#enough2skim
Live, measured metrics for the hashtag #enough2skim from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #enough2skim
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Day-by-day usage
measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-28 23:42 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · fosstodon.org (Mastodon public search API) · fetched 2026-07-28 23:42 UTCNo related tags with measured usage found for #enough2skim.
Live pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-28 23:42 UTCEverything below is measured over the latest 6 public posts (spanning ~7234 hours).
Posting hours (UTC)
Languages: English (6)
Avg boosts / post: 1.3
Top of the latest posts
So many warn that evaluating with GPT favors GPT (or any LLM evaluating itself). Now it is also shown Science, not just educated guesses (Fig: T5, GPT, Bart each prefer their own) https://arxiv.org/abs/2311.09766 #enough2skim #scientivism #
A new benchmark for data 📚 Rather than test if a model is good This tests whether you can filter data 360 languages They also share metrics for data redundancy if you want just those https://arxiv.org/abs/2311.06440 https://github.com/toiz
🤖: Detecting if chatGPT made this text... It did not A survey on the (few) datasets and methods to detect it https://arxiv.org/abs/2309.07689 (not sure why chatGPT and not LLM in general, but NVM) #enough2skim #NLP #nlproc #chatgpt #LLM #L
Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/enough2skim