#adversarialml

Live, measured metrics for the hashtag #adversarialml 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 #adversarialml

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.

$5.00/ year · 13-character #name
Claim #adversarialml — $5.00/yr→
Annual, renews each year
Buy on hashtag.space (web3)
one-timepay once, yours for life
card via hashtag.org · tokens via hashtag.space
0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
12
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 12
0.4
Avg reactions / post
Mastodon · last 12

Day-by-day usage

measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 12:50 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 12:50 UTC

No related tags with measured usage found for #adversarialml.

Live pulse

measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 12:50 UTC

Everything below is measured over the latest 12 public posts (spanning ~31004 hours).

Posting hours (UTC) — busiest: 04:00

00:0012:0023:00

Languages: English (11) · French (1)

Avg boosts / post: 2

Top of the latest posts

  • Quite fascinating. If confirmed, this may reveal a structural weakness in how refusal is implemented in some LLMs. The accept/refuse mechanism may be relatively isolated in internal representations and therefore observable and manipulable —

    Hack in Days of Future Past@[email protected]♥ 3↻ 02026-03-15 15:09 UTCView post →

  • If you build and maintain a database of "fingerprints" of adversarial attacks, you can estimate which kind is being used against your model in real time. This tells you both about the technical sophistication of your adversary, and the stre

    adversarial-designs@[email protected]♥ 1↻ 22023-08-01 17:25 UTCView post →

  • Our paper on adversarially-robust regression was accepted to SaTML 2023 (https://satml.org) -- the first ever IEEE Conference on Secure and Trustworthy Machine Learning! I'm really excited about this conference and hoping to see it take off

    Daniel Lowd@[email protected]♥ 1↻ 42022-11-15 03:36 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/adversarialml