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".
Ian Ng
According to our database1,
Ian Ng
authored at least 2 papers
between 2022 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
2022
Stanford MLab at SemEval 2022 Task 7: Tree- and Transformer-Based Methods for Clarification Plausibility.
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Proceedings of the 16th International Workshop on Semantic Evaluation, SemEval@NAACL 2022, 2022