most citedBenchmarking Adversarial Robustness to Bias Elicitation in Large Language Models: Scalable Automated Assessment with LLM-as-a-Judge

6 citations · 6 across the 1 of their papers we have counts for

collaborators

1 paper

cs.CL2025★ 6 cited

Benchmarking Adversarial Robustness to Bias Elicitation in Large Language Models: Scalable Automated Assessment with LLM-as-a-Judge

Riccardo Cantini, Alessio Orsino, Massimo Ruggiero +1

The growing integration of Large Language Models (LLMs) into critical societal domains has raised concerns about embedded biases that can perpetuate stereotypes and undermine fairn…