Selected publications
1. O. Camburu, T. Rocktäschel, T. Lukasiewicz, P. Blunsom. e-SNLI: Natural Language Inference with Natural Language Explanations. NeurIPS, 2018.
2. M. Kayser, B. Menzat, C. Emde, B. Bercean, A. Novak, A. Espinosa, B. Papiez, S. Gaube, T. Lukasiewicz, O. Camburu. Fool Me Once? Contrasting Textual and Visual Explanations in a Clinical Decision-Support Setting. EMNLP, 2024. Outstanding Paper Award.
3. P. Atanasova, O. Camburu, C. Lioma, T. Lukasiewicz, J. Simonsen, I. Augenstein. Faithfulness Tests for Natural Language Explanations. ACL, 2023.
4. N. Siegel, O. Camburu, N. Heess, M. Perez-Ortiz. The Probabilities Also Matter: A More Faithful Metric for Faithfulness of Free-Text Explanations in Large Language Models. ACL, 2024.
5. V. Swamy, D. Romano, B. Desikan, O. Camburu, T. Käser. From Explanations to Action: A Zero-Shot, Theory-Driven LLM Framework for Student Performance Feedback. AAAI Special Track on AI for Social Impact, 2025.
6. X. He, Y. Wu, O. Camburu, P. Minervini, P. Stenetorp. Using Natural Language Explanations to Improve Robustness of In-context Learning. ACL, 2024.
7. J. Solano, M. Sanni, O. Camburu, P. Minervini. SPARSEFIT: Few-shot Prompting with Sparse Fine-tuning for Jointly Generating Predictions and Natural Language Explanations. ACL, 2024.
8. M. Kayser, C. Emde, O. Camburu, G. Parsons, B. Papiez, T. Lukasiewicz. Explaining Chest X-ray Pathologies in Natural Language. MICCAI, 2022.
9. B. Majumder, O. Camburu, T. Lukasiewicz, J. McAuley. Knowledge-Grounded Self-Rationalization via Extractive and Natural Language Explanations. ICML, 2022.
10. Kayser, O. Camburu, L. Salewski, C. Emde, V. Do, Z. Akata, T. Lukasiewicz. e-ViL: A Dataset and Benchmark for Natural Language Explanations in Vision-Language Tasks. ICCV, 2021.
11. O. Camburu, B. Shillingford, P. Minervini, T. Lukasiewicz, P. Blunsom. Make Up Your Mind! Adversarial Generation of Inconsistent Natural Language Explanations. ACL, 2020.