activity
20242026
collaborators

5 papers

cs.AI2026

A Natural Language Agentic Approach to Study Affective Polarization

Stephanie Anneris Malvicini, Ewelina Gajewska, Arda Derbent +3

Affective polarization has been central to political and social studies, with growing focus on social media, where partisan divisions are often exacerbated. Real-world studies tend…

cs.CL2025

AI Debaters are More Persuasive when Arguing in Alignment with Their Own Beliefs

María Victoria Carro, Denise Alejandra Mester, Facundo Nieto +9

The core premise of AI debate as a scalable oversight technique is that it is harder to lie convincingly than to refute a lie, enabling the judge to identify the correct position.…

cs.AI2025

Do Large Language Models Show Biases in Causal Learning? Insights from Contingency Judgment

María Victoria Carro, Denise Alejandra Mester, Francisca Gauna Selasco +4

Causal learning is the cognitive process of developing the capability of making causal inferences based on available information, often guided by normative principles. This process…

cs.AI2025

A Conceptual Framework for AI Capability Evaluations

María Victoria Carro, Denise Alejandra Mester, Francisca Gauna Selasco +7

As AI systems advance and integrate into society, well-designed and transparent evaluations are becoming essential tools in AI governance, informing decisions by providing evidence…

cs.AI2024

Do Large Language Models Show Biases in Causal Learning?

Maria Victoria Carro, Francisca Gauna Selasco, Denise Alejandra Mester +4

Causal learning is the cognitive process of developing the capability of making causal inferences based on available information, often guided by normative principles. This process…