#posttraining
Live, measured metrics for the hashtag #posttraining from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #posttraining
This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.
Day-by-day usage
measured · mastodon.online (Mastodon public tags API) · fetched 2026-09-18 18:41 UTC2 uses by 2 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · mastodon.online (Mastodon public search API) · fetched 2026-09-18 18:41 UTCLive pulse
measured · mastodon.online (Mastodon tag timeline) · fetched 2026-09-18 18:41 UTCEverything below is measured over the latest 38 public posts (spanning ~8235 hours).
Posting hours (UTC) — busiest: 09:00
Languages: English (35) · German (2) · Dutch (1)
Avg boosts / post: 0.2
Top of the latest posts
What should you do if your academic publishers asks you to license a monograph for AI training? A few people have asked my advice on this recently so I’m sharing here in case it’s useful: Check if models have been trained on your monographs
Subham Sahoo (@ssahoo_) RL 기반 포스트트레이닝에서 speculative decoding은 가속 효과를 내기 어렵지만, diffusion adapters를 활용하면 30~40% 수준의 속도 향상을 비교적 쉽게 달성할 수 있다는 제안이다. RL 학습/추론 파이프라인 최적화 관점에서 검토할 만하다. https://x.com/ssahoo_/status/2100357465141617115 #posttraining
Xing Han Lu (@xhluca) 어떤 모델의 기술 보고서에 Blender 언급이 전혀 없다는 점을 지적하며, 해당 Blender 관련 성능이 제로샷 능력인지 혹은 포스트트레이닝 과정이 비공개인지 의문을 제기했다. 모델의 실제 학습·후처리 공개 범위와 재현 가능성 관점에서 볼 만한 논의다. https://x.com/xhluca/status/2099227975237468500 #llm #technicalreport #pos
#posttraining across platforms
every network with a public tag surfaceFollow #posttraining straight to each platform’s own tag page. Where a platform publishes open data we measure it above; the rest lock their numbers behind paid APIs, so we link rather than guess.
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/posttraining