#visionlanguage

Live, measured metrics for the hashtag #visionlanguage 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 #visionlanguage

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.

$5.00/ year · 14-character #name
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card via hashtag.org · tokens via hashtag.space
0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
33
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 33
0
Avg reactions / post
Mastodon · last 33

Day-by-day usage

measured · mastodon.online (Mastodon public tags API) · fetched 2026-07-27 13:30 UTC
0
07-21
0
07-22
0
07-23
0
07-24
0
07-25
0
07-26
0
07-27

0 uses by 0 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 2026-07-27 13:30 UTC

Live pulse

measured · mastodon.online (Mastodon tag timeline) · fetched 2026-07-27 13:30 UTC

Everything below is measured over the latest 33 public posts (spanning ~18014 hours).

Posting hours (UTC) — busiest: 17:00

00:0012:0023:00

Languages: English (33)

Avg boosts / post: 0

Top of the latest posts

  • fly51fly (@fly51fly) 비전-언어 모델에서 환각 이후의 추론(post-hallucination reasoning)을 다루는 연구입니다. 모델이 잘못된 시각 정보나 환각이 발생한 뒤 어떻게 추론을 이어가는지 분석하는 내용으로, 멀티모달 모델의 신뢰성 및 디버깅과 관련된 주제입니다. https://x.com/fly51fly/status/2075339232240132516 #visionlanguage #hallucin

    ainews@[email protected]002026-07-10 19:45 UTCView post →
  • fly51fly (@fly51fly) 음성/비전-언어 사전학습에서 negative pair 없이 end-to-end로 학습하는 LeVLJEPA 연구입니다. 멀티모달 표현학습과 사전학습 목표 설계에 관심 있는 연구자에게 참고할 만하지만, 아직은 연구 단계의 소식입니다. https://x.com/fly51fly/status/2073523607020662844 #visionlanguage #pretraining #multimodal

    ainews@[email protected]002026-07-05 18:44 UTCView post →
  • Justine Moore (@venturetwins) 실제 세계의 특정 장소를 매우 잘 인식하는 모델들의 능력을 보여주는 예시 트윗이다. NeurIPS 2025 포스터 홀, 스탠퍼드 캠퍼스를 자전거로 달리는 시점 등 간단한 프롬프트만으로도 장면을 생성하거나 이해하는 성능을 시연했다. 공간 이해와 현실감 있는 비전 모델의 발전을 시사한다. https://x.com/venturetwins/status/2040276591000117

    ainews@[email protected]002026-04-04 19:49 UTCView post →

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/visionlanguage