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20242026
most citedTowards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach

20 citations · 28 across the 4 of their papers we have counts for

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5 papers · 1 filter

cs.AI2026

Evaluating Language Models for Harmful Manipulation

Canfer Akbulut, Rasmi Elasmar, Abhishek Roy +9

Interest in the concept of AI-driven harmful manipulation is growing, yet current approaches to evaluating it are limited. This paper introduces a framework for evaluating harmful…

cs.AI2025

Toward an Evaluation Science for Generative AI Systems

Laura Weidinger, Inioluwa Deborah Raji, Hanna Wallach +7

There is an increasing imperative to anticipate and understand the performance and safety of generative AI systems in real-world deployment contexts. However, the current evaluatio…

cs.AI2024

STAR: SocioTechnical Approach to Red Teaming Language Models

Laura Weidinger, John Mellor, Bernat Guillen Pegueroles +9

This research introduces STAR, a sociotechnical framework that improves on current best practices for red teaming safety of large language models. STAR makes two key contributions:…

cs.AI2024

Operationalizing Contextual Integrity in Privacy-Conscious Assistants

Sahra Ghalebikesabi, Eugene Bagdasaryan, Ren Yi +10

Advanced AI assistants combine frontier LLMs and tool access to autonomously perform complex tasks on behalf of users. While the helpfulness of such assistants can increase dramati…

cs.AI2024

Holistic Safety and Responsibility Evaluations of Advanced AI Models

Laura Weidinger, Joslyn Barnhart, Jenny Brennan +16

Safety and responsibility evaluations of advanced AI models are a critical but developing field of research and practice. In the development of Google DeepMind's advanced AI models…