#大型語言模型

Live, measured metrics for the hashtag #大型語言模型 from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.

hashtag.org network · sponsored

Own #大型語言模型

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.

$520.70/ year · 6-character #name
Claim #大型語言模型 — $520.70/yr→Buy on hashtag.space (web3)
card via hashtag.org · tokens via hashtag.space
11
Uses / 7 days
Mastodon
5
Accounts / 7 days
Mastodon
40
Recent posts
Mastodon
~0.1/hr
Recent pace
Mastodon · last 40
0.1
Avg reactions / post
Mastodon · last 40
—
Reddit posts / month
Reddit search
—
Open-web mentions
hashtag.org Firehose

Day-by-day usage

measured · mastodon.social (Mastodon public tags API) · fetched 2026-08-22 17:45 UTC
3
08-16
3
08-17
3
08-18
1
08-19
0
08-20
0
08-21
1
08-22

11 uses by 5 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.

Related hashtags

measured · mastodon.social (Mastodon public search API) · fetched 2026-08-22 17:45 UTC
#大型語言模型效能分析
0 uses · 0 accounts / 7d
#大型語言模型評測
0 uses · 0 accounts / 7d
#大型語言模型和
0 uses · 0 accounts / 7d
#大型語言模型兼容性
0 uses · 0 accounts / 7d
#大型語言模型_large_language_model
0 uses · 0 accounts / 7d
#大型語言模型_llm
0 uses · 0 accounts / 7d
#大型語言模型_large_language_models
0 uses · 0 accounts / 7d
#大型語言模型推論優化
0 uses · 0 accounts / 7d

Live pulse

measured · mastodon.social (Mastodon tag timeline) · fetched 2026-08-22 17:45 UTC

Everything below is measured over the latest 40 public posts (spanning ~506 hours).

Posting hours (UTC) — busiest: 07:00

00:0012:0023:00

Languages: Chinese (Taiwan) (36) · Chinese (2)

Avg boosts / post: 0.1

Top of the latest posts

  • 🌘 GenRec：邁向 Netflix 的 LLM 原生推薦系統 ➤ 擺脫繁雜特徵工程，以語意空間重塑個人化推薦體驗 ✤ https://netflixtechblog.com/genrec-towards-llm-native-recommendation-at-netflix-f20be6f643e3 Netflix 開發了名為 GenRec 的 LLM 推薦排行系統，旨在解決傳統推薦系統過度依賴繁雜手動特徵工程與專用架構的問題。該系統採用兩階段訓練框架，首先將開源模型

    GripNews@GripNews♥ 1↻ 02026-08-15 14:20 UTCView post →

  • 🌗 llama.app - llama.cpp 官方網站 ➤ 擺脫雲端限制，在個人裝置上打造安全且高效的本機 AI 運行環境 ✤ https://llama.app llama.cpp 是一款專為個人電腦設計的開源且完全本機運行的 AI 工具，無需 API 金鑰或網路連線即可保障個人隱私與資料安全。使用者只需透過簡單的指令即可完成安裝，並能無縫整合本地編碼助手。該工具針對多種硬體進行了優化，支援從 Apple Silicon 到各式 GPU 與 CPU 的架構，讓使用者能在

    GripNews@GripNews♥ 1↻ 02026-08-12 06:19 UTCView post →

  • 🌗 被竊取的思考：從專利 LLM API 中還原隱藏推理痕跡 ➤ 揭示加密思維鏈重放漏洞與隱私外洩危機 ✤ https://stolen-thoughts.com/ 本研究揭示了主流專利大型語言模型（如 OpenAI、Anthropic 和 Google）在 API 傳輸中，因使用可重複讀取的加密思維鏈數據包而產生的安全漏洞。研究人員藉由將強大模型的加密思維數據包注入至同體系但已被越獄的輕量模型中，成功繞過反蒸餾防護，以純文字還原強大模型的隱藏推理過程。此外，分析公開數據集

    GripNews@GripNews♥ 1↻ 02026-08-11 15:22 UTCView post →

#大型語言模型 across platforms

every network with a public tag surface

Follow #大型語言模型 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.

X (Twitter) ↗Instagram ↗TikTok ↗Facebook ↗LinkedIn ↗YouTube ↗Threads ↗Bluesky ↗Mastodon ↗Reddit ↗Pinterest ↗Tumblr ↗

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/大型語言模型