Papers by Yoan Dinkov
EXAMS: A Multi-subject High School Examinations Dataset for Cross-lingual and Multilingual Question Answering (2020.emnlp-main)
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| Challenge: | EXAMS is a benchmark dataset for cross-lingual and multilingual question answering for high school examinations. |
| Approach: | They propose to use EXAMS to evaluate cross-lingual and multilingual question answering for high school examinations. |
| Outcome: | The proposed model can be used to explore multilingual reasoning and knowledge transfer methods and pre-trained models in schools in different languages, which was not possible by now. |
A Neighborhood Framework for Resource-Lean Content Flagging (2022.tacl-1)
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Sheikh Muhammad Sarwar, Dimitrina Zlatkova, Momchil Hardalov, Yoan Dinkov, Isabelle Augenstein, Preslav Nakov
| Challenge: | Existing approaches to cross-lingual content flagging with limited target language data are lacking in many languages. |
| Approach: | They propose a framework for cross-lingual content flagging with limited target- language data based on a nearest-neighbor architecture and a transformer representation in all its components. |
| Outcome: | The proposed framework outperforms previous work in terms of predictive performance on eight languages from two different datasets. |
What Was Written vs. Who Read It: News Media Profiling Using Text Analysis and Social Media Context (2020.acl-main)
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Ramy Baly, Georgi Karadzhov, Jisun An, Haewoon Kwak, Yoan Dinkov, Ahmed Ali, James Glass, Preslav Nakov
| Challenge: | a growing number of fake news reports are published online, causing a trust crisis . a new study aims to predict political bias and factuality of reporting of entire news outlets . |
| Approach: | They propose to profile entire news outlets and look for those that are likely to publish fake content . they also examine what was written about the target medium and who reads it . |
| Outcome: | The proposed method improves on the current state-of-the-art in analyzing social media and what was written about the target medium. |