15 Nov 2025, 06:31 UTC≈1,040 viewsread 6 August 2026
https://www.cell.com/trends/cognitive-sciences/fulltext/S1364-6613(25)00286-4
Channel
Vintage NLP for Work
@nlpfw
On this record: Growth · Engagement · What this channel posts · Posts · Citations · Cite this entry
1,101subscribers
+0 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 | -1001100803939 |
|---|---|
| Type | Channel |
| Username | @nlpfw |
| Description | Natural Language Processing for Work 频道历史内容的网页归档： https://www.notion.so/NLP-for-Work-af812710c3a543c2adc7acbdb3990036 For Work 系列频道 梗频道： @JISFW 图频道： @GfWR16 反馈投稿吹水群： @FishingFW 更多精彩： https://t.me/JISFW/13392 |
| Created | Between 1 January 2017 and 28 February 2018— 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 | 2 |
| On Telegram | t.me/nlpfw |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 6 Aug 2026, 18:01 | 1,101 | no change |
| 6 Aug 2026, 17:57 | 1,101 | first reading |
Engagement
20 posts held, back to 27 March 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 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 15 November 2025. An engagement rate over an empty window would be a number about nothing.
What this channel posts
- Photos
- 266
- Links
- 343
Lifetime counters from Telegram’s own channel header, read 6 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.
Recent posts
15 Oct 2025, 16:04 UTC≈1,200 viewsread 6 August 2026
惭愧第一次看到 hinton, 1986，整理下可能至少留意如下几种“分布的”的语源： - distributional semantics/hypothesis/representation (Harris, 1956) : 指用语料中分布情况来定义成“语义”，在当时可能希望把“分布”数学化但其实还是挺语言学的 - distributed representation(Hinton, 1986): 指特征并非是组织好的而是像神经元一样散落地在各处激活 而无论如何我们都可以用更数学（至少更概率统计）的方式来描述更当代的 representation了，上述语源可能也从 word2vec 开始合流，不再有区分的必要
15 Oct 2025, 15:47 UTC916 viewsread 6 August 2026
Forwarded from @LinghaoCh
https://gregorygundersen.com/blog/2025/10/01/large-language-models/ 预感这篇会是 LLM Researcher 必读：作者把跨越数十年的语言模型研究梳理成了一条清晰的时间线，讲述我们是怎么一步一步得到今天的 transformer based LLM 的。文章的思路非常 from first principles，并且用前后一致的符号串起了 N 篇不同的论文的要点。 非常喜欢文尾的一段话： > If you feel that it’s a bit perverse that next-word prediction is a sufficient objective to solve elite math problems, if this feels like a stochastic parrot outsmarting you, then you …
10 Oct 2025, 05:04 UTC754 viewsread 6 August 2026
看目录比想象的更有意思，内容不明（
10 Oct 2025, 05:04 UTC854 viewsread 6 August 2026
File
Theory of Deep Learning ( Sanjeev Arora ). 2022
14 Jul 2025, 07:59 UTC≈1,330 viewsread 6 August 2026
https://knowledge-flows.web.app/ 展示一部分ML概念系谱
28 Jun 2025, 12:46 UTCviews —
Channel name was changed to «Vintage NLP for Work»
30 May 2025, 06:16 UTC≈1,640 viewsread 6 August 2026
Photo
What, How, Where, and How Well? A Survey on Test-Time Scaling in Large Language Models https://testtimescaling.github.io/ 主要是这图整挺好（ 另附一篇相似目标的综述，称为长CoT https://long-cot.github.io/ 个人感觉这两篇只可以作为检索工具使用，或者帮新入学研究生建立低分辨率地图。推理发展内驱力还并不能完整地被这个分类学刻画，在机理解释性不足的现在也没有条件做理论家的工作，有那功夫直接做研究文章了（
20 May 2025, 05:17 UTC≈1,540 viewsread 6 August 2026
https://storage.googleapis.com/deepmind-media/Era-of-Experience%20/The%20Era%20of%20Experience%20Paper.pdf https://lilianweng.github.io/posts/2025-05-01-thinking/ https://ysymyth.github.io/The-Second-Half/ 三位RL学者近期巨作：转向经验学习 (R. Sutton) — 思考如何思考 (Lilian Weng) — 算法让位给产品(Shunyu Yao) 欢迎讨论～
19 May 2025, 13:31 UTC≈1,170 viewsread 6 August 2026
https://open.substack.com/pub/cameronrwolfe/p/llm-debugging
20 Jan 2024, 14:38 UTC≈3,160 viewsread 6 August 2026
https://thegradientpub.substack.com/p/ted-gibson-language-structure-communication-llms 才发现有transcripts了
5 Jul 2023, 12:44 UTC≈4,080 viewsread 6 August 2026
Photo
Binding Language Models in Symbolic Languages https://lm-code-binder.github.io/ ICLR23 top-25% 终于也开始实际地评估LLM转换形式语言的效果了
Showing the 12 most recent of 20 posts we hold for @nlpfw. 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.
Forward network
Republishes
Channels on the register whose posts this channel has forwarded.
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.
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 6 August 2026 — this entry's latest reading, not the date you are reading this.
“Vintage NLP for Work” (@nlpfw), 1,101 subscribers as measured 6 August 2026. Telegram Register, tgregister.com/channel/nlpfw.
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.