CsAuthors.net database
Most of the data is coming from the
DBLP Computer Science Bibliography
and the rest is coming from CsAuthors.net own database.
We are working hard to keep everything up-to-date. However, we know that there are many papers not yet included in our dataset.
If something is wrong or missing, feel free to write me at
We are working hard to keep everything up-to-date. However, we know that there are many papers not yet included in our dataset.
If something is wrong or missing, feel free to write me at
my email address
.
The "Dijkstra number"
The Dijkstra number describes the collaborative distance between an author and
Edsger W. Dijkstra.
In our dataset 90.4% of authors are connected to Edsger W. Dijkstra and the average Dijkstra number among them is 5.05.
These kind of number/metrics are quite famous and already well defined in other fields.
In our dataset 90.4% of authors are connected to Edsger W. Dijkstra and the average Dijkstra number among them is 5.05.
These kind of number/metrics are quite famous and already well defined in other fields.
- The "Erdős number" expresses the collaborative distance with Paul Erdős, the famous Hungarian mathematician.
- The "Bacon number" expresses the co-acting distance with Kevin Bacon.
The "Erdős number"
The Erdős number describes the collaborative distance between an author and
Paul Erdős.
In our dataset 90.4% of authors are connected to Paul Erdős and the average Erdős number among them is 4.64.
Find more on Wikipedia with an article on the"Erdős number".
In our dataset 90.4% of authors are connected to Paul Erdős and the average Erdős number among them is 4.64.
Find more on Wikipedia with an article on the"Erdős number".
Arun Kirubarajan
According to our database1,
Arun Kirubarajan
authored at least 4 papers
between 2019 and 2023.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
On csauthors.net:
Bibliography
2023
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.
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Trans. Mach. Learn. Res., 2023
Real or Fake Text?: Investigating Human Ability to Detect Boundaries between Human-Written and Machine-Generated Text.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2020
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, 2020
2019
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019