44 citations · 116 across the 19 of their papers we have counts for
4 papers · 1 filter
DelusionEval: Measuring Delusion-Linked Behaviors in AI Chatbots
Jared Moore, Andrea Mock, Yifan Mai +9
Mental health professionals have raised concerns about risks of psychological harm from interaction with large language models (LLMs), including "delusional spirals" in which conce…
Introducing v0.5 of the AI Safety Benchmark from MLCommons
Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed +97
This paper introduces v0.5 of the AI Safety Benchmark, which has been created by the MLCommons AI Safety Working Group. The AI Safety Benchmark has been designed to assess the safe…
LawInstruct: A Resource for Studying Language Model Adaptation to the Legal Domain
Joel Niklaus, Lucia Zheng, Arya D. McCarthy +7
Instruction tuning is an important step in making language models useful for direct user interaction. However, the legal domain is underrepresented in typical instruction datasets…
When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboards
Norah Alzahrani, Hisham Abdullah Alyahya, Yazeed Alnumay +9
Large Language Model (LLM) leaderboards based on benchmark rankings are regularly used to guide practitioners in model selection. Often, the published leaderboard rankings are take…