#rewardmodeling
Live, measured metrics for the hashtag #rewardmodeling from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #rewardmodeling
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.
Day-by-day usage
measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 08:24 UTC1 uses by 1 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 2026-07-27 08:24 UTCNo related tags with measured usage found for #rewardmodeling.
Live pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 08:24 UTCEverything below is measured over the latest 2 public posts (spanning ~4284 hours).
Posting hours (UTC)
Languages: English (2)
Avg boosts / post: 0.5
Top of the latest posts
Séb Krier (@sebkrier) 사회적 가치 변화에 맞춰 AI 정렬을 조정하기 위한 엔드투엔드 파이프라인을 제안한 연구입니다. 개인화 보상 모델링, 추론 시점의 민주적 필터링, 특정 배심원 집단을 대상으로 한 적응을 결합해 가치관 변화와 집단별 선호를 반영하려 합니다. https://x.com/sebkrier/status/2081339797671448687 #aialignment #rewardmodeling #infer
Avi Chawla (@_avichawla) RULER의 핵심 통찰은 절대 점수 부여보다 상대적 스코어링이 더 쉽다는 점입니다. LLM 심판이 각각에 절대 점수를 매기기보다 '궤적 A가 B보다 낫다'처럼 상대 비교를 통해 판단하는 것이 보상 평가에서 더 간단하다는 설명을 담고 있습니다. https://x.com/_avichawla/status/2016502643032748415 #ruler #rewardmodeling #rl
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/rewardmodeling