#languagemodeling
Live, measured metrics for the hashtag #languagemodeling from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #languagemodeling
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 · mas.to (Mastodon public tags API) · fetched 2026-10-12 02:29 UTC1 uses by 1 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · mas.to (Mastodon public search API) · fetched 2026-10-12 02:29 UTCNo related tags with measured usage found for #languagemodeling.
Live pulse
measured · mas.to (Mastodon tag timeline) · fetched 2026-10-12 02:29 UTCEverything below is measured over the latest 14 public posts (spanning ~29351 hours).
Posting hours (UTC) — busiest: 14:00
Languages: English (13) · German (1)
Avg boosts / post: 0.4
Top of the latest posts
fly51fly (@fly51fly) NVIDIA 연구진이 텍스트를 토큰 단위 자기회귀 방식 대신 연속 확산(continuous diffusion) 과정으로 생성하는 Large Language Continuous Diffusion Models를 제안했다. LLM 생성 구조를 바꾸려는 연구로, 병렬 생성·추론 특성 및 기존 자기회귀 모델과의 품질/비용 비교가 핵심 검증 포인트다. https://x.com/fly51fly/stat
ICYMI: Explaining few-shot prompting: Few-shot prompting places a handful of worked examples inside the input to a language model so it infers a task without retraining. Mechanics, limits, disputes. https://ppc.land/few-shot-prompting/ #Few
🔮 Behold, the mystical prophecy of CS336! 🌟 Students are invited to glimpse the future of 2026, where they'll be serenaded by the dulcet tones of "Language Modeling from Scratch" every Monday and Wednesday. 🤖 No need to travel through ti
#languagemodeling across platforms
every network with a public tag surfaceFollow #languagemodeling 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/languagemodeling