Citation Analysis

Minimax and Bayes Optimal Best-Arm Identification
Masahiro Kato
https://arxiv.org/abs/2506.24007

Citation mentions

Cited references

Sections

11,910

Words (approx)

References by Citation Intensity

Ordered by composite index (descending). Higher values indicate more intensive citation.

#	Mentions	Breadth	Sec. Wtd	Share	Composite	Main %
1	7	4	6.5	0.085	0.950	86%
2	5	4	5.5	0.061	0.928	80%
3	4	3	2.5	0.049	0.843	75%
4	4	3	3.5	0.049	0.843	75%
5	6	5	5.0	0.073	0.794	50%
6	3	3	2.0	0.037	0.737	67%
7	5	2	2.5	0.061	0.737	60%
8	4	2	2.0	0.049	0.737	75%
9	4	2	2.0	0.049	0.644	50%
10	4	2	2.0	0.049	0.644	50%
11	2	2	2.5	0.024	0.644	100%
12	2	2	2.5	0.024	0.644	100%
13	2	2	2.5	0.024	0.644	100%
14	2	2	1.5	0.024	0.511	50%
15	3	2	1.5	0.037	0.511	33%
16	2	2	1.0	0.024	0.511	50%
17	2	2	2.5	0.024	0.511	50%
18	1	1	0.5	0.012	0.406	100%
19	1	1	0.5	0.012	0.406	100%
20	1	1	0.5	0.012	0.406	100%
21	1	1	0.5	0.012	0.406	100%
22	1	1	0.5	0.012	0.406	100%
23	1	1	0.5	0.012	0.406	100%
24	1	1	0.5	0.012	0.406	100%
25	1	1	0.5	0.012	0.406	100%
26	1	1	0.5	0.012	0.406	100%
27	1	1	0.5	0.012	0.406	100%
28	1	1	2.0	0.012	0.406	100%
29	1	1	2.0	0.012	0.406	100%
30	2	1	1.0	0.024	0.110	0%
31	2	1	1.0	0.024	0.110	0%
32	1	1	0.5	0.012	0.087	0%
33	1	1	0.5	0.012	0.087	0%
34	1	1	0.5	0.012	0.087	0%
35	1	1	0.5	0.012	0.087	0%
36	1	1	0.5	0.012	0.087	0%

Measures: Mentions = total in-text citations; Breadth = distinct sections; Sec. Wtd = section-weighted count (body ×2, lit review/appendix ×0.5); Share = mentions / total citations in paper; Composite = geometric mean of normalised count, breadth, and main-text ratio; Main % = fraction of mentions in main text (excl. appendix). (self) = self-citation.