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Paper Citation Record · LEDGER

Connecting the Dots: LLMs can Infer and Verbalize Latent Structure from Disparate Training Data

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2406.14546.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2406.14546 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:34:11.758174Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-12T10:01:29.579804Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 560dfe76-4e53-4706-94aa-4f106fedc1d0 · inbound

The Prompt is Mightier than the Example cites this paper.

The Prompt is Mightier than the Example Connecting the Dots: LLMs can Infer and Verbalize Latent Structure from Disparate Training Data

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T14:34:11.758174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:34:11.758174Z digest=sha256:0c7808b50c0924f591f8589ba7b6b16e70ddea5bd056bde40ef33cabd677ff54

Observation e4000abf-55d7-47dd-9335-9c7e27a51c26 · inbound

Model Organisms for Emergent Misalignment cites this paper.

Model Organisms for Emergent Misalignment Connecting the Dots: LLMs can Infer and Verbalize Latent Structure from Disparate Training Data

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T04:07:28.219516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:07:28.219516Z digest=sha256:e484eea35145b5d67f29cb50210b411e12fc7cbf875bdcdabc6a46c3e2c8d7af

Observation 3408638e-1214-4327-bd51-4847ba9a6e00 · inbound

Convergent Linear Representations of Emergent Misalignment cites this paper.

Convergent Linear Representations of Emergent Misalignment Connecting the Dots: LLMs can Infer and Verbalize Latent Structure from Disparate Training Data

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T04:09:27.678867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:09:27.678867Z digest=sha256:63a3590193756c0256b9fff45d10efe14aacf89c1c4e2bcc3922bd5ddc391250

Observation 754bff99-2877-43b2-ac82-fe61f88e9305 · inbound

Characterizing the Consistency of the Emergent Misalignment Persona cites this paper.

Characterizing the Consistency of the Emergent Misalignment Persona Connecting the Dots: LLMs can Infer and Verbalize Latent Structure from Disparate Training Data

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-12T10:01:29.582468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-07T08:06:58.635103Z digest=sha256:c7999e5bbbc0e7d3e43ece4c5c948593439a2b2ea90620858f55be494fd99658

Observation b1885033-e6ae-4ec6-bb3f-25c27ca3ddaf · inbound

Shared SFT Lessons Across Alignment, Model Organisms, and Toy Models cites this paper.

Shared SFT Lessons Across Alignment, Model Organisms, and Toy Models Connecting the Dots: LLMs can Infer and Verbalize Latent Structure from Disparate Training Data

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-01T00:38:42.989353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T00:38:42.989353Z digest=sha256:8e654b76dc876e730b8cd9025550ed405233d21baa52ba48411476be1a1bc434