Channel
@ai_cs_ut
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
1,134subscribers
+2 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1002078578608 |
|---|---|
| Type | Channel |
| Username | @ai_cs_ut |
| Created | Between 1 November 2023 and 11 May 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 10 August 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 10 August 2026 |
| On Telegram | t.me/ai_cs_ut |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 10 Aug 2026, 22:18 | 1,134 | +2 |
| 7 Aug 2026, 15:42 | 1,132 | no change |
| 6 Aug 2026, 16:05 | 1,132 | first reading |
20 posts held, back to 11 May 2024 — the 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.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 8 September 2024. An engagement rate over an empty window would be a number about nothing.
442 reactions across 20 posts, in 12 distinct kinds. The most used accounts for 87.1% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 385 | 87.1% | |
| 👍 | 23 | 5.20% | |
| 😭 | 15 | 3.39% | |
| 🙏 | 5 | 1.13% | |
| ⚡ | 4 | 0.905% | |
| 👀 | 3 | 0.679% | |
| 🤬 | 2 | 0.452% | |
| 👏 | 1 | 0.226% | |
| 💯 | 1 | 0.226% | |
| 😁 | 1 | 0.226% | |
| 😢 | 1 | 0.226% | |
| 🤯 | 1 | 0.226% |
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 20 of the 20 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 442reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 11 May 2024 to 8 September 2024, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
ویدیو جلسه هفدهم: سیر تکاملی مکانیزم توجه در داده های تصویری و ویژن ترنسفورمرز Evolution of Attention mechanism on Visual Data (Squeeze & Excitation, CBAM, NLM, AANet, Relative Positional Embedding, Local Attention, Axial DeepLab,....) and Vision Transformers (ViT, DeiT, T2T-ViT, Swin Transformer, ...) از دوره جامع Transformers and Diffusion models برگزار شده در دانشکده ریاضی، آمار و علوم کامپیوتر دانشگاه تهران @ai…
❤23⚡2👍2🤯1
ویدیو جلسه شانزدهم: تشخیص اشیا، تقسیم بندی معنایی Object Detection (R-CNN, Fast R-CNN, Fater R-CNN, YOLO, Feature Pyramid Network, RetinaNet, FCOS, ...), Semantic Segmentation (U-Net, ...), Instance Segmentation (Mask R-CNN, Panoptic Segmentation, ...) از دوره جامع Transformers and Diffusion models برگزار شده در دانشکده ریاضی، آمار و علوم کامپیوتر دانشگاه تهران @ai_cs_ut https://youtu.be/LlHFtqXf2so?si=t4iqxk1WGOg…
❤19⚡1
ویدیو جلسه پانزدهم: مقدمه ای بر بینایی ماشین و شبکه های عصبی پیچشی Introduction to Computer Vision, Convolution Neural Network (CNN) از دوره جامع Transformers and Diffusion models برگزار شده در دانشکده ریاضی، آمار و علوم کامپیوتر دانشگاه تهران @ai_cs_ut https://youtu.be/NhNp23oiOo8?si=Uz5751B66H5YWvwQ
❤17⚡1😢1
ویدیو جلسه چهاردهم: GPT-3, Instruction Fine-Tuning, RLHF (Reinforcement learning from human feedback), InstructGPT (ChatGPT) از دوره جامع Transformers and Diffusion models برگزار شده در دانشکده ریاضی، آمار و علوم کامپیوتر دانشگاه تهران @ai_cs_ut https://youtu.be/9uhS9rGgOzs?si=mQ8ruqL9Yb8H-EoV
❤20
ویدیو جلسه سیزدهم: GPT-2, T5 از دوره جامع Transformers and Diffusion models برگزار شده در دانشکده ریاضی، آمار و علوم کامپیوتر دانشگاه تهران @ai_cs_ut https://youtu.be/kEWCVoeO0Mc?si=sXRBFflY8eBCVkej
❤24
ویدیو جلسه دوازدهم: Byte pair encoding (BPE), WordPiece, GPT1, Bert از دوره جامع Transformers and Diffusion models برگزار شده در دانشکده ریاضی، آمار و علوم کامپیوتر دانشگاه تهران @ai_cs_ut https://youtu.be/bxiCvC7ck1M?si=GECmIAO4ydokJyz1
❤25👍1😁1
ویدیو جلسه یازدهم: Transformer از دوره جامع Transformers and Diffusion models برگزار شده در دانشکده ریاضی، آمار و علوم کامپیوتر دانشگاه تهران @ai_cs_ut https://youtu.be/4BnolUGdgS4?si=9hZ-0Di4st_qr6nK
❤18
‼️ به اطلاع همراهان عزیز میرسانیم با توجه به شروع امتحانات پایان ترم دانشگاه تهران، جلسه حضوری بعدی دوره، بعد از اتمام امتحانات پایان ترم دانشگاه تهران، روز شنبه مورخ ۱۶ تیر ماه برگزار خواهد شد. ❗️پی نوشت اول: برای رفاه حال دانشجویان خوابگاهی که پیش از این، دوره را به صورت حضوری دنبال میکردند اما تابستان امکان حضور در تهران ندارند، سعی خواهد شد جلسات بعدی دوره، با کیفیت صوتی و تصویری به مراتب بهتری ضبط شوند. ❗️پی …
❤23👍9
‼️ به اطلاع همراهان عزیز میرسانیم که کلاس روز شنبه مورخ ۲۶ خرداد ماه تشکیل نخواهد شد.
😭15👀3
ویدیو جلسه دهم: Sequence-to-Sequence Learning (seq2seq) از دوره جامع Transformers and Diffusion models برگزار شده در دانشکده ریاضی، آمار و علوم کامپیوتر دانشگاه تهران @ai_cs_ut https://youtu.be/u5jjaXHlyLk?si=u2b8EWpk6SrDe5Al
❤15👍2
ویدیو جلسه نهم: Embeddings (Word2vec) از دوره جامع Transformers and Diffusion models برگزار شده در دانشکده ریاضی، آمار و علوم کامپیوتر دانشگاه تهران @ai_cs_ut https://youtu.be/ALdavxiPeMs?si=v26ikoS_tyfU0ycr
❤13
ویدیو جلسه هشتم: Long Short-Term Memory (LSTMs) RNNs از دوره جامع Transformers and Diffusion models برگزار شده در دانشکده ریاضی، آمار و علوم کامپیوتر دانشگاه تهران @ai_cs_ut https://youtu.be/tUZs7gw_dSk?si=kX7XXhYQ94K81YVU
❤19👍2💯1🙏1
Showing the 12 most recent of 20 posts we hold for @ai_cs_ut. 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 — 1,133,238 of 1,189,255entries 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.
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.
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 10 August 2026 — this entry's latest reading, not the date you are reading this.
“کانال حلقه هوش مصنوعی دانشگاه تهران” (@ai_cs_ut), 1,134 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/ai_cs_ut.
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.