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Decoupled Predictive Decision

Agent decisions depend on empirical relationships that deployment observations reveal and task descriptions alone may leave unresolved. We introduce Decoupled Predictive Decision Making (DPDM), an architecture that formulates heterogeneous agent decisions as conditional prediction with a shared pretrained learner. Language models provide semantic representat

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First observed in our collection
Nov 6, 2026, 9:49 AM UTC
Earliest cited publication
Nov 1, 2026, 12:00 AM UTC
Last observed
Nov 6, 2026, 5:34 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 / 4

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

Current window:2026-10-30 → 2026-11-06 (end excluded) · History 12 days

Observed source coverage by seven-day window
SourceCurrent daysPrevious daysLast success
arXiv64Nov 6, 2026, 12:30 AM UTC
arXiv73Nov 6, 2026, 5:15 AM UTC
Ask HN74Nov 6, 2026, 3:45 PM UTC
Ask HN74Nov 6, 2026, 3:30 PM UTC
Ask HN74Nov 6, 2026, 4:00 PM UTC
Ask HN74Nov 6, 2026, 4:00 PM UTC
GitHub74Nov 6, 2026, 12:45 PM UTC
GitHub Issues74Nov 6, 2026, 4:00 PM UTC
GitHub Releases72Nov 6, 2026, 12:15 PM UTC
GitHub74Nov 6, 2026, 2:30 PM UTC
GitHub Issues74Nov 6, 2026, 4:45 PM UTC
GitHub Releases74Nov 6, 2026, 4:45 PM UTC
GitHub74Nov 6, 2026, 2:30 PM UTC
GitHub Issues74Nov 6, 2026, 5:00 PM UTC
GitHub Releases74Nov 6, 2026, 4:45 PM UTC
GitHub Discovery10Nov 6, 2026, 4:00 PM UTC
GitHub Trending74Nov 6, 2026, 1:15 PM UTC
Google73Nov 6, 2026, 8:30 AM UTC
Hugging Face73Nov 6, 2026, 8:30 AM UTC
Hugging Face Spaces10Nov 6, 2026, 3:30 PM UTC
Hacker News74Nov 6, 2026, 1:15 PM UTC
Hacker News74Nov 6, 2026, 4:15 PM UTC
Hacker News74Nov 6, 2026, 4:15 PM UTC
Hacker News10Nov 6, 2026, 4:00 PM UTC
Show HN10Nov 6, 2026, 3:45 PM UTC
MIT News73Nov 6, 2026, 5:45 PM UTC
OpenAI74Nov 6, 2026, 11:45 AM UTC
Product Hunt74Nov 6, 2026, 1:15 PM UTC
量子位64Nov 4, 2026, 10:15 AM UTC
OpenRouter10Nov 6, 2026, 5:34 PM UTC
Hugging Face Models10Nov 6, 2026, 5:34 PM UTC
HF Daily Papers10Nov 6, 2026, 5:34 PM UTC
OpenRouter10Nov 6, 2026, 5:34 PM UTC
SEC EDGAR74Nov 6, 2026, 10:45 AM UTC
Sequoia Capital73Nov 6, 2026, 6:45 AM UTC
Simon Willison10Nov 6, 2026, 3:15 PM UTC
TechCrunch74Nov 6, 2026, 3:00 PM UTC
Contracts Finder74Nov 6, 2026, 8:00 AM UTC
V2EX74Nov 6, 2026, 3:00 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.

2026-10-232026-11-06
View accessible daily data
Daily source mentions and collection observations
UTC dateMentionsSourcesObservationsRanking appearances
2026-10-230000
2026-10-240000
2026-10-250000
2026-10-260000
2026-10-270000
2026-10-280000
2026-10-290000
2026-10-300000
2026-10-310000
2026-11-011100
2026-11-020000
2026-11-030000
2026-11-040000
2026-11-050000
2026-11-060011
Source page screenshot: Decoupled Predictive Decision Making: A Shared Conditional Predictor for Agents
Source page screenshot · arxiv.org

Source evidence

Sources in the evidence shown:HF Daily Papers 1

  1. HF Daily Papers · Published Nov 1, 2026

    Decoupled Predictive Decision Making: A Shared Conditional Predictor for Agents

    Agent decisions depend on empirical relationships that deployment observations reveal and task descriptions alone may leave unresolved. We introduce Decoupled Predictive Decision Making (DPDM), an architecture that formulates heterogeneous agent decisions as conditional prediction with a shared pretrained learner. Language models provide semantic representat

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

    14.6 / 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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