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Found 4 papers, 2 papers with code
Prediction-Powered Ranking of Large Language Models
Our framework is computationally efficient, easy to use, and does not make any assumption about the distribution of human preferences nor about the degree of alignment between the pairwise comparisons by the humans and the strong large language model.
Diversity-aware clustering: Computational Complexity and Approximation Algorithms
We present parameterized approximation algorithms with approximation ratios $1+ \frac{2}{e}$, $1+\frac{8}{e}$ and $3$ for diversity-aware $k$-median, diversity-aware $k$-means and diversity-aware $k$-supplier, respectively.
Finding path motifs in large temporal graphs using algebraic fingerprints
In particular, given a vertex-colored temporal graph and a multiset of colors as a query, we search for temporal paths in the graph that contain the colors specified in the query.
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