#rewardlearning

Live, measured metrics for the hashtag #rewardlearning 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
3
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 3
0
Avg reactions / post
Mastodon · last 3

Day-by-day usage

measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 12:32 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 · fosstodon.org (Mastodon public search API) · fetched 2026-07-27 12:32 UTC

No related tags with measured usage found for #rewardlearning.

Live pulse

measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 12:32 UTC

Everything below is measured over the latest 3 public posts (spanning ~3642 hours).

Posting hours (UTC)

00:0012:0023:00

Languages: English (3)

Avg boosts / post: 0

Top of the latest posts

  • DATE: June 29, 2026 at 06:00PM SOURCE: PSYPOST.ORG ** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. ** ---------------------------------

    Psychology News Robot@[email protected]♥ 0↻ 02026-06-29 22:12 UTCView post →

  • fly51fly (@fly51fly) TOPReward 논문은 언어모델의 토큰 확률을 로봇 제어를 위한 숨겨진 제로샷 보상으로 활용하는 새로운 접근을 제안합니다. University of Washington과 Amazon 연구진이 제시한 이 방법은 보상 설계 없이 텍스트 기반 확률 정보를 보상 신호로 변환해 로봇 태스크에 적용하는 실험·분석을 담고 있으며 로보틱스에서 제로샷 보상 추출 가능성을 탐구합니다. https://x.c

    ainews@[email protected]♥ 0↻ 02026-03-02 07:46 UTCView post →

  • Sumanth (@Sumanth_077) 튜토리얼을 시도해본 후 RULER(Relative Universal LLM-Elicited Rewards)이 에이전트 행동에 자동으로 보상을 할당해 수작업 보상 설계(핸드크래프트 리워드 엔지니어링)를 제거해 준다는 점을 긍정적으로 평가한 코멘트입니다. RULER 기반 자동 보상 할당의 실사용 경험을 공유합니다. https://x.com/Sumanth_077/status/201651534

    ainews@[email protected]♥ 0↻ 02026-01-29 03:46 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/rewardlearning