14 citations · 27 across the 6 of their papers we have counts for
7 papers
ClinAgent: A ReAct-Based Agent for Conversational Access to Clinical Trial Information
Antonino Vaccarella, Riccardo Cantini, Domenico Talia +4
Querying clinical trial registries remains a manual and error-prone process, requiring researchers to navigate large volumes of semi-structured data without support for natural lan…
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…
Dynamic hashtag recommendation in social media with trend shift detection and adaptation
Riccardo Cantini, Fabrizio Marozzo, Alessio Orsino +2
Hashtag recommendation systems have emerged as a key tool for automatically suggesting relevant hashtags and enhancing content categorization and search. However, existing static m…
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…
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…
Detecting mental disorder on social media: a ChatGPT-augmented explainable approach
Loris Belcastro, Riccardo Cantini, Fabrizio Marozzo +2
In the digital era, the prevalence of depressive symptoms expressed on social media has raised serious concerns, necessitating advanced methodologies for timely detection. This pap…
Block size estimation for data partitioning in HPC applications using machine learning techniques
Riccardo Cantini, Fabrizio Marozzo, Alessio Orsino +5
The extensive use of HPC infrastructures and frameworks for running dataintensive applications has led to a growing interest in data partitioning techniques and strategies. In fact…