Channel
@ksenia_and_ai
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
24subscribers
+0 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1001889561541 |
|---|---|
| Type | Channel |
| Username | @ksenia_and_ai |
| Created | Between 1 October 2022 and 6 July 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 11 August 2026 |
| Last confirmed live | 18 September 2026 |
| Measurements held | 4 |
| Confirmed unchanged | 1 time, most recently 18 September 2026 |
| On Telegram | t.me/ksenia_and_ai |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 18 Sept 2026, 04:02 | 24 | -1 |
| 14 Aug 2026, 16:03 | 25 | +1 |
| 11 Aug 2026, 10:31 | 24 | no change |
| 6 Aug 2026, 06:49 | 24 | first reading |
20 posts held, back to 6 July 2023 — 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 page of 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 14 August 2023. An engagement rate over an empty window would be a number about nothing.
4 reactions across 4 posts, in 3 distinct kinds. The most used accounts for 50.0% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 2 | 50.0% | |
| 🔥 | 1 | 25.0% | |
| 😁 | 1 | 25.0% |
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 4 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 4 reactions 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 6 July 2023 to 14 August 2023, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Well… not to be calculative in order to ask for merits but in terms of fairness… whether I indeed wrote the last fresh paper or not. The last paper is a reusing of the first paper which I wrote from scratch almost by myself. I didn’t write the state of the art, Z&DG did, except the small part of LLMs that became the beginning of the introduction they also wrote (because me and GPT-4, we crafted it so well). DP reus…
🔥1
This summer I wrote …ok, in the last one I contributed but it was a big big journal article and there were a lot of things to write… three papers. And I haven’t even started my PhD. If I didn’t love the team I am working with I would never do anything similar. It’s a big deal, believe me, even when you have help. But yeah, it seems I found taste for academics. This is what my UPC master thesis supervisor, Marta R. …
The more papers I have opened trying to write the state of the art, the slower I write. I have 30 papers open rn and I should close 27, read the three that are left and finally do it.
Look how good my make up looks next to a pytorch profiler.
❤1
Woke up with the thought that I’ve written 2 papers this summer and I have to write one more by 14.08.
Well, I agree that learning grammar is a bit tricky. Since I remember myself I always was a bit of a linguist. (Not a bit, very much so, even if a self-taught one). I admit that without this base it can be complicated to do it fast. But I am sure there is a way.
I find the posts like this one ridiculous. https://t.me/kovinagorelik/298 I just cannot believe that people really try to fit language learning in a square box. For me the only way to learn a language is to understand in what form you like to consume the information, what sources you prefer to get it from and in what activities. And you have to learn grammar of course, this is crucial. And then you just do it. It…
https://www.science.org/doi/10.1126/sciadv.aaw2594
Discovered that I kinda like to write papers.
❤1
I dreamt about our project, David said that it is called nightmare. Understood some stuff about my own patterns of thinking which I didn’t like at all.
Impossible to scale (as with most KNN distances, I guess?) 🤷🏻♀️ but the idea is super pretty.
Pretty cool! this paper's nuts. for sentence classification on out-of-domain datasets, all neural (Transformer or not) approaches lose to good old kNN on representations generated by.... gzip (c) It's super elegant. If x1 and x2 are similar, then their joint compression (lzw/whatever) is more efficient. (c) https://twitter.com/giffmana/status/1679399205570326528?s=46&t=tJA3XyJ6UXEb-9Si1PfeJQ
Showing the 12 most recent of 20 posts we hold for @ksenia_and_ai. 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.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
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.
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.
Names
Channels on the register whose handles appear in this channel's posts.
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 18 September 2026 — this entry's latest reading, not the date you are reading this.
“Ksenia's Public Channel on #whatever” (@ksenia_and_ai), 24 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/ksenia_and_ai.
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.