Todor Mihaylov

4.2k total citations · 1 hit paper
17 papers, 621 citations indexed

About

Todor Mihaylov is a scholar working on Artificial Intelligence, Information Systems and Sociology and Political Science. According to data from OpenAlex, Todor Mihaylov has authored 17 papers receiving a total of 621 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 6 papers in Information Systems and 3 papers in Sociology and Political Science. Recurrent topics in Todor Mihaylov's work include Topic Modeling (11 papers), Natural Language Processing Techniques (8 papers) and Spam and Phishing Detection (3 papers). Todor Mihaylov is often cited by papers focused on Topic Modeling (11 papers), Natural Language Processing Techniques (8 papers) and Spam and Phishing Detection (3 papers). Todor Mihaylov collaborates with scholars based in Germany, Bulgaria and Qatar. Todor Mihaylov's co-authors include Preslav Nakov, Peter E. Clark, Tushar Khot, Ashish Sabharwal, Georgi Georgiev, Anette Frank, Ivan Koychev, Lluı́s Màrquez, María José Marcelino and António José Mendes and has published in prestigious journals such as Internet Research, Research at the University of Copenhagen (University of Copenhagen) and arXiv (Cornell University).

In The Last Decade

Todor Mihaylov

17 papers receiving 570 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering

2018 284 citations Todor Mihaylov, Peter E. Clark et al. profile →

Peers

Todor Mihaylov

AI

IS

CVPR

SPS

SP

Rahul Pandey United States

Edison Marrese-Taylor Japan

Ivan Koychev Bulgaria

Julia Kiseleva Netherlands

Dustin Arendt United States

Nattiya Kanhabua Germany

Alan Akbik Germany

Jianxing Yu China

Kazi Saidul Hasan United States

Sasha Blair-Goldensohn United States

Rahul Pandey United States

Todor Mihaylov

319 ×0.6

AI

222 ×1.4

IS

79 ×0.6

CVPR

65 ×0.6

SPS

27 ×1.0

SP

Citations per year, relative to Todor Mihaylov Todor Mihaylov (= 1×) peers Rahul Pandey

Countries citing papers authored by Todor Mihaylov

Since Specialization

Citations

This map shows the geographic impact of Todor Mihaylov'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 Todor Mihaylov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Todor Mihaylov more than expected).

Fields of papers citing papers by Todor Mihaylov

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Todor Mihaylov. 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 Todor Mihaylov. The network helps show where Todor Mihaylov may publish in the future.

Co-authorship network of co-authors of Todor Mihaylov

This figure shows the co-authorship network connecting the top 25 collaborators of Todor Mihaylov. A scholar is included among the top collaborators of Todor Mihaylov 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 Todor Mihaylov. Todor Mihaylov is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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17 of 17 papers shown

1.

Hardalov, Momchil, Pepa Atanasova, Todor Mihaylov, et al.. (2023). bgGLUE: A Bulgarian General Language Understanding Evaluation Benchmark. Research at the University of Copenhagen (University of Copenhagen). 8733–8759. 1 indexed citations

2.

Han, Xiaochuang, et al.. (2023). Understanding In-Context Learning via Supportive Pretraining Data. 12660–12673. 5 indexed citations

3.

Radenović, Filip, Abhimanyu Dubey, Abhishek Kadian, et al.. (2023). Filtering, Distillation, and Hard Negatives for Vision-Language Pre-Training. 6967–6977. 25 indexed citations

4.

Chen, Mingda, Jingfei Du, Ramakanth Pasunuru, et al.. (2022). Improving In-Context Few-Shot Learning via Self-Supervised Training. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 17 indexed citations

5.

Mihaylov, Todor, Ivan Koychev, Georgi Georgiev, & Preslav Nakov. (2021). Exposing Paid Opinion Manipulation Trolls. arXiv (Cornell University). 443–450. 6 indexed citations

6.

Mihaylov, Todor & Anette Frank. (2019). Discourse-Aware Semantic Self-Attention for Narrative Reading Comprehension. 18 indexed citations

7.

Mihaylov, Todor, Peter E. Clark, Tushar Khot, & Ashish Sabharwal. (2018). Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering. 2381–2391. 284 indexed citations breakdown →

8.

Frank, Anette, Tobias Falke, Ana Marasović, et al.. (2018). What's Important in a Text? An Extensive Evaluation of Linguistic Annotations for Summarization. 22. 272–277. 2 indexed citations

9.

Mihaylov, Todor, et al.. (2018). The dark side of news community forums: opinion manipulation trolls. Internet Research. 28(5). 1292–1312. 40 indexed citations

10.

Mihaylov, Todor & Anette Frank. (2017). Story Cloze Ending Selection Baselines and Data Examination. 87–92. 7 indexed citations

11.

Mihaylov, Todor & Anette Frank. (2016). Discourse Relation Sense Classification Using Cross-argument Semantic Similarity Based on Word Embeddings. 100–107. 17 indexed citations

12.

Mihaylov, Todor & Preslav Nakov. (2016). Hunting for Troll Comments in News Community Forums. 399–405. 42 indexed citations

13.

Mihaylov, Todor & Preslav Nakov. (2016). SemanticZ at SemEval-2016 Task 3: Ranking Relevant Answers in Community Question Answering Using Semantic Similarity Based on Fine-tuned Word Embeddings. 879–886. 40 indexed citations

14.

Mihaylov, Todor, Momchil Hardalov, Ivan Koychev, et al.. (2016). SUper Team at SemEval-2016 Task 3: Building a Feature-Rich System for Community Question Answering. 836–843. 20 indexed citations

15.

Mihaylov, Todor, Georgi Georgiev, & Preslav Nakov. (2015). Finding Opinion Manipulation Trolls in News Community Forums. 310–314. 80 indexed citations

16.

Mihaylov, Todor, et al.. (2014). SU-FMI: System Description for SemEval-2014 Task 9 on Sentiment Analysis in Twitter. 590–595. 4 indexed citations

17.

Marcelino, María José, Todor Mihaylov, & António José Mendes. (2008). H-SICAS, a handheld algorithm animation and simulation tool to support initial programming learning. 13. T4A–7. 13 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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