Telegram RegisterThe public register of Telegram

Channel

Center for Cognitive Modeling

@cogmodel

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

1,772subscribers

+1 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1001124306846
TypeChannel
Username@cogmodel
CreatedBetween 1 June 2017 and 31 August 2020— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live13 August 2026
Measurements held3
Confirmed unchanged1 time, most recently 13 August 2026
On Telegramt.me/cogmodel

Growth

1,7711,7721,771.56 August 2026 — 1,771 subscribers6 August 2026 — 1,771 subscribers13 August 2026 — 1,772 subscribers6 August 202613 August 2026
3 measurements spanning 7 days, net +1. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 1,771–1,772 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
13 Aug 2026, 03:261,772+1
6 Aug 2026, 16:321,771no change
6 Aug 2026, 14:351,771first reading

Engagement

9 posts held, back to 11 June 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 2 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
39.8%
avg views ÷ 1,772 subscribers
Avg views / post
705
3 posts measured
Reaction rate
2.84%
reactions ÷ views · ER floor
Posts in window
3
of 9 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.

What these figures were computed from
WindowRolling 30 days · latest post in window 24 July 2026
Posts held9 (11 June 202624 July 2026)
Views total2,114
Reactions total60
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Aug 2026, 17:36 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

What this channel posts

Video runtime
15s
Average length
15s

Measured directly from 1 video with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no mark.

Reaction mix

134 reactions across 9 posts, in 5 distinct kinds. The most used accounts for 56.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥7656.7%
4936.6%
👏64.48%
❤‍🔥21.49%
👍10.746%

No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.

Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.

Coverage. Reactions were read on 9 of the 9 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 134reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 9 most recent posts we hold, published 11 June 2026 to 24 July 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.

Recent posts

24 Jul 2026, 17:00 UTC625 views9 reactionsread 7 August 2026
Photo

🦾 — Запускаем дополнительный набор в магистратуру ФПМИ МФТИ по искусственному интеллекту и робототехнике! Поступление проходит по 2 направлениям: — “Фундаментальные методы искусственного интеллекта” – база ЦКМ, 25 мест — “Мультимодальный искусственный интеллект”– база Институт AIRI, 10 мест Для поступления необходимо: 🪼Заполнить заявку на нашем в форме до 12:00 28 июля и пройти собеседование в Центре. 🪼Подать докум

🔥9

23 Jul 2026, 08:08 UTC690 views40 reactionsread 7 August 2026
Photo

🪼TerraCognitaSLAM: проект нашего сотрудника на инвестиционной программе. Наш сотрудник Олег Буличев защитил свой проект TerraCognitaSLAM на программе Трансляционных Исследований от Центрального Университета. Проект родился благодаря участию Олега в археологическом конкурсе — он увидел пробел в технологиях и решил его закрыть. TerraCognitaSLAM — это система навигации для роботов там, где GPS не работает: под кронами

🔥249👏6👍1

20 Jul 2026, 11:06 UTC799 views11 reactionsread 7 August 2026
Photo

🪼Дайджест ЦКМ: начинаем неделю с полезных материалов Собрали для вас подборку свежих статей и разработок — от генерации 3D-сцен до новых подходов к вниманию в нейросетях и организации научного поиска. 3D и Генерация сцен Метод Sage от команды NVIDIA — генерацию интерактивных 3D-сцен с помощью LLM/VLM тул-коллинга на базе Open3D (ранее упоминался как QUEN3-VL). В отличие от статичных мешей, объекты загружаются в Isa

11

12 Jul 2026, 15:45 UTC≈1,050 views32 reactionsread 7 August 2026
Photo

💫Сотрудники и студенты из команды ЦКМ и Института AIRI на ICML 2026! На этой неделе в Сеуле прошла ICML 2026 — одна из сильнейших мировых конференций в области машинного обучения (категория А*). KAGE-Bench: Fast Known-Axis Visual Generalization Evaluation for Reinforcement Learning — бенчмарк для быстрой и прозрачной оценки того, как алгоритмы обучения с подкреплением обобщают визуальные признаки по заданным осям (

🔥239

22 Jun 2026, 09:38 UTC≈1,960 views8 reactionsread 7 August 2026
Photo

🎓 — Семинар 21. Защита магистерских диссертаций выпускников ЦКМ 2026 Ещё одна группа морских котиков ИИ готова к финальной миссии своего обучения — защите магистерской работы🏆 За два года мы постарались передать студентам самые актуальные и прикладные знания в области ИИ и робототехники, а ребята достигли больших успехов. Приглашаем всех присоединиться и послушать выступления! 📹 Трансляция ВК #семинары #магистрат

8

18 Jun 2026, 14:11 UTC≈1,310 views4 reactionsread 7 August 2026
Photo

💫 — Начинаем семинар, присоединяйтесь к трансляции в ВК или на YouTube!

🔥4

16 Jun 2026, 17:00 UTC≈2,310 views12 reactionsread 7 August 2026
Photo

🎓 — Семинар 20. Обзор конференции ICRA 2026 | Александр Панов, Дмитрий Юдин, Дмитрий Макаров, Юлия Даник В начале июня наша команда выезжала в Вену на ICRA 2026. Это крупнейшая в мире конференция по робототехнике и автоматизации. На конференцию прошло 3 наших статьи: 1) Dynamic Neural Potential Field: Online Trajectory Optimization in Presence of Moving Obstacles — представляет метод нейросетевой генерации траектор

🔥93

11 Jun 2026, 14:11 UTC≈1,310 views2 reactionsread 7 August 2026
Photo

💫 — Начинаем семинар, присоединяйтесь к трансляции в ВК или на YouTube!

🔥2

11 Jun 2026, 07:53 UTC≈2,010 views16 reactionsread 7 August 2026
Photo

⚡️ — Робототехника в археологии — рассказываем о ходе соревнований Экспедиция.Земля, трек Археология. Конкурс предполагает разработку наземных мобильных роботов, позволяющих с высокой точностью обнаруживать и классифицировать археологические объекты и предметы различного состава, расположенных на различной глубине под землей. Наша команда под руководством Олега Буличева уже участвовала в соревнованиях в прошлом год

9🔥5❤‍🔥2

Showing the 9 most recent of 9 posts we hold for @cogmodel. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.

Citation-graph rank

Citation-graph rank — 173,086 of 1,160,990entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

Forward network

Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.

Mentions

Named by 4 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.

A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 13 August 2026 — this entry's latest reading, not the date you are reading this.

“Center for Cognitive Modeling” (@cogmodel), 1,772 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/cogmodel.

Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.