Oana-Maria Camburu
Senior Research Fellow with a Leverhulme Early Career Fellowship, University College London
I work mainly on Explainable AI, building neural networks that generate human-like explanations for their predictions. I did my Ph.D. on "Explaining Deep Neural Networks", working with Prof. Phil Blunsom and Prof. Thomas Lukasiewicz at the Department of Computer Science, University of Oxford.
Selected work
For the full list, see my Google Scholar.
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Most recent
B. Majumder, O. Camburu, T. Lukasiewicz, J. McAuley. Knowledge-Grounded Self-Rationalization via Extractive and Natural Language Explanations. In ICML, 2022.
Other relevant work
O. Camburu. Explaining Deep Neural Networks. PhD Thesis, University of Oxford, 2020.
O. Camburu, T. Rocktaschel, T. Lukasiewicz, P. Blunsom. e-SNLI: Natural Language Inference with Natural Language Explanations. In NeurIPS, 2018.
O. Camburu, B. Shillingford, P. Minervini, T. Lukasiewicz, P. Blunsom. Make Up Your Mind! Adversarial Generation of Inconsistent Natural Language Explanations. In ACL, 2020.
M. 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. In ICCV, 2021.
M. Kayser, C. Emde, O. Camburu, G. Parsons, B. Papiez, T. Lukasiewicz. Explaining Chest X-ray Pathologies in Natural Language. In MICCAI, 2022.
L. Sha, O. Camburu, T. Lukasiewicz. Learning from the Best: Rationalising Prediction by Information Calibration. In AAAI, 2020.
J. Mao, J. Huang, A. Toshev, O. Camburu, A. Yuille, K. Murphy. Generation and Comprehension of Unambiguous Object Descriptions. In CVPR, 2016.
V. Kocijan, A. Cretu, O. Camburu, Y. Yordanov, T. Lukasiewicz. A Surprisingly Robust Trick for the Winograd Schema Challenge. In ACL, 2019.
V. Kocijan, O. Camburu, A. Cretu, Y. Yordanov, P. Blunsom, T. Lukasiewicz. WikiCREM: A Large Unsupervised Corpus for Coreference Resolution. In EMNLP, 2019.
V. Kocijan, O. Camburu, T. Lukasiewicz. The Gap on GAP. Tackling the Problem of Differing Data Distributions in Bias-Measuring Datasets. In AAAI, 2020.