-variance environment.Robustne…
Let's Think Frame by Frame with VIP: A Video Infilling and Prediction Dataset for Evaluating Video Chain-of-Thought
Vaishnavi Himakunthala, Andy Ouyang, Daniel Rose +6
Despite exciting recent results showing vision-language systems' capacity to reason about images using natural language, their capacity for video reasoning remains under-explored.…
Visual Chain of Thought: Bridging Logical Gaps with Multimodal Infillings
Daniel Rose, Vaishnavi Himakunthala, Andy Ouyang +7
Recent advances in large language models elicit reasoning in a chain-of-thought that allows models to decompose problems in a human-like fashion. Though this paradigm improves mult…
Users are the North Star for AI Transparency
Alex Mei, Michael Saxon, Shiyu Chang +2
Despite widespread calls for transparent artificial intelligence systems, the term is too overburdened with disparate meanings to express precise policy aims or to orient concrete…
Foveate, Attribute, and Rationalize: Towards Physically Safe and Trustworthy AI
Alex Mei, Sharon Levy, William Yang Wang
Users' physical safety is an increasing concern as the market for intelligent systems continues to grow, where unconstrained systems may recommend users dangerous actions that can…
Mitigating Covertly Unsafe Text within Natural Language Systems
Alex Mei, Anisha Kabir, Sharon Levy +7
An increasingly prevalent problem for intelligent technologies is text safety, as uncontrolled systems may generate recommendations to their users that lead to injury or life-threa…