Argflow: A Toolkit for Deep Argumentative Explanations for Neural Networks. - Adam Dejl; Chloe He 002; Pranav Mangal; Hasan Mohsin; Bogdan Surdu; Eduard Voinea; Emanuele Albini; Piyawat Lertvittayakumjorn; Antonio Rago 001; Francesca Toni (AAMAS, 2021)

Treatment-RSPN: Recurrent Sum-Product Networks for Sequential Treatment Regimes. - Adam Dejl; Harsh Deep; Jonathan Fei; Ardavan Saeedi; Li-Wei H. Lehman (CoRR, 2022)

RadGraph2: Modeling Disease Progression in Radiology Reports via Hierarchical Information Extraction. - Sameer Tajdin Khanna; Adam Dejl; Kibo Yoon; Steven Q. H. Truong; Hanh Duong; Agustina Saenz; Pranav Rajpurkar (MLHC, 2023)

RadGraph2: Modeling Disease Progression in Radiology Reports via Hierarchical Information Extraction. - Sameer Tajdin Khanna; Adam Dejl; Kibo Yoon; Quoc Hung Truong; Hanh Duong; Agustina Saenz; Pranav Rajpurkar (CoRR, 2023)

CAFE: Conflict-Aware Feature-wise Explanations. - Adam Dejl; Hamed Ayoobi; Matthew Williams 001; Francesca Toni (CoRR, 2023)

A Knowledge Distillation Approach for Sepsis Outcome Prediction from Multivariate Clinical Time Series. - Anna Wong; Shu Ge; Nassim Oufattole; Adam Dejl; Megan Su; Ardavan Saeedi; Li-Wei H. Lehman (CoRR, 2023)

Contestable AI Needs Computational Argumentation. - Francesco Leofante; Hamed Ayoobi; Adam Dejl; Gabriel Freedman; Deniz Gorur; Junqi Jiang; Guilherme Paulino-Passos; Antonio Rago 001; Anna Rapberger; Fabrizio Russo 002; Xiang Yin 007; Dekai Zhang; et al. (KR, 2024)

Argumentative Large Language Models for Explainable and Contestable Decision-Making. - Gabriel Freedman; Adam Dejl; Deniz Gorur; Xiang Yin 007; Antonio Rago 001; Francesca Toni (CoRR, 2024)

Analyzing Key Neurons in Large Language Models. - Lihu Chen; Adam Dejl; Francesca Toni (CoRR, 2024)

Identifying Query-Relevant Neurons in Large Language Models for Long-Form Texts. - Lihu Chen; Adam Dejl; Francesca Toni (AAAI, 2025)

Argumentative Large Language Models for Explainable and Contestable Claim Verification. - Gabriel Freedman; Adam Dejl; Deniz Gorur; Xiang Yin 007; Antonio Rago 001; Francesca Toni (AAAI, 2025)

Hidden Conflicts in Neural Networks and their Implications for Explainability. - Adam Dejl; Dekai Zhang; Hamed Ayoobi; Matthew Williams 001; Francesca Toni (FAccT, 2025)

XAI-Units: Benchmarking Explainability Methods with Unit Tests. - Jun Rui Lee; Sadegh Emami; Michael David Hollins; Timothy C. H. Wong; Carlos Ignacio Villalobos Sánchez; Francesca Toni; Dekai Zhang; Adam Dejl (FAccT, 2025)

Heterogeneous graph neural networks with post-hoc explanations for multi-modal and explainable land use inference. - Xuehao Zhai; Junqi Jiang; Adam Dejl; Antonio Rago 001; Fangce Guo; Francesca Toni; Aruna Sivakumar (Inf. Fusion, 2025)