collaborators

5 papers

cs.AI2026

Closing the AI Trust Gap: The Case for Independent Certification for Trustworthy AI

Trisevgeni Papakonstantinou, Cansu Canca, Farah Nanji +14

Over the past decade, responsible AI (RAI) has produced a substantial body of practice for identifying and mitigating the risks AI poses in high-stakes settings. Yet this work has…

cs.CL2026

Beyond Topical Similarity: Contrastive Evidence Retrieval with Interpretable Attention Alignment in RAG

Francielle Vargas, João Robiatti, Diego Alves +6

Ensuring factuality and interpretability in RAG remains an open and urgent problem. We introduce Contrastive Evidence Rationale Attention (CERA), the first retrieval framework to e…

cs.CL2026

Self-Explaining Hate Speech Detection with Moral Rationales

Francielle Vargas, Jackson Trager, Diego Alves +6

Existing hate speech detection models are often opaque and rely on surface-level lexical cues, which makes them vulnerable to spurious correlations and limits robustness, interpret…

cs.CL2025

Factuality and Transparency Are All RAG Needs! Self-Explaining Contrastive Evidence Re-ranking

Francielle Vargas, Daniel Pedronette

This extended abstract introduces Self-Explaining Contrastive Evidence Re-Ranking (CER), a novel method that restructures retrieval around factual evidence by fine-tuning embedding…

cs.CL2025

MFTCXplain: A Multilingual Benchmark Dataset for Evaluating the Moral Reasoning of LLMs through Multi-hop Hate Speech Explanation

Jackson Trager, Francielle Vargas, Diego Alves +6

Ensuring the moral reasoning capabilities of Large Language Models (LLMs) is a growing concern as these systems are used in socially sensitive tasks. Nevertheless, current evaluati…