WeWorkBuddy

Named entitynamed-entityNewly observed

MSafeTemp

Safety alignment for Large Language Models is heavily focused on English with limited multilingual representation, particularly damaging low-resource language performance. Related open training datasets are often limited in size or do not follow region-localized harmful topics to broaden the scope of alignment beyond cultures. We propose a scalable template-

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First observed in our collection
Nov 5, 2026, 3:10 PM UTC
Earliest cited publication
Oct 29, 2026, 12:00 AM UTC
Last observed
Nov 5, 2026, 3:41 PM UTC

Evidence in the last complete seven days

Source mentions
1
Previous seven days 0
Distinct sources
1
Previous 0
Comparable growth
Not comparable
Ranking appearances
0

Collection observations and undated records are separate from dated publication counts. Observed in 7d:0 · Undated records:0

Collection coverage · Limited historyCurrent / previous observed days 7 / 3

Counts use complete UTC days. First observed means first seen by this collection, not when a term was coined.

Current window:2026-10-29 → 2026-11-05 (end excluded) · History 11 days

Observed source coverage by seven-day window
SourceCurrent daysPrevious daysLast success
arXiv63Nov 5, 2026, 10:00 AM UTC
arXiv72Nov 5, 2026, 10:01 AM UTC
Ask HN73Nov 5, 2026, 3:00 PM UTC
Ask HN73Nov 5, 2026, 2:30 PM UTC
Ask HN73Nov 5, 2026, 3:00 PM UTC
Ask HN73Nov 5, 2026, 3:00 PM UTC
GitHub73Nov 5, 2026, 12:15 PM UTC
GitHub Issues73Nov 5, 2026, 10:01 AM UTC
GitHub Releases71Nov 5, 2026, 12:00 PM UTC
GitHub73Nov 5, 2026, 2:30 PM UTC
GitHub Issues73Nov 5, 2026, 10:01 AM UTC
GitHub Releases73Nov 5, 2026, 3:14 PM UTC
GitHub73Nov 5, 2026, 2:30 PM UTC
GitHub Issues73Nov 5, 2026, 10:01 AM UTC
GitHub Releases73Nov 5, 2026, 3:14 PM UTC
GitHub Discovery00Nov 5, 2026, 3:13 PM UTC
GitHub Trending73Nov 5, 2026, 3:14 PM UTC
Google72Nov 5, 2026, 10:00 AM UTC
Hugging Face72Nov 5, 2026, 8:15 AM UTC
Hugging Face Spaces00Nov 5, 2026, 3:13 PM UTC
Hacker News73Nov 5, 2026, 12:45 PM UTC
Hacker News73Nov 5, 2026, 3:30 PM UTC
Hacker News73Nov 5, 2026, 3:30 PM UTC
Hacker News00Nov 5, 2026, 3:13 PM UTC
Show HN00Nov 5, 2026, 3:13 PM UTC
MIT News72Nov 5, 2026, 10:01 AM UTC
OpenAI73Nov 5, 2026, 11:30 AM UTC
Product Hunt73Nov 5, 2026, 12:45 PM UTC
量子位73Nov 4, 2026, 10:15 AM UTC
OpenRouter00Nov 5, 2026, 3:41 PM UTC
Hugging Face Models00Nov 5, 2026, 3:41 PM UTC
HF Daily Papers00Nov 5, 2026, 3:41 PM UTC
OpenRouter00Nov 5, 2026, 3:41 PM UTC
SEC EDGAR73Nov 5, 2026, 10:30 AM UTC
Sequoia Capital72Nov 5, 2026, 10:00 AM UTC
Simon Willison00Nov 5, 2026, 3:13 PM UTC
TechCrunch73Nov 5, 2026, 2:30 PM UTC
Contracts Finder73Nov 5, 2026, 10:00 AM UTC
V2EX73Nov 5, 2026, 2:30 PM UTC
  • Counts describe monitored public sources, not the whole web or search demand.
  • Both weeks need adequate, comparable collection coverage.

Daily history · up to 90 days

Bars show dated source mentions. The latest UTC day may be incomplete. Zero mentions and missing collection coverage are different conditions.

2026-10-222026-11-05
View accessible daily data
Daily source mentions and collection observations
UTC dateMentionsSourcesObservationsRanking appearances
2026-10-220000
2026-10-230000
2026-10-240000
2026-10-250000
2026-10-260000
2026-10-270000
2026-10-280000
2026-10-291100
2026-10-300000
2026-10-310000
2026-11-010000
2026-11-020000
2026-11-030000
2026-11-040000
2026-11-050011
Source reference for How I Aligned Your Model: Scaling Up Multilingual Safety Training with Templates. Screenshot not yet available.
Source record · preview pending · arxiv.orgOpen the source for the full page.

Source evidence

Sources in the evidence shown:HF Daily Papers 1

  1. HF Daily Papers · Published Oct 29, 2026

    How I Aligned Your Model: Scaling Up Multilingual Safety Training with Templates

    Safety alignment for Large Language Models is heavily focused on English with limited multilingual representation, particularly damaging low-resource language performance. Related open training datasets are often limited in size or do not follow region-localized harmful topics to broaden the scope of alignment beyond cultures. We propose a scalable template-

Review priority 39 / 100

This score orders research candidates. It is not search volume, a forecast or verified commercial demand.

  • Evidence

    8 / 30

    Distinct dated articles or first observations; repeat crawling adds nothing.

  • Publisher diversity

    8 / 25

    Conservative owner grouping; syndicated copies count once.

  • Comparable change

    0 / 20

    Comparable complete weeks only; no percentage from a zero baseline.

  • Recent evidence

    15 / 15

    Latest publication or first observation, not repeated fetch time.

  • Name specificity

    8.3 / 10

    Explicit entities and technical concepts outrank ambiguous acronyms.

Limitations and interpretation

  • First observation is a collection milestone, not proof that a word or product is new to the world.
  • Counts describe monitored public sources, not the whole web or search demand.
  • First observed here is not the invention date of a name or idea.
  • Candidates come from public titles, summaries and entity URLs, not verified full-text analysis.
  • Owner grouping is conservative; undisclosed syndication may remain.
  • Repeat ranking appearances are observations, not new articles or independent endorsements.
  • Both weeks need adequate, comparable collection coverage.
  • Sources behind this term changed or lack a comparable baseline.
  • Recent evidence includes collection over three days after publication.
  • The previous week is too small for a reliable percentage change.
  • Current evidence comes from one publisher or owner.

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