Development

Adobe extracts large causal models from LLMs

development2025-12-27

Claim

Adobe researchers extracted large causal models from LLMs through prompting and scaffolding, against the argument that statistical models cannot reason causally.

Reporting date: 2025-12-27 (not necessarily the event date)

Sources

Attribution and reporting linked by this record; links do not imply independent verification.

Welcome to December 27, 2025 (theinnermostloop.substack.com)

Knowledge graphopen in browser →

Reported in

Welcome to December 27, 2025

Actor

Adobe

Evidence for

Scaffolding, not weights

Referenced by

Cite or correct this record

Citation formatCitation text

Adobe extracts large causal models from LLMs
Innermost Loop KB — secondary record
Reporting date: 2025-12-27
KB permalink: https://nicholsn.github.io/innermost-loop-kb/developments/2025-12-27-adobe-causal-models-from-llms
Claim: Adobe researchers extracted large causal models from LLMs through prompting and scaffolding, against the argument that statistical models cannot reason causally.
Attributed sources:
- Welcome to December 27, 2025 — https://theinnermostloop.substack.com/p/welcome-to-december-27-2025
This citation does not imply independent verification of linked-source claims.

Suggest a correction — opens a GitHub draft for you to review and submit.