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cs.CL2025
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…
cs.CL2025
Is Reasoning All You Need? Probing Bias in the Age of Reasoning Language Models
Riccardo Cantini, Nicola Gabriele, Alessio Orsino +1
Reasoning Language Models (RLMs) have gained traction for their ability to perform complex, multi-step reasoning tasks through mechanisms such as Chain-of-Thought (CoT) prompting o…
cs.CL2025
Are Large Language Models Really Bias-Free? Jailbreak Prompts for Assessing Adversarial Robustness to Bias Elicitation
Riccardo Cantini, Giada Cosenza, Alessio Orsino +1
Large Language Models (LLMs) have revolutionized artificial intelligence, demonstrating remarkable computational power and linguistic capabilities. However, these models are inhere…