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Paper Citation Record · LEDGER

GDM AI Control Roadmap

As of 8 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2607.13087.

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

pith.paper-citation-record.v1
2607.13087 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T06:53:55.445729Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

47 of 47 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved47
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b60e1a69-0e63-447a-81d8-c5de76a9ea53 · outbound

This paper cites Claude S onnet 4.5 system card, 2025.

GDM AI Control Roadmap Claude S onnet 4.5 system card, 2025

Reference 1

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source=arxiv_source observed=2026-08-02T06:53:49.913689Z digest=sha256:8cd48dd54c9c65dd0bece0d27fd9c636e786c670906fd8bf7991fe341aef68ae

Observation cd29e084-35a7-4020-91b2-8234c5ef69ad · outbound

This paper cites How we contain Claude across products.

GDM AI Control Roadmap How we contain Claude across products

Reference 2

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source=arxiv_source observed=2026-08-02T06:53:49.977645Z digest=sha256:466ac4b6b018fa77a0942a580fc1fe586fb399613589ca5f6c9f0fcbb8e1b03f

Observation 34788628-32d2-424b-bdd3-ee8c3d30b04b · outbound

This paper cites Project G lasswing: Securing critical software for the AI era, 2026 b.

GDM AI Control Roadmap Project G lasswing: Securing critical software for the AI era, 2026 b

Reference 3

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source=arxiv_source observed=2026-08-02T06:53:50.034147Z digest=sha256:6813549bf284ce013a4511964246ae0344473c9d085e09cd590d979d5425b2b4

Observation 9a53884b-c9fa-4e7c-b628-2ad0685c88f1 · outbound

This paper cites Arnav, P.

GDM AI Control Roadmap Arnav, P

Reference 4

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source=arxiv_source observed=2026-08-02T06:53:50.226067Z digest=sha256:e0d5ffb64659cb70f7ee2c7842fabcefc95f0c9a6d5af551305dd81ec19de5ec

Observation 3ecf09f9-6aba-4b0c-aa42-7b87e27aba39 · outbound

This paper cites Obfuscated Activations Bypass LLM Latent-Space Defenses.

GDM AI Control Roadmap Obfuscated Activations Bypass LLM Latent-Space Defenses

Reference 5

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source=arxiv_source observed=2026-08-02T06:53:50.342415Z digest=sha256:0310901e3948e69bf3201777d0cb01a0e7f8f3670bfdaea4ccec36add75d1755

Observation 69dd53fd-b4f3-4cc5-9ba9-b6ab55ab4a8f · outbound

This paper cites Monitoring Reasoning Models for Misbehavior and the Risks of Promoting Obfuscation.

GDM AI Control Roadmap Monitoring Reasoning Models for Misbehavior and the Risks of Promoting Obfuscation

Reference 6

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source=arxiv_source observed=2026-08-02T06:53:50.414751Z digest=sha256:762b5984b98f7f719dec9ac1e0d754c0376a562ff169bfc6b770f69eb29be056

Observation 2b414687-1f94-4269-8c7b-571cb2e20a40 · outbound

This paper cites Ctrl-Z: Controlling AI Agents via Resampling.

GDM AI Control Roadmap Ctrl-Z: Controlling AI Agents via Resampling

Reference 7

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source=arxiv_source observed=2026-08-02T06:53:50.462952Z digest=sha256:c6f6b87286fbff2fd3cfb1f336ed28d386d3f81ff0510786a9b6e048059f8f23

Observation 0ccca1b0-3936-4f8a-bc48-9ad1e502a3f6 · outbound

This paper cites When Chain of Thought is Necessary, Language Models Struggle to Evade Monitors.

GDM AI Control Roadmap When Chain of Thought is Necessary, Language Models Struggle to Evade Monitors

Reference 8

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source=arxiv_source observed=2026-08-02T06:53:50.604505Z digest=sha256:9d2bf4bcd67f3ad4a7ce2864cf29fc9df36c187f7d9c03ca8b77fba5c6fccd6d

Observation fbd21a3e-9140-42de-9ed0-6f25cbc48774 · outbound

This paper cites Emmons, R.

GDM AI Control Roadmap Emmons, R

Reference 9

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source=arxiv_source observed=2026-08-02T06:53:50.754360Z digest=sha256:d654a63d23141d43e6a3f66312cb10ede3d93a90082eda90f22d8d09c1c339d4

Observation 225fd4d6-0711-4373-b380-a814be6e8910 · outbound

This paper cites The promise of white-box tools for detecting and mitigating AI deception, 2026.

GDM AI Control Roadmap The promise of white-box tools for detecting and mitigating AI deception, 2026

Reference 10

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source=arxiv_source observed=2026-08-02T06:53:50.874748Z digest=sha256:9f2b0ae3f98d9b2090272733228bdac7d1e604edce008fdc4bc74a0b95294187

Observation 9812df10-8555-47b0-8d26-7488c2ed337c · outbound

This paper cites Fronsdal, I.

GDM AI Control Roadmap Fronsdal, I

Reference 11

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source=arxiv_source observed=2026-08-02T06:53:50.974943Z digest=sha256:1d5a825b534136c5db38242c15d386c33ef1f66b66fc314a0eec042f41c2eeba

Observation bef678c0-f65b-4310-b63d-c497325f6c66 · outbound

This paper cites Detecting Strategic Deception Using Linear Probes.

GDM AI Control Roadmap Detecting Strategic Deception Using Linear Probes

Reference 12

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source=arxiv_source observed=2026-08-02T06:53:51.091332Z digest=sha256:661bce9e1695aeed20de506206d644959be3043c9eca945b6e1d4687a0c33991

Observation 8215f62a-b03c-4087-9586-ce4130e76f61 · outbound

This paper cites Frontier Safety Framework 3.1, 2025.

GDM AI Control Roadmap Frontier Safety Framework 3.1, 2025

Reference 13

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source=arxiv_source observed=2026-08-02T06:53:51.267213Z digest=sha256:5608884a178c1b7c871dac3c24edf822fba3e6edbb3177edb07c604ab40d5cb8

Observation d215e500-d378-4bf3-bc45-d73efd04439e · outbound

This paper cites Think Fast: Estimating No-CoT Task-Completion Time Horizons of Frontier AI Models.

GDM AI Control Roadmap Think Fast: Estimating No-CoT Task-Completion Time Horizons of Frontier AI Models

Reference 14

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source=arxiv_source observed=2026-08-02T06:53:51.434906Z digest=sha256:28cf3ebb7dce71fe8764d8c3245a3d122ff22b73eba07f12d126ef52114770fd

Observation 65958911-8a88-4054-b7e9-5277e811f816 · outbound

This paper cites Greenblatt.

GDM AI Control Roadmap Greenblatt

Reference 15

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source=arxiv_source observed=2026-08-02T06:53:51.644876Z digest=sha256:2245c76301cd1684a302d6bea838538e226f3a4fffd072af0046624f750b09da

Observation 7b3efadf-a322-4126-9fbc-6e8688fab083 · outbound

This paper cites Greenblatt and B.

GDM AI Control Roadmap Greenblatt and B

Reference 16

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source=arxiv_source observed=2026-08-02T06:53:51.767967Z digest=sha256:e5841891721b16881ec10b43e9b4168116f8a432488fe20658a675905d230a4c

Observation b6f05b4e-2134-4ea0-b1a8-32bde78b494b · outbound

This paper cites AI Control: Improving Safety Despite Intentional Subversion.

GDM AI Control Roadmap AI Control: Improving Safety Despite Intentional Subversion

Reference 17

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source=arxiv_source observed=2026-08-02T06:53:51.953667Z digest=sha256:0a69ba05f12dfdacec6ea9b63eface500727d9b32c086c327b8f68734fe39915

Observation e63ed777-bfbd-4e74-a559-785acc437361 · outbound

This paper cites an unresolved cited work.

GDM AI Control Roadmap Unresolved cited work

Reference 18

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source=arxiv_source observed=2026-08-02T06:53:52.074754Z digest=sha256:db5f36f9ea6b8b3fc1ca682d0d1f62c814bf84487a1ebf30f3f58aa3d03fca43

Observation fdede326-5f37-4bff-b822-02bb3f65a436 · outbound

This paper cites an unresolved cited work.

GDM AI Control Roadmap Unresolved cited work

Reference 19

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source=arxiv_source observed=2026-08-02T06:53:52.194753Z digest=sha256:08227e9ab8f343774f3ed67ecbed5725fb920172b050d50a5023ac223ead1fdf

Observation de8d2968-85ae-4be2-9af7-d37c10db74e0 · outbound

This paper cites CyScenarioBench : Evaluating LLM cyber capabilities through scenario-based benchmarking, 2025.

GDM AI Control Roadmap CyScenarioBench : Evaluating LLM cyber capabilities through scenario-based benchmarking, 2025

Reference 20

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source=arxiv_source observed=2026-08-02T06:53:52.252144Z digest=sha256:80a70b939ce5a033172f470d6dded4515e517fa40959363e2dfb36c8019ccf94

Observation 0998724f-f03a-44de-9197-387fb1ff2b7f · outbound

This paper cites Joglekar, J.

GDM AI Control Roadmap Joglekar, J

Reference 21

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source=arxiv_source observed=2026-08-02T06:53:52.267917Z digest=sha256:f45cf962b911c398f92f1217ac5253f25df0e415d79a5005a1fddf7bdba8a7bf

Observation 4f7a305e-8b05-4b77-932e-46a3c5b6e14b · outbound

This paper cites Karvonen, J.

GDM AI Control Roadmap Karvonen, J

Reference 22

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source=arxiv_source observed=2026-08-02T06:53:52.364481Z digest=sha256:85cc65161bf92ff49e84456fdc80ee6f095c6066f5f29ac32ba43621ad21999e

Observation c956e04d-15f3-4430-b18a-18ab741f967f · outbound

This paper cites Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety.

GDM AI Control Roadmap Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety

Reference 23

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source=arxiv_source observed=2026-08-02T06:53:52.430294Z digest=sha256:7fc8bc4ac214716c7365a2c3d01d31bbfb754c23d3c9df30a93baf40ba220fa5

Observation dda6b0ac-5ed6-43fb-abb1-cdcbeaa1d1e9 · outbound

This paper cites Realistic honeypot evaluations for scheming propensity.

GDM AI Control Roadmap Realistic honeypot evaluations for scheming propensity

Reference 24

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source=arxiv_source observed=2026-08-02T06:53:52.504746Z digest=sha256:f26805fdeffe1c23db9083ca5d1c3bc8ea9335706efb6dffb8adfa5adcdda8f1

Observation 3051a48b-11e3-4cbc-b860-6b0cf9bf53ce · outbound

This paper cites an unresolved cited work.

GDM AI Control Roadmap Unresolved cited work

Reference 25

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source=arxiv_source observed=2026-08-02T06:53:52.619409Z digest=sha256:0f784435d4582813304a4685fb94b0e24447a5cadc4c661f27d7e8b6220d75e1

Observation 85452ad1-235e-4b71-a20a-90b57c45cae9 · outbound

This paper cites an unresolved cited work.

GDM AI Control Roadmap Unresolved cited work

Reference 26

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source=arxiv_source observed=2026-08-02T06:53:52.760874Z digest=sha256:6892ffc9fd14bd57c931cbfb7fa0b8068909ac236e62d74de77609a067407b53

Observation 9f07c341-49e0-4e04-8348-1e35f1fcf668 · outbound

This paper cites The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning.

GDM AI Control Roadmap The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning

Reference 27

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source=arxiv_source observed=2026-08-02T06:53:52.876548Z digest=sha256:9642c447eda96e840e8eea7e03bb5ae56d48f57aebd6340d55a38b60ebd2e933

Observation bb809b1e-5110-4f7a-8c0f-0b612fd87520 · outbound

This paper cites Gram: Assessing sabotage propensities via automated alignment auditing.

GDM AI Control Roadmap Gram: Assessing sabotage propensities via automated alignment auditing

Reference 28

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source=arxiv_source observed=2026-08-02T06:53:53.022636Z digest=sha256:8c4c46a226f0e37fbad543dd94e5169abb84c658ff1ce22c69aeb51d9aad8a42

Observation 95a36e71-de68-452d-93ad-c64a3c7e6cc7 · outbound

This paper cites Subversion Strategy Eval: Can language models statelessly strategize to subvert control protocols?.

GDM AI Control Roadmap Subversion Strategy Eval: Can language models statelessly strategize to subvert control protocols?

Reference 29

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source=arxiv_source observed=2026-08-02T06:53:53.134779Z digest=sha256:c7a193cfc10bdb24a031a6c479b4dc3f9b8c8601ecc6c9369c42bd2171c34585

Observation 4956763c-4437-48e9-986e-a835920f2897 · outbound

This paper cites Auditing language models for hidden objectives.

GDM AI Control Roadmap Auditing language models for hidden objectives

Reference 30

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source=arxiv_source observed=2026-08-02T06:53:53.237703Z digest=sha256:4a13593cbc3bfb8a889d1e10e9a61768bc4c9700724e7c9971e6def6465b4240

Observation 72b105b1-5062-4a64-9ab7-c3c37ee33673 · outbound

This paper cites Task-completion time horizons of frontier AI models, 2026.

GDM AI Control Roadmap Task-completion time horizons of frontier AI models, 2026

Reference 31

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source=arxiv_source observed=2026-08-02T06:53:53.374750Z digest=sha256:bd0a775fd716e426906a3d23376df452287d5a5b029091c34b0f81e4220bf33f

Observation 192cb271-6098-420d-956a-ec9e1164dd75 · outbound

This paper cites MITRE ATLAS : Adversarial threat landscape for AI systems, 2021.

GDM AI Control Roadmap MITRE ATLAS : Adversarial threat landscape for AI systems, 2021

Reference 32

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source=arxiv_source observed=2026-08-02T06:53:53.492862Z digest=sha256:22d1d966e4043c1e20ee2852bcd27fef4d1d969822422aea858a920046f2c798

Observation ba2c8bdc-104f-410b-96ff-7f459093c8e8 · outbound

This paper cites an unresolved cited work.

GDM AI Control Roadmap Unresolved cited work

Reference 33

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source=arxiv_source observed=2026-08-02T06:53:53.619438Z digest=sha256:87e1762c130d636e58233ba35e00202f6f515d2c871090a70c86f0f5dd5f1403

Observation 5e88207b-b825-4644-be1b-a8eb585b8ab2 · outbound

This paper cites an unresolved cited work.

GDM AI Control Roadmap Unresolved cited work

Reference 34

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source=arxiv_source observed=2026-08-02T06:53:53.712253Z digest=sha256:2a55ede50ec6c716dbbc4939daa62833538710b56d8a3ee8900641ed0f7363e0

Observation 6e9174ec-fd47-475a-b7bb-abe34d266f80 · outbound

This paper cites Supply-chain levels for software artifacts ( SLSA ) specification, 2024.

GDM AI Control Roadmap Supply-chain levels for software artifacts ( SLSA ) specification, 2024

Reference 35

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source=arxiv_source observed=2026-08-02T06:53:53.828800Z digest=sha256:039f268508a93db2c4fe11d57f515b89cbbcd55a4dab0966cd16de0944c45f41

Observation 5b4c7b80-519f-4d73-92b8-35787c26c490 · outbound

This paper cites Schoen, E.

GDM AI Control Roadmap Schoen, E

Reference 36

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source=arxiv_source observed=2026-08-02T06:53:53.925597Z digest=sha256:10d7a37e23c789ae2b553e8e253eaed87d26e0b4dc06d5054882618eb713297f

Observation e3afdd97-fbe5-41e0-a0db-d3efa8b724dc · outbound

This paper cites An Approach to Technical AGI Safety and Security.

GDM AI Control Roadmap An Approach to Technical AGI Safety and Security

Reference 37

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source=arxiv_source observed=2026-08-02T06:53:54.095689Z digest=sha256:de3c1289812bebfac94b9965c323d264a94f2dcf6332fdcb6c3bc8604431bc76

Observation ea88e60f-152d-4073-a41a-7fc02255e71c · outbound

This paper cites Shlegeris.

GDM AI Control Roadmap Shlegeris

Reference 38

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source=arxiv_source observed=2026-08-02T06:53:54.235141Z digest=sha256:c67d06b53285cf4b418b9df28808cb6985d60a10c2ce23279eaa8c72fdcaaeed

Observation f01cf2a5-43e2-4c7c-a027-dafa9fa04a54 · outbound

This paper cites Singh, G.

GDM AI Control Roadmap Singh, G

Reference 39

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source=arxiv_source observed=2026-08-02T06:53:54.342918Z digest=sha256:00feed14e434aaf6026b5ca18088b8447915237154b240d56a675d71244c69ef

Observation 3e91a089-42f3-4617-b539-0f9d6d801131 · outbound

This paper cites Smith, B.

GDM AI Control Roadmap Smith, B

Reference 40

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source=arxiv_source observed=2026-08-02T06:53:54.506956Z digest=sha256:74cd735b5e18f5f46c91babc16c62e64178df7738d071338d1721557873d77b8

Observation dd3bd027-81d0-4e2f-951c-48c920634ea1 · outbound

This paper cites South, S.

GDM AI Control Roadmap South, S

Reference 41

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source=arxiv_source observed=2026-08-02T06:53:54.596538Z digest=sha256:c01ff3feb7db4b4049faf3e40794c728583b2df9f7b124da286cb55b82610255

Observation 7f196a27-55e8-455a-aa14-76a1569a8f4a · outbound

This paper cites Trębacz, S.

GDM AI Control Roadmap Trębacz, S

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-02T06:53:54.744803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T06:53:54.744803Z digest=sha256:f56f73927bc4ee8cbef29435faf9cd2284e8f36a675a2ded8f1587bd35f9cb0d

Observation 9a807262-9450-452f-870e-705c684766db · outbound

This paper cites Our evaluation of C laude M ythos P review’s cyber capabilities, 2026.

GDM AI Control Roadmap Our evaluation of C laude M ythos P review’s cyber capabilities, 2026

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-02T06:53:54.850139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T06:53:54.850139Z digest=sha256:d7a7d93900ae5f8d20a978c91841150936fda178fd5aee2da113ae3d9a4a19bc

Observation a14aec19-a154-4fcc-9891-280d7c55042c · outbound

This paper cites an unresolved cited work.

GDM AI Control Roadmap Unresolved cited work

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-02T06:53:55.005020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T06:53:55.005020Z digest=sha256:0337c979f3f1cc4bd583bdbb17cb9bce15861e1953531455f01aaeccfe8532a0

Observation d8005eaf-5f13-4793-b659-65e88abe04a7 · outbound

This paper cites Williams, C.

GDM AI Control Roadmap Williams, C

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-02T06:53:55.194748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T06:53:55.194748Z digest=sha256:2075cde6b2a836e44891397151de98602a9713e0570bfdaf43e626ef90d5dbdc

Observation 2935b1f3-0a75-418c-93d3-b2227aebe6bf · outbound

This paper cites Willison.

GDM AI Control Roadmap Willison

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-02T06:53:55.315608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T06:53:55.315608Z digest=sha256:00fd63827a3e8aae0cbe80cbeeca23e3c1e481c5fde55dc79bc6173913f143ef

Observation 4d1d7dad-f917-4254-9029-1928b1460641 · outbound

This paper cites an unresolved cited work.

GDM AI Control Roadmap Unresolved cited work

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-02T06:53:55.445729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T06:53:55.445729Z digest=sha256:569592c4205aae2fa59cbb201371a7ad8cc01e919e3fcd28f5ee2c1d582c069b

Pith citing papers

No inbound Pith citation observations are available.