Publications

5 distinct works, with publication and preprint status noted below. Google Scholar

1. Investigating Knowledge Transfer Across Interactive Dialogue Games

   Filippo Momentè, Mir Nafis Sharear Shopnil, Andrea de Varda, Pavel Merinov, Raffaella Bernardi, Oswald Lanz, Alessandro Suglia, Alessandro Torcinovich

   arXiv:2608.23969 · Preprint · August 2026

   Joint first authorship: Filippo Momentè and Mir Nafis Sharear Shopnil.

   Studies transfer between dialogue games through fine-tuning, task-transfer graphs, and task vectors.

   arXiv · PDF

2. Evidence-Grounded Multimodal Misinformation Detection with Attention-Based GNNs

   Sharad Duwal, Mir Nafis Sharear Shopnil, Abhishek Tyagi, Adiba Mahbub Proma

   IEEE/CVF CVPR Workshops (PP-MisDet), 2026, pp. 10994–11003

   Evidence-grounded prompting and graph-based comparison of claims and evidence for multimodal misinformation detection.

   Proceedings · PDF

3. MERIT: Modular Framework for Multimodal Misinformation Detection with Web-Grounded Reasoning

   Mir Nafis Sharear Shopnil, Sharad Duwal, Abhishek Tyagi, Adiba Mahbub Proma

   arXiv:2510.17590 · Preprint · 2025, revised April 2026

   A four-module framework for multimodal misinformation detection with web-grounded verification and citation-linked rationales.

   arXiv · PDF · Code

4. Reflections from the 2025 EcoHack: AI & LLM Hackathon for Applications in Evidence-based Ecological Research & Practice

   Jennifer D’Souza et al., including Mir Nafis Sharear Shopnil

   EcoEvoRxiv · Preprint · April 2025 · Not peer reviewed

   A collaborative report on eleven hackathon team projects exploring AI and large language models for ecological research and practice.

   EcoEvoRxiv · DOI · PDF

5. Demystifying Black-box Learning Models of Rumor Detection from Social Media Posts

   Faiza Tafannum, Mir Nafis Sharear Shopnil, Anika Salsabil, Navid Ahmed, Md. Golam Rabiul Alam, Md Tanzim Reza

   IEEE UEMCON, 2021, pp. 358–364

   Explainable-AI methods for interpreting rumor-detection models trained on social media posts.

   DOI