#rewardmodels

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

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0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
2
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 2
0
Avg reactions / post
Mastodon · last 2

Day-by-day usage

measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-28 00:22 UTC
0
07-22
0
07-23
0
07-24
0
07-25
0
07-26
0
07-27
0
07-28

0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.

Related hashtags

measured · fosstodon.org (Mastodon public search API) · fetched 2026-07-28 00:22 UTC

No related tags with measured usage found for #rewardmodels.

Live pulse

measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-28 00:22 UTC

Everything below is measured over the latest 2 public posts (spanning ~3560 hours).

Posting hours (UTC)

00:0012:0023:00

Languages: English (2)

Avg boosts / post: 0

Top of the latest posts

  • LLM Evaluators are Biased across Languages 23개 언어에서 의미가 동일한 지시문·응답 쌍을 평가한 결과, LLM-as-a-Judge와 보상 모델은 언어별로 체계적으로 다른 점수를 부여했습니다. 서로 다른 아키텍처와 학습 방식을 가진 8개 오픈웨이트 평가기 및 프런티어 평가기에서 이 현상이 나타났으며, 저자원 언어일수록 더 관대하게 채점되는 경향이 관찰됐습니다. 쌍대 정확도는 90% 이상이어도

    ainews@[email protected]♥ 0↻ 02026-07-17 13:37 UTCView post →

  • Atticus Wang (@atticuswzf) 연구진이 보상모델(RM)이 특정 응답 형식을 선호하는 등 예상치 못한 선호를 보인다는 내용을 공개하며, 보상모델이 모델 행동과 정렬(alignment)에 미치는 영향을 밝히는 논문 초록을 제시하고 있습니다. RMs의 설계·평가 중요성을 강조합니다. https://x.com/atticuswzf/status/2024184099632455938 #rewardmodels #alignme

    ainews@[email protected]♥ 0↻ 02026-02-19 05:50 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/rewardmodels