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Paper Citation Record · LEDGER

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures

As of 17 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2607.27617.

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

pith.paper-citation-record.v1
2607.27617 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T04:38:50.463405Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

26 of 26 outbound references displayed

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  • unresolved26
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  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 525dd4db-f4ba-4980-b028-38ae4d601580 · outbound

This paper cites What is in R1? What value is stored in R1? Return the value of R1.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures What is in R1? What value is stored in R1? Return the value of R1

Reference 5

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source=pdf_text observed=2026-08-01T04:38:49.862323Z digest=sha256:646e8adc91aa57947dea4854d87c611964b031ce09cd7228224b807393d1aead

Observation 5cb0d65d-5647-4180-9069-ef12bb217580 · outbound

This paper cites Coordination Among Neural Modules Through a Shared Global Workspace.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures Coordination Among Neural Modules Through a Shared Global Workspace

Reference 7

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source=pdf_text observed=2026-08-01T04:38:47.695120Z digest=sha256:77751cf5e805c09ef2028bb57d84a616182599cc10d5d94dc57db6e2d9467dde

Observation b7e363d1-8075-43ea-8538-d5336d2af231 · outbound

This paper cites The Llama 3 Herd of Models.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures The Llama 3 Herd of Models

Reference 8

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source=pdf_text observed=2026-08-01T04:38:47.848813Z digest=sha256:67f7a84ccf08f1f960a70a10bc8d8944a45ae8d4d18df5c2026ebba43d2bb957

Observation ae59fc80-2cd8-41a8-9f87-112fcf225a01 · outbound

This paper cites Verbalizable Representations Form a Global Workspace in Language Models.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures Verbalizable Representations Form a Global Workspace in Language Models

Reference 9

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source=pdf_text observed=2026-08-01T04:38:47.969437Z digest=sha256:5b47c994ab9d76726340855772efbd4809df6f6ef764f713946f503cc87ab862

Observation 1b25919b-5a48-4033-a316-5cdd3fb9bfbd · outbound

This paper cites Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training

Reference 11

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source=pdf_text observed=2026-08-01T04:38:48.315072Z digest=sha256:fdcb6e471bad16d6decd6bb6b93daec808d0c0ed9997d3071e6286dc2781102a

Observation 742dbb2d-fc81-4d2a-990b-bbabf32eb826 · outbound

This paper cites The Linear Representation Hypothesis and the Geometry of Large Language Models.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures The Linear Representation Hypothesis and the Geometry of Large Language Models

Reference 13

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source=pdf_text observed=2026-08-01T04:38:48.558628Z digest=sha256:07be0c5fa80b01d2ee40763e8c88c87c8fc9f03f01f0d25fb92b72ec55848c7f

Observation 1de55a49-4185-4bdf-9369-cdbf6b1a54f2 · outbound

This paper cites The Model Organism Lottery: Model Organism Interpretability Strongly Depends on Training Methodology.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures The Model Organism Lottery: Model Organism Interpretability Strongly Depends on Training Methodology

Reference 14

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source=pdf_text observed=2026-08-01T04:38:48.704646Z digest=sha256:eca55f3a13cf987fa9f2424fda8785c33bedefb07bb3446b9d42cf9ce6a38f72

Observation 03d3824c-817b-4d15-b155-2161929e66cf · outbound

This paper cites Proofwriter: Generating implications, proofs, and abductive statements over natural language.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures Proofwriter: Generating implications, proofs, and abductive statements over natural language

Reference 15

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source=pdf_text observed=2026-08-01T04:38:48.828512Z digest=sha256:7c1c1634019b99951f81ba4a4e489c57365e617b340feaee66a727f05700d54e

Observation db2a2871-d1f4-45a8-9eac-10434247e324 · outbound

This paper cites Scaling monosemanticity: Extracting interpretable features from claude 3 sonnet—transformer-circuits.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures Scaling monosemanticity: Extracting interpretable features from claude 3 sonnet—transformer-circuits

Reference 16

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source=pdf_text observed=2026-08-01T04:38:48.948363Z digest=sha256:27d1327b24288eb9bc3132eb2c568df17ffe4c7407af0ba3974d14544de8b0f2

Observation bad18a71-8f05-4d9c-b017-d71e07bc5762 · outbound

This paper cites Steering Language Models With Activation Engineering.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures Steering Language Models With Activation Engineering

Reference 17

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source=pdf_text observed=2026-08-01T04:38:49.093668Z digest=sha256:dbdf94f0b97f683859d970c272a5c650b735ac670a2b2dbd15208f93215a4e3c

Observation fb5024ea-41ee-48c5-9aa3-63bcf72d1120 · outbound

This paper cites Model Organisms for Emergent Misalignment.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures Model Organisms for Emergent Misalignment

Reference 18

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source=pdf_text observed=2026-08-01T04:38:49.192379Z digest=sha256:51b21eaea1dc07fcb154195cc2498da3b7dd7bd450d51616cf1dbb4b5bdaa0c5

Observation b5f4d5b9-bccc-47af-b6b1-ba755438641c · outbound

This paper cites Representation Engineering: A Top-Down Approach to AI Transparency.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures Representation Engineering: A Top-Down Approach to AI Transparency

Reference 19

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source=pdf_text observed=2026-08-01T04:38:49.368600Z digest=sha256:3214ee8ab9d4c6c60e2bc1373fec289a7783ee9cc6123af55aabacb8c6060f0c

Observation 0c7e78b9-69c5-462b-b27a-88fbde0c9751 · outbound

This paper cites an unresolved cited work.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures Unresolved cited work

Reference 20

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source=pdf_text observed=2026-08-01T04:38:49.540080Z digest=sha256:933377e453775cf322f43ed8be7e13a2caa86bd07c8f81cb01bb766d8aa65f5e

Observation 28b47e0d-33d1-4cee-8454-08085ee51064 · outbound

This paper cites Supplementary Fig.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures Supplementary Fig

Reference 24

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source=pdf_text observed=2026-08-01T04:38:50.222566Z digest=sha256:eda5e1ebed392af39e15c9e42e7dcd8de84411186806ed87a25e5962e3acdb0c

Observation 25489f4d-d239-4a18-82de-b8dda0157f29 · outbound

This paper cites Density and hub overlap differ from matched null graphs at p <0.001.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures Density and hub overlap differ from matched null graphs at p <0.001

Reference 26

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source=pdf_text observed=2026-08-01T04:38:50.338846Z digest=sha256:6bafad4cbaf1a9acd69832285d5ac35168b55ebaa9b81ee0421f735691edc498

Observation c9e5789e-5aef-4026-8a5e-90195245000f · outbound

This paper cites The Shared architecture is favored under the tested operation bank and coding contract.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures The Shared architecture is favored under the tested operation bank and coding contract

Reference 64

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source=pdf_text observed=2026-08-01T04:38:50.463405Z digest=sha256:f5daa78cd12574f6b39104b2c43e196a4100ac6975bd6d2e0e2580dfde655e5e

Observation 65aa6cfa-f1d5-48b8-9337-ddbe5745b855 · outbound

This paper cites an unresolved cited work.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures Unresolved cited work

Reference 300

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source=pdf_text observed=2026-08-01T04:38:49.697066Z digest=sha256:43f8efb43eb49528ec2be526bc7bb088b34613c9ffffe29788f7475a59023211

Observation e24dcb9b-1607-4e90-916b-cfd26b790e70 · outbound

This paper cites always Shared.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures always Shared

Reference 512

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source=pdf_text observed=2026-08-01T04:38:50.022110Z digest=sha256:cc63c696aebde6bbbcafb20f9d5aef6f9237f27bfd7aa5b4155d10636bbb7863

Observation 958832b7-ea95-46ec-8014-a855eebab417 · outbound

This paper cites Most Current Model Organisms Are Leaky: Perplexity Differencing Often Reveals Finetuning Objectives.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures Most Current Model Organisms Are Leaky: Perplexity Differencing Often Reveals Finetuning Objectives

Reference 1993

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source=pdf_text observed=2026-08-01T04:38:46.959081Z digest=sha256:efa4fb8902c98336397f1af0a04bd712fc1453579930a1079de966f6be6431d8

Observation 652f6c59-9509-4d69-8400-22a9019ddd27 · outbound

This paper cites Principal component analysis.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures Principal component analysis

Reference 2000

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source=pdf_text observed=2026-08-01T04:38:48.448397Z digest=sha256:6fa8daf8222ff0de11341a4173725700c124e5ef14aa54525201e39fbb276094

Observation 81145fc9-2271-4a90-a257-8aa95e6d5e06 · outbound

This paper cites Scaling and evaluating sparse autoencoders.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures Scaling and evaluating sparse autoencoders

Reference 2021

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source=pdf_text observed=2026-08-01T04:38:47.319921Z digest=sha256:635d305271750bee78d60aace883a0f34b34c4923f4793fdfe641770762e6e46

Observation 185a0d8f-3d6a-4c1d-9262-4358f8ad36a4 · outbound

This paper cites The Consciousness Prior.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures The Consciousness Prior

Reference 2022

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source=pdf_text observed=2026-08-01T04:38:47.098855Z digest=sha256:b6bcbfc16adfdf7e17080123ae0a65346a518d4fb902773fe08e40c5bc1c0a4f

Observation 2c4911a3-76a3-4c47-a933-f075ac900c0b · outbound

This paper cites Sparse Autoencoders Find Highly Interpretable Features in Language Models.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures Sparse Autoencoders Find Highly Interpretable Features in Language Models

Reference 2023

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source=pdf_text observed=2026-08-01T04:38:47.201686Z digest=sha256:aa42f6e93473b549a8943779071ca69e63a41eb481169e54ebb9cccb311b601d

Observation 54dea94e-c682-4258-8e7a-fe02286e01dc · outbound

This paper cites Localizing Model Behavior with Path Patching.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures Localizing Model Behavior with Path Patching

Reference 2024

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source=pdf_text observed=2026-08-01T04:38:47.572549Z digest=sha256:c165d7013315b1a49be6a940a4e4256fe2d3a1991c2caf99a5b6284d6b16fd48

Observation 040dc338-e7f4-40cf-a6d5-09e949d9ebf7 · outbound

This paper cites Patchscopes: A Unifying Framework for Inspecting Hidden Representations of Language Models.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures Patchscopes: A Unifying Framework for Inspecting Hidden Representations of Language Models

Reference 2025

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source=pdf_text observed=2026-08-01T04:38:47.440173Z digest=sha256:bdc432279e64251e3cd091f00ab074ceb4f58c1a6880484aadcc011752bbb06a

Observation 047b2678-4406-449c-a449-06bd6f84fa9b · outbound

This paper cites In-context learning creates task vectors.

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures In-context learning creates task vectors

Reference 2026

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source=pdf_text observed=2026-08-01T04:38:48.144072Z digest=sha256:66765c6bafb63469b56d90d0a9757dddfc6c96c22a2e1f195338af19bd2d0bc4

Pith citing papers

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