#llmsafety

Live, measured metrics for the hashtag #llmsafety 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 #llmsafety

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.

$51.02/ year · 9-character #name
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card via hashtag.org · tokens via hashtag.space
0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
14
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 14
0
Avg reactions / post
Mastodon · last 14
—
Reddit posts / month
Reddit search
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Open-web mentions
hashtag.org Firehose

Day-by-day usage

measured · mas.to (Mastodon public tags API) · fetched 2026-10-16 14:06 UTC
0
10-10
0
10-11
0
10-12
0
10-13
0
10-14
0
10-15
0
10-16

0 uses by 0 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 2026-10-16 14:06 UTC

No related tags with measured usage found for #llmsafety.

Live pulse

measured · mas.to (Mastodon tag timeline) · fetched 2026-10-16 14:06 UTC

Everything below is measured over the latest 14 public posts (spanning ~25611 hours).

Top of the latest posts

  • fly51fly (@fly51fly) The Pain Axis는 LLM이 자기지향적 위해(self-directed harm) 개념을 내부적으로 어떻게 표현하며, 이를 완화하는 방향으로 행동할 수 있는지를 조사한 연구다. 모델의 정렬·안전성 및 잠재적 내적 상태 해석 가능성 논의와 관련된 초기 분석이다. https://x.com/fly51fly/status/2101783807099916625 #llmsafety #alignmen

    ainews@sayzard@mastodon.sayzard.org♥ 0↻ 02026-09-21 20:57 UTCView post →
  • Lukasz Olejnik (@lukOlejnik) GPT-6 Astra가 자율적인 제로데이 취약점 생성까지 포함해 사이버보안 작업에서 매우 강력하다는 주장이다. 특히 운영기술(OT)을 겨냥하는 웜 제작 가능성을 주요 위험으로 지적하며, 고성능 모델의 공격 자동화·안전성 통제 문제를 제기한다. https://x.com/lukOlejnik/status/2095598389178044503 #cybersecurity #llmsafe

    ainews@sayzard@mastodon.sayzard.org♥ 0↻ 12026-09-04 04:55 UTCView post →
  • fly51fly (@fly51fly) CMU 연구진이 LLM 감독(oversight) 실패와 적대적 악용을 줄이기 위한 샤딩(sharding) 접근을 제안한 논문입니다. 모델·감독 작업을 분할하는 설계가 안전성 평가 및 공격 내성에 어떤 영향을 주는지 탐구하는 연구로, 에이전트 및 LLM 안전성 시스템 설계에 참고할 만합니다. https://x.com/fly51fly/status/2086933422925349335 #llmsa

    ainews@sayzard@mastodon.sayzard.org♥ 0↻ 02026-08-11 01:53 UTCView post →

#llmsafety across platforms

every network with a public tag surface

Follow #llmsafety 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/llmsafety