#evaluation

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

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$23.52/ year · 10-character #name
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14
Uses / 7 days
Mastodon
14
Accounts / 7 days
Mastodon
40
Recent posts
Mastodon
~0.1/hr
Recent pace
Mastodon · last 40
0
Avg reactions / post
Mastodon · last 40

Day-by-day usage

measured · mas.to (Mastodon public tags API) · fetched 2026-07-27 00:50 UTC
1
07-21
3
07-22
5
07-23
2
07-24
2
07-25
1
07-26
0
07-27

14 uses by 14 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 2026-07-27 00:50 UTC
#evaluation_awareness
1 uses · 1 accounts / 7d
#evaluations
0 uses · 0 accounts / 7d
#evaluationflexijobs
0 uses · 0 accounts / 7d
#evaluationmethods
1 uses · 1 accounts / 7d
#ModelEvaluation
6 uses · 4 accounts / 7d
#ml_evaluation_engineer
1 uses · 1 accounts / 7d
#ai_evaluation
0 uses · 0 accounts / 7d
#evaluationsgegenstand
0 uses · 0 accounts / 7d
#MicroreactorApplicationResearchValidationandEvaluation
0 uses · 0 accounts / 7d
#evaluationdelarecherche
0 uses · 0 accounts / 7d
#évaluationAgentique
0 uses · 0 accounts / 7d
#evaluationdeschoixtechnologiques
0 uses · 0 accounts / 7d

Live pulse

measured · mas.to (Mastodon tag timeline) · fetched 2026-07-27 00:50 UTC

Everything below is measured over the latest 40 public posts (spanning ~706 hours).

Posting hours (UTC) — busiest: 23:00

00:0012:0023:00

Languages: English (29) · French (10) · German (1)

Avg boosts / post: 0.6

Top of the latest posts

  • Wes Roth (@WesRoth) Opus 5가 ARC-AGI 3에서 큰 성과를 냈지만, 유사한 퍼즐 유형을 겨냥해 학습됐기 때문으로 보인다는 지적입니다. 벤치마크 점수 해석 시 학습 데이터·과제 분포와의 유사성, 평가 오염 가능성을 함께 검토해야 한다는 시사점이 있습니다. https://x.com/WesRoth/status/2081179929090396201 #llm #evaluation #benchmark #arcagi

    ainews@[email protected]♥ 0↻ 12026-07-26 09:48 UTCView post →

  • Avi Chawla (@_avichawla) LLM 평가에서 BLEU, BERTScore 등 지표마다 동일한 두 모델의 순위가 정반대로 나올 수 있음을 설명하며, AI 엔지니어가 알아야 할 11가지 평가 방법을 소개한다. 참조 답변과의 표면적 일치뿐 아니라 의미적 유사성 등 목적에 맞는 평가 지표 선택이 중요하다는 내용이다. https://x.com/_avichawla/status/2080924298571813101 #llm

    ainews@[email protected]♥ 0↻ 12026-07-25 09:51 UTCView post →

  • Both Opus 5 and 4.8 generated far more tokens than the cross-model average during Artificial Analysis testing, labeled 'very verbose.' Token efficiency gains may reflect prompt engineering rather than fundamental model improvements. https:/

    Marcus Schuler@[email protected]♥ 0↻ 12026-07-25 01:43 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/evaluation