18 citations · 21 across the 10 of their papers we have counts for
6 papers · 1 filter
BetterBench: Assessing AI Benchmarks, Uncovering Issues, and Establishing Best Practices
Anka Reuel, Amelia Hardy, Chandler Smith +3
AI models are increasingly prevalent in high-stakes environments, necessitating thorough assessment of their capabilities and risks. Benchmarks are popular for measuring these attr…
TomOpt: Differential optimisation for task- and constraint-aware design of particle detectors in the context of muon tomography
Giles C. Strong, Maxime Lagrange, Aitor Orio +11
We describe a software package, TomOpt, developed to optimise the geometrical layout and specifications of detectors designed for tomography by scattering of cosmic-ray muons. The…
Measuring Free-Form Decision-Making Inconsistency of Language Models in Military Crisis Simulations
Aryan Shrivastava, Jessica Hullman, Max Lamparth
There is an increasing interest in using language models (LMs) for automated decision-making, with multiple countries actively testing LMs to aid in military crisis decision-making…
Human vs. Machine: Behavioral Differences Between Expert Humans and Language Models in Wargame Simulations
Max Lamparth, Anthony Corso, Jacob Ganz +3
To some, the advent of artificial intelligence (AI) promises better decision-making and increased military effectiveness while reducing the influence of human error and emotions. H…
Risks from Language Models for Automated Mental Healthcare: Ethics and Structure for Implementation
Declan Grabb, Max Lamparth, Nina Vasan
Amidst the growing interest in developing task-autonomous AI for automated mental health care, this paper addresses the ethical and practical challenges associated with the issue a…
Analyzing And Editing Inner Mechanisms Of Backdoored Language Models
Max Lamparth, Anka Reuel
Poisoning of data sets is a potential security threat to large language models that can lead to backdoored models. A description of the internal mechanisms of backdoored language m…