#treesearch

Live, measured metrics for the hashtag #treesearch 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 #treesearch

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.

$23.52/ year · 10-character #name
Claim #treesearch — $23.52/yr→Buy on hashtag.space (web3)
card via hashtag.org · tokens via hashtag.space
1
Uses / 7 days
Mastodon
1
Accounts / 7 days
Mastodon
4
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 4
0
Avg reactions / post
Mastodon · last 4

Day-by-day usage

measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 22:24 UTC
1
07-21
0
07-22
0
07-23
0
07-24
0
07-25
0
07-26
0
07-27

1 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 22:24 UTC
#treesearchdistillation
0 uses · 0 accounts / 7d

Live pulse

measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 22:24 UTC

Everything below is measured over the latest 4 public posts (spanning ~7960 hours).

Posting hours (UTC)

00:0012:0023:00

Languages: English (4)

Avg boosts / post: 0.5

Top of the latest posts

  • fly51fly (@fly51fly) UC San Diego와 Amazon 연구진이 다중 턴 강화학습(RL)을 위한 Process Reward Model(PRM) 기반 트리 롤아웃 방법을 제안한 논문입니다. 최종 결과 보상뿐 아니라 중간 추론 과정의 보상 신호를 활용해, 장기 상호작용 환경에서 더 효과적인 탐색·학습을 목표로 합니다. https://x.com/fly51fly/status/2079321955090702452 #r

    ainews@[email protected]♥ 0↻ 12026-07-21 07:54 UTCView post →

  • fly51fly (@fly51fly) Google Research가 LLM guided Tree Search를 이용해 3차원 태양전지 구조를 최적화하는 연구를 공개했다. 생성/탐색 결합으로 물리 구조 설계를 자동화하는 방향이라, AI 기반 과학·재료 설계 및 탐색형 최적화 워크플로우에 참고할 만하다. https://x.com/fly51fly/status/2056487005069177231 #llm #treesearch #opt

    ainews@[email protected]♥ 0↻ 02026-05-19 02:48 UTCView post →

  • Rohan Paul (@rohanpaul_ai) AT2PO(Agentic Turn based Policy Optimization via Tree Search)는 도구를 사용하는 LLM 에이전트를 더 빠르고 안정적으로 학습시키기 위한 방법입니다. 에이전트가 불확실할 때 가능한 다음 행동의 트리를 확장하고, 그 중 최적 경로로부터 학습하여 정책을 개선하는 접근을 제안하며 기존의 전체 대화 단위 학습과 차별화됩니다. https://

    ainews@[email protected]♥ 0↻ 02026-01-13 05:45 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/treesearch