← The rising topics of the week

In: All of arXiv. One to three words, as in a title; plurals count with their singular. Premium compares three terms, in any field or category, and exports the counts. Discover Premium

"state space model" is declining. 7.2 papers per 10,000 over the last 13 weeks (78 papers), against 11.6 over the 13 weeks before (107 papers). A fall too large to be chance. A year before, over the same weeks: 16.2 per 10,000.

Papers using the term per 10,000 papers of the week, averaged over 4 weeks
0102030Apr 2025Jun 2025Aug 2025Oct 2025Dec 2025Feb 2026Apr 2026Jun 2026Aug 2026Oct 2026

Left axis: out of 10,000 papers submitted in a week, how many use the term. Each point averages that week with the three before, as the count of a single week jumps with holidays and conference deadlines. Hover over the curve to read each week and its number of papers.

"state space model": 634 papers in 80 weeks. Counted since the week of 7 April 2025.

The weekly values
Week ofstate space model
12 Oct 20264 papers (4.2 per 10,000)
5 Oct 20264 papers (4.0 per 10,000)
28 Sep 202610 papers (8.5 per 10,000)
21 Sep 20269 papers (9.5 per 10,000)
14 Sep 20267 papers (8.1 per 10,000)
7 Sep 20265 papers (6.3 per 10,000)
31 Aug 20262 papers (2.5 per 10,000)
24 Aug 202613 papers (17.2 per 10,000)
17 Aug 20265 papers (7.4 per 10,000)
10 Aug 20265 papers (7.2 per 10,000)
3 Aug 20266 papers (8.0 per 10,000)
27 Jul 20264 papers (5.3 per 10,000)
20 Jul 20264 papers (6.3 per 10,000)
13 Jul 20265 papers (7.7 per 10,000)
6 Jul 20264 papers (6.1 per 10,000)
29 Jun 202610 papers (14.0 per 10,000)
22 Jun 20268 papers (11.4 per 10,000)
15 Jun 202610 papers (14.9 per 10,000)
8 Jun 20262 papers (2.8 per 10,000)
1 Jun 20266 papers (8.1 per 10,000)
25 May 20269 papers (11.4 per 10,000)
18 May 202610 papers (13.2 per 10,000)
11 May 202618 papers (22.6 per 10,000)
4 May 202612 papers (15.4 per 10,000)
27 Apr 20267 papers (10.8 per 10,000)
20 Apr 20266 papers (9.6 per 10,000)
13 Apr 202615 papers (22.4 per 10,000)
6 Apr 20268 papers (12.3 per 10,000)
30 Mar 202610 papers (15.3 per 10,000)
23 Mar 20266 papers (9.2 per 10,000)
16 Mar 202611 papers (16.3 per 10,000)
9 Mar 20268 papers (11.7 per 10,000)
2 Mar 202616 papers (24.6 per 10,000)
23 Feb 20269 papers (14.4 per 10,000)
16 Feb 20264 papers (8.0 per 10,000)
9 Feb 20266 papers (9.6 per 10,000)
2 Feb 202610 papers (14.8 per 10,000)
26 Jan 202610 papers (14.7 per 10,000)
19 Jan 202611 papers (19.9 per 10,000)
12 Jan 20260 papers (0.0 per 10,000)
5 Jan 20266 papers (11.3 per 10,000)
29 Dec 20256 papers (16.2 per 10,000)
22 Dec 20252 papers (4.8 per 10,000)
15 Dec 20256 papers (9.8 per 10,000)
8 Dec 20254 papers (6.9 per 10,000)
1 Dec 20257 papers (11.7 per 10,000)
24 Nov 20258 papers (13.3 per 10,000)
17 Nov 20259 papers (15.5 per 10,000)
10 Nov 20258 papers (12.8 per 10,000)
3 Nov 20252 papers (3.7 per 10,000)
27 Oct 20254 papers (6.7 per 10,000)
20 Oct 20255 papers (8.7 per 10,000)
13 Oct 202511 papers (17.9 per 10,000)
6 Oct 202512 papers (18.5 per 10,000)
29 Sep 20255 papers (7.3 per 10,000)
22 Sep 202512 papers (17.5 per 10,000)
15 Sep 20255 papers (8.4 per 10,000)
8 Sep 20253 papers (5.7 per 10,000)
1 Sep 20259 papers (17.0 per 10,000)
25 Aug 202510 papers (18.8 per 10,000)
18 Aug 20258 papers (16.2 per 10,000)
11 Aug 20259 papers (18.0 per 10,000)
4 Aug 202514 papers (25.0 per 10,000)
28 Jul 202512 papers (23.0 per 10,000)
21 Jul 202510 papers (18.7 per 10,000)
14 Jul 202512 papers (22.6 per 10,000)
7 Jul 20258 papers (15.1 per 10,000)
30 Jun 20259 papers (17.4 per 10,000)
23 Jun 202511 papers (21.1 per 10,000)
16 Jun 20258 papers (15.5 per 10,000)
9 Jun 202510 papers (17.8 per 10,000)
2 Jun 20259 papers (14.9 per 10,000)
26 May 202514 papers (20.5 per 10,000)
19 May 202512 papers (17.6 per 10,000)
12 May 20258 papers (14.5 per 10,000)
5 May 20257 papers (14.5 per 10,000)
28 Apr 20255 papers (10.4 per 10,000)
21 Apr 20256 papers (12.8 per 10,000)
14 Apr 202511 papers (22.2 per 10,000)
7 Apr 20258 papers (15.6 per 10,000)

Who works on it? Literature review Search and follow the term

How it works

  1. Every week, we read the title and abstract of every new paper on arXiv (first versions only, not updates) and note the terms of one to three words they use.
  2. For your term, we count the papers using it each week, and divide by all the papers of that week. A share rather than a number: arXiv grows every year, so the number of papers would rise for almost every topic, while the share rises only when the topic takes a larger place.
  3. The answer at the top compares the last 13 weeks with the 13 weeks before. The topic "rises" only when its share is at least ×1.2 and the gap is too large to come from chance, a test of the same kind as for the rising topics of the week; it "declines" in the same way the other way round.

How to read it

  • A curve that climbs over several months: more and more teams write about the topic. A peak that falls back after a few weeks: an event, a release, a data set or a conference deadline.
  • The height matters less than the trend: a broad term (graph neural network) is always higher than a precise one (equivariant message passing). To compare two topics, compare how their curves move.
  • The terms are counted as words, in English, plurals with their singular. A term with several meanings counts them all (transformer, in electrical engineering and in AI): then try a more specific term. A week where a single paper uses the term counts as zero.
  • The curve says how much the topic is written about, not whether the papers are good or cited, nor what is published outside arXiv.

Why it is useful

  • Check an impression: "everyone is working on it" — true, or only in the papers you happen to see?
  • Choose a thesis or project subject: a rising topic draws funding and competition; a declining one may be maturing, or being left aside.
  • Back up a "growing interest" in a grant proposal or an introduction with a number. When citing it, name the source and the period.
  • Compare competing methods or instruments week by week, to see which one is taking over. Premium

The rising topics of the week work the other way round: instead of checking a term you chose, they find by themselves the terms that jumped this week. The rising topics of the week