activity
20222025
most citedWhat Type of Explanation Do Rejected Job Applicants Want? Implications for Explainable AI

1 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025

Evaluating Binary Decision Biases in Large Language Models: Implications for Fair Agent-Based Financial Simulations

Alicia Vidler, Toby Walsh

Large Language Models (LLMs) are increasingly being used to simulate human-like decision making in agent-based financial market models (ABMs). As models become more powerful and ac…

econ.GN20241 cited

The role of gender in promotion rates in the Australian Finance Industry

Cassandra Crowe, Belinda Middleweek, Laura Ryan +2

We surveyed Australian finance professionals and tested whether there are statistically significant differences in promotional propensity according to gender identity. The findings…

cs.GT2024

Non cooperative Liquidity Games and their application to bond market trading

Alicia Vidler, Toby Walsh

We present a new type of game, the Liquidity Game. We draw inspiration from the UK government bond market and apply game theoretic approaches to its analysis. In Liquidity Games, m…

q-fin.CP20241 cited

Modelling Opaque Bilateral Market Dynamics in Financial Trading: Insights from a Multi-Agent Simulation Study

Alicia Vidler, Toby Walsh

Exploring complex adaptive financial trading environments through multi-agent based simulation methods presents an innovative approach within the realm of quantitative finance. Des…

econ.GN20221 cited

What Type of Explanation Do Rejected Job Applicants Want? Implications for Explainable AI

Matthew Olckers, Alicia Vidler, Toby Walsh

Rejected job applicants seldom receive explanations from employers. Techniques from Explainable AI (XAI) could provide explanations at scale. Although XAI researchers have develope…