Oana-Maria Camburu

662 total citations
15 papers, 227 citations indexed

About

Oana-Maria Camburu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Control and Systems Engineering. According to data from OpenAlex, Oana-Maria Camburu has authored 15 papers receiving a total of 227 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 2 papers in Computer Vision and Pattern Recognition and 1 paper in Control and Systems Engineering. Recurrent topics in Oana-Maria Camburu's work include Topic Modeling (11 papers), Natural Language Processing Techniques (7 papers) and Explainable Artificial Intelligence (XAI) (6 papers). Oana-Maria Camburu is often cited by papers focused on Topic Modeling (11 papers), Natural Language Processing Techniques (7 papers) and Explainable Artificial Intelligence (XAI) (6 papers). Oana-Maria Camburu collaborates with scholars based in United Kingdom, Austria and United States. Oana-Maria Camburu's co-authors include Thomas Lukasiewicz, Phil Blunsom, Tim Rocktäschel, Lei Sha, Zeynep Akata, Jakob Grue Simonsen, Pepa Atanasova, Christina Lioma, Isabelle Augenstein and Yordan Yordanov and has published in prestigious journals such as Artificial Intelligence, 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and Research at the University of Copenhagen (University of Copenhagen).

In The Last Decade

Oana-Maria Camburu

12 papers receiving 217 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Oana-Maria Camburu United Kingdom 5 212 57 14 10 6 15 227
Jasmijn Bastings United States 5 164 0.8× 37 0.6× 15 1.1× 8 0.8× 8 1.3× 8 195
Dor Muhlgay Israel 2 104 0.5× 40 0.7× 23 1.6× 6 0.6× 5 0.8× 2 154
Daniel Deutsch United States 9 211 1.0× 35 0.6× 23 1.6× 4 0.4× 3 0.5× 31 226
Piyawat Lertvittayakumjorn United Kingdom 6 105 0.5× 21 0.4× 14 1.0× 4 0.4× 7 1.2× 19 127
Rongzhong Lian Hong Kong 5 231 1.1× 53 0.9× 24 1.7× 2 0.2× 2 0.3× 12 247
Or Honovich Israel 7 199 0.9× 40 0.7× 29 2.1× 2 0.2× 4 0.7× 10 221
Potsawee Manakul United Kingdom 5 130 0.6× 9 0.2× 17 1.2× 7 0.7× 16 2.7× 13 173
Peter Hase United States 5 119 0.6× 32 0.6× 5 0.4× 6 0.6× 7 1.2× 7 138
Khalid Almubarak Saudi Arabia 4 183 0.9× 31 0.5× 13 0.9× 1 0.1× 11 1.8× 9 217
Rangan Majumder Finland 5 210 1.0× 86 1.5× 32 2.3× 2 0.2× 2 0.3× 5 223

Countries citing papers authored by Oana-Maria Camburu

Since Specialization
Citations

This map shows the geographic impact of Oana-Maria Camburu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Oana-Maria Camburu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Oana-Maria Camburu more than expected).

Fields of papers citing papers by Oana-Maria Camburu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Oana-Maria Camburu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Oana-Maria Camburu. The network helps show where Oana-Maria Camburu may publish in the future.

Co-authorship network of co-authors of Oana-Maria Camburu

This figure shows the co-authorship network connecting the top 25 collaborators of Oana-Maria Camburu. A scholar is included among the top collaborators of Oana-Maria Camburu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Oana-Maria Camburu. Oana-Maria Camburu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

15 of 15 papers shown
1.
He, Xuanli, Yuxiang Wu, Oana-Maria Camburu, Pasquale Minervini, & Pontus Stenetorp. (2024). Using Natural Language Explanations to Improve Robustness of In-context Learning. 13477–13499. 2 indexed citations
2.
Minervini, Pasquale, et al.. (2024). Atomic Inference for NLI with Generated Facts as Atoms. 10188–10204.
3.
Novak, Alex, et al.. (2024). Fool Me Once? Contrasting Textual and Visual Explanations in a Clinical Decision-Support Setting. 18891–18919. 2 indexed citations
4.
5.
Atanasova, Pepa, Oana-Maria Camburu, Christina Lioma, et al.. (2023). Faithfulness Tests for Natural Language Explanations. Research at the University of Copenhagen (University of Copenhagen). 283–294. 9 indexed citations
6.
7.
8.
Yordanov, Yordan, et al.. (2022). Few-Shot Out-of-Domain Transfer Learning of Natural Language Explanations in a Label-Abundant Setup. 3486–3501. 2 indexed citations
9.
Sha, Lei, Oana-Maria Camburu, & Thomas Lukasiewicz. (2022). Rationalizing predictions by adversarial information calibration. Artificial Intelligence. 315. 103828–103828. 5 indexed citations
10.
Omeiza, Daniel, et al.. (2021). Towards Explainable and Trustworthy Autonomous Physical Systems. Research Publications (Maastricht University). 1–3. 2 indexed citations
11.
Sha, Lei, Oana-Maria Camburu, & Thomas Lukasiewicz. (2021). Learning from the Best: Rationalizing Predictions by Adversarial Information Calibration. Proceedings of the AAAI Conference on Artificial Intelligence. 35(15). 13771–13779. 13 indexed citations
12.
Camburu, Oana-Maria, et al.. (2021). e-ViL: A Dataset and Benchmark for Natural Language Explanations in Vision-Language Tasks. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 1224–1234. 35 indexed citations
13.
Camburu, Oana-Maria, et al.. (2021). The Gap on Gap: Tackling the Problem of Differing Data Distributions in Bias-Measuring Datasets. Proceedings of the AAAI Conference on Artificial Intelligence. 35(14). 13180–13188. 1 indexed citations
14.
Camburu, Oana-Maria, et al.. (2020). The Gap on GAP: Tackling the Problem of Differing Data Distributions in Bias-Measuring Datasets. arXiv (Cornell University). 35(14). 13180–13188. 2 indexed citations
15.
Camburu, Oana-Maria, Tim Rocktäschel, Thomas Lukasiewicz, & Phil Blunsom. (2018). e-SNLI: Natural Language Inference with Natural Language Explanations. arXiv (Cornell University). 31. 9539–9549. 152 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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