Telegram RegisterThe public register of Telegram

Channel

Научный опенсорс

@scientific_opensource

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

952subscribers

+0 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1002166621782
TypeChannel
Username@scientific_opensource
DescriptionКанал сообщества ITMO OpenSource, посвященного созданию и использованию наукоёмких open-source проектов, в том числе в области AI/ML. Чат: https://t.me/itmo_opensource По всем вопросам - @nicl_nno
CreatedBetween 1 June 2024 and 30 September 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded8 August 2026
Last confirmed live8 August 2026
Measurements held2
On Telegramt.me/scientific_opensource

Growth

9527 Aug 2026, 15:07 — 952 subscribers8 Aug 2026, 00:48 — 952 subscribers7 Aug 2026, 15:078 Aug 2026, 00:48
2 measurements taken within a single day. 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 951–953 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
8 Aug 2026, 00:48952no change
7 Aug 2026, 15:07952first reading

Engagement

19 posts held, back to 3 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 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
63.8%
avg views ÷ 952 subscribers
Avg views / post
607
11 posts measured
Reaction rate
1.03%
reactions ÷ views · ER floor
Posts in window
11
of 19 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. It is computed over the 10 of 11 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 5 August 2026
Posts held19 (3 June 20265 August 2026)
Views total6,676
Reactions total66
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken8 Aug 2026, 00:48 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

Photos
115
Videos
1
Links
186

Lifetime counters from Telegram’s own channel header, read 8 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.

Reaction mix

142 reactions across 18 posts, in 10 distinct kinds. The most used accounts for 56.3% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥8056.3%
2416.9%
👍2114.8%
👏85.63%
🆒21.41%
👀21.41%
👎21.41%
💯10.704%
🖕10.704%
🤬10.704%

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 18 of the 19 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 142reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 19 most recent posts we hold, published 3 June 2026 to 5 August 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

5 Aug 2026, 14:08 UTC300 views11 reactionsread 8 August 2026
Photo

Коллеги из Sber AI Lab опубликовали новый открытый репозиторий https://github.com/sb-ai-lab/SIRIN (Semantic Inconsistency Recognition and Inspection Nexus) - инструмент для поиска смысловых ошибок в ответах языковых моделей. Что умеет SIRIN: - Проверяет соответствие ответа исходному контексту на уровне токенов, последовательностей и отдельных утверждений. - Поддерживает детекцию галлюцинаций и оценку answerability -

7🔥4

Signed Nikolay Nikitin

4 Aug 2026, 16:26 UTC296 viewsread 8 August 2026

Анонсируют такой вот вебинар из цикла опенсорс-курсов по ИИ от МФТИ:

Signed Nikolay Nikitin

4 Aug 2026, 16:26 UTC183 views3 reactionsread 8 August 2026
Forwarded from @ivoryzoo

#зоопарк_одобряет #конференции Вернее, не конференция, а интересный (и бесплатный) вебинар от girafe.ai "Рабочее окружение ML-инженера: делегируем рутину ИИ-агентам" Почему интересно: хотя бы по той причине, что у girafe.ai есть совместная онлайн-мага с МФТИ, что, на наш взгляд, уже знак качества (Физтех очень разборчив в выборе таких партнеров) Темы: • организация удобного рабочего окружения ML-инженера с нуля •

🔥3

Signed Nikolay Nikitin

3 Aug 2026, 15:23 UTC345 views7 reactionsread 8 August 2026
Photo

Тематически близкая конференция про качество кода продлила дедлайн до 17 августа: https://www.iccq.ru/2026.html Публикации в IEEE Xplore/Scopus, локация - уютный декабрьский Новосибирск.

🔥51👎1

Signed Nikolay Nikitin

29 Jul 2026, 15:29 UTC365 views4 reactionsread 8 August 2026
Forwarded from @tech_shpilmanPhoto

🤖 Интересная дискуссия развернулась по поводу open-weights моделей – после того, как стало известно об инициативах в правительстве США по запрету использования китайских моделей в американских компаниях. Дженсен Хуанг (CEO NVIDIA) – с еще семью десятками ИТ- и ИИ-лидерами – написал открытое письмо, в котором заявил, что open source – это, вообще-то, замечательно, да и open-weight тоже, так что не надо, пожалуйста, н

👍31

Signed Nikolay Nikitin

27 Jul 2026, 17:42 UTC526 views5 reactionsread 8 August 2026
Photo

"У нас есть воспроизводимость дома" - ШАД и Сириус следом за HuggingFace анонсировали "Интенсив по воспроизведению современных научных результатов — 2026" в начале октября. Бесплатный научный интенсив для тех, кто интересуется машинным обучением, архитектурами нейросетей и системами обработки данных. Участники воспроизведут эксперименты из реальных исследований и разберут их вместе с менторами — учёными и разработчи

👍5

Signed Nikolay Nikitin

27 Jul 2026, 15:47 UTC623 views5 reactionsread 8 August 2026
Photo

Moonshot AI выпустила Kimi K3 на Hugging Face: Это первая модель с открытыми весами в классе ~3T. Благодаря MoE на каждый токен активируются лишь 104B параметров (16 экспертов из 896). По заявлению разработчиков, K3 создана для длинных агентных задач: работы с большими репозиториями, использования терминала, исследований, оптимизации GPU-ядер, компиляторов и других многошаговых инженерных сценариев. Что внутри: -

🔥5

Signed Nikolay Nikitin

20 Jul 2026, 06:31 UTC≈1,130 views14 reactionsread 8 August 2026
Photo

RAGU - на HuggingFace! Сегодня мы выложили на HuggingFace препринт про открытый GraphRAG-фреймворк RAGU. RAGU - это модульный GraphRAG-движок, который превращает сырой текст в граф знаний: извлекает сущности и связи, строит и чистит граф, а затем ищет ответы через локальные, глобальные или гибридные стратегии. Этот проект сейчас разрабатывается совместно Лабораторией прикладных цифровых технологий НГУ (Иван Бондар

👍94💯1

Signed Nikolay Nikitin

18 Jul 2026, 07:07 UTC≈1,650 views11 reactionsread 8 August 2026
Photo

Hugging Face и alphaXiv объявили соревнование по воспроизведению результатов научных статей с ICML 2026 - тема, на которую периодически пишем. Из каждой статьи выделено несколько claims, корректность которых и нужно проверить. Цель проекта – создать публичную базу проверок научных работ, чтобы сделать их более прозрачными и воспроизводимыми. За участие организаторы предлагают GPU-кредиты на каждую статью (но их бы

🔥83

Signed Nikolay Nikitin

16 Jul 2026, 09:23 UTC639 views2 reactionsread 8 August 2026

Объявлены репозитории-победители очередного опенсорс-конкурса KaiCode: 1) raprogramm/yew-nav-link 6★ - Вьетнам - Perfect $2048 А navigation-link library for the Yew framework in Rust with automatic active-state detection, demonstrated perfect software development practices: clean and idiomatic code, requirements captured as formal specifications and architecture decision records, strict static analysis (clippy, Cod

👀2

Signed Nikolay Nikitin

15 Jul 2026, 10:35 UTC619 views4 reactionsread 8 August 2026
Photo

Сбер выкатил новые опенсорс-модели - теперь со звуком: 1) Новая GigaChat Audio. Audio-native LLM на базе GigaAM Multilingual и GigaChat3.1-10B-A1.8B. Поддерживает multi-turn диалог, классификацию аудио, перевод и распознавание речи, и temporal grounding (локализацию событий во времени), описание интервала аудио и суммаризацию с временными метками. В комплекте идет датасет TimeGround-1M — для обучения LLM привязке с

🔥31

Signed Nikolay Nikitin

3 Jul 2026, 08:01 UTC885 views12 reactionsread 8 August 2026
Photo

И снова рубрика "рассказываем о научно-опенсорсных успехах коллективов ИТМО". Сегодня - про AI4Physics. Андрей Богданов из Нового физтеха ИТМО совместно с Харбинским инженерными университетом: (1) разработали ИИ-модель MetaDiT для автоматического проектирования сверхтонкой оптики. (2) опубликовали статью "MetaDiT: Enabling Fine-grained Constraints in High-degree-of Freedom Metasurface Design" на А*-конференции AAAI

🔥12

Signed Nikolay Nikitin

Showing the 12 most recent of 19 posts we hold for @scientific_opensource. 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 — 239,354 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 1 registered channel — 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.

Named by

Channels on the register whose posts name this channel's handle.

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 8 August 2026 — this entry's latest reading, not the date you are reading this.

“Научный опенсорс” (@scientific_opensource), 952 subscribers as measured 8 August 2026. Telegram Register, tgregister.com/channel/scientific_opensource.

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.