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Paper Citation Record · LEDGER

Transmuting prompts into weights

As of 9 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2510.08734.

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

pith.paper-citation-record.v1
2510.08734 v3

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T10:49:03.893003Z

measured 24 of 24 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

24 of 24 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved24
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a56a102c-e363-4f25-9aab-45b14980081d · outbound

This paper cites Learning without training: The implicit dynamics of in-context learning.

Transmuting prompts into weights Learning without training: The implicit dynamics of in-context learning

Reference 1

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no resolver link, observed 2026-08-04T10:49:01.294460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:01.294460Z digest=sha256:57874667081408c9e3e3c065b774520ed891394611f0321829ac9e2713327854

Observation 426404f5-7477-42d6-aa73-989fb7fa6694 · outbound

This paper cites an unresolved cited work.

Transmuting prompts into weights Unresolved cited work

Reference 2

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no resolver link, observed 2026-08-04T10:49:01.348027Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:01.348027Z digest=sha256:59ea9f19939d70c108fa82370ea15896b880788ac2d198dc29278f4a084296ad

Observation b4cd9f52-6fdc-4372-840e-25b89e9e7c09 · outbound

This paper cites Inference-Time Intervention: Eliciting Truthful Answers from a Language Model.

Transmuting prompts into weights Inference-Time Intervention: Eliciting Truthful Answers from a Language Model

Reference 3

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:01.441654Z digest=sha256:f35a8056d56803b9db3b9928cf456d5e9d56a3da4d0cdd9ec21388fd984a27a6

Observation 7940ec54-2048-4b59-ad0e-e5880f325092 · outbound

This paper cites Steering language models with activation engineering, 2025.

Transmuting prompts into weights Steering language models with activation engineering, 2025

Reference 4

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:01.578153Z digest=sha256:9e880c2c587f6dae512a67b250bc9a4bafddaebd12a2b5106558cd0ff015fb13

Observation 7de65b63-e3c3-4b33-8882-1e8d5246a63f · outbound

This paper cites Function vectors in large language models.

Transmuting prompts into weights Function vectors in large language models

Reference 5

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no resolver link, observed 2026-08-04T10:49:01.745268Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:01.745268Z digest=sha256:9ca857e0813dc6f4529a0863ff71235ab66beb1c891c51cc3ac7f7108ef67ba4

Observation dde73895-17d7-442a-a9a7-1a0cc00276b3 · outbound

This paper cites Locating and editing factual associations in GPT.

Transmuting prompts into weights Locating and editing factual associations in GPT

Reference 6

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no resolver link, observed 2026-08-04T10:49:01.897672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:01.897672Z digest=sha256:38ae72b7092f4ed86a25eecf2b136d0eed99714a78ea01eac930e303308c2e4f

Observation 9dc0c8a5-1004-4ece-8308-ae8bce0888c4 · outbound

This paper cites Fast model editing at scale.

Transmuting prompts into weights Fast model editing at scale

Reference 7

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no resolver link, observed 2026-08-04T10:49:02.042021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:02.042021Z digest=sha256:f700d3daa8f01cc1d2478869f901ed6f746c3de1f48248c662aa7d1ba365a2d3

Observation 3f752a1e-0956-4dbc-be13-cc04cf3456ba · outbound

This paper cites Byun, Zifan Wang, Alex Mallen, Steven Basart, Sanmi Koyejo, Dawn Song, Matt Fredrikson, J.

Transmuting prompts into weights Byun, Zifan Wang, Alex Mallen, Steven Basart, Sanmi Koyejo, Dawn Song, Matt Fredrikson, J

Reference 8

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no resolver link, observed 2026-08-04T10:49:02.215814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:02.215814Z digest=sha256:1b0306be0e5a6121969b71ee230ac6e3329ea18c666c72431f6194133f1daeb2

Observation 9b8dd970-7f31-4663-98b6-d2e3de118eb6 · outbound

This paper cites A unified understanding and evaluation of steering methods.ArXiv, 2025.

Transmuting prompts into weights A unified understanding and evaluation of steering methods.ArXiv, 2025

Reference 9

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no resolver link, observed 2026-08-04T10:49:02.391531Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:02.391531Z digest=sha256:f5aab7f67ebfde5131ed7ab649daa9579e30c12b15749118af3fd695d12ba72a

Observation 185ca4c5-3d1f-4173-9d18-0480aba1bd38 · outbound

This paper cites In-context learning creates task vectors.

Transmuting prompts into weights In-context learning creates task vectors

Reference 10

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no resolver link, observed 2026-08-04T10:49:02.565274Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:02.565274Z digest=sha256:b4404ae0052264c98116a2b758149c927dff504befd0b311b25a6712878ebd1d

Observation d292a625-39ed-480e-ad22-5e7eb3694f02 · outbound

This paper cites Analysing the generalisation and reliability of steering vectors.

Transmuting prompts into weights Analysing the generalisation and reliability of steering vectors

Reference 11

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:02.682353Z digest=sha256:6f6fa5df2296cc06af37fce181d7a275ce05db0171b68bef64f1e6ec45cd2b9b

Observation b2781232-74a0-46df-9089-ef4bbb67230f · outbound

This paper cites Towards Reliable Evaluation of Behavior Steering Interventions in LLMs.

Transmuting prompts into weights Towards Reliable Evaluation of Behavior Steering Interventions in LLMs

Reference 12

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:02.853156Z digest=sha256:90d4c1f3dbe2f6d606c6baafab3944043ca168afefe07f584e9f83b24320666f

Observation 4a63b250-31ba-41ca-86a6-a93426f031a9 · outbound

This paper cites Comparing bottom-up and top-down steering approaches on in-context learning tasks.ArXiv, 2024.

Transmuting prompts into weights Comparing bottom-up and top-down steering approaches on in-context learning tasks.ArXiv, 2024

Reference 13

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no resolver link, observed 2026-08-04T10:49:02.947155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:02.947155Z digest=sha256:36994208d56382c9bdcd471911230bc87589618fc7e9776ed4fe79bcb01eaff4

Observation d6dce485-a0b3-49f0-9ff5-afba5426b1c9 · outbound

This paper cites Task vectors in in-context learning: Emergence, formation, and benefit, 2025.

Transmuting prompts into weights Task vectors in in-context learning: Emergence, formation, and benefit, 2025

Reference 14

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no resolver link, observed 2026-08-04T10:49:03.079086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:03.079086Z digest=sha256:c4f7e3d0198519477e21721fdd7d5d7b6cf06f4f8eecd3c3125ea3e606279088

Observation cf025543-e954-4c4f-934f-590060de8385 · outbound

This paper cites Transformer feed-forward layers are key-value memories, 2021.

Transmuting prompts into weights Transformer feed-forward layers are key-value memories, 2021

Reference 15

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no resolver link, observed 2026-08-04T10:49:03.217802Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:03.217802Z digest=sha256:5d05f018a2938a4d7278e96174d313d988115c540dbc761c08c0fcbe67354327

Observation 4f332140-6f0c-405a-b533-a3617352cf00 · outbound

This paper cites Editing factual knowledge in language models, 2021.

Transmuting prompts into weights Editing factual knowledge in language models, 2021

Reference 16

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no resolver link, observed 2026-08-04T10:49:03.336844Z

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source=pdf_text observed=2026-08-04T10:49:03.336844Z digest=sha256:5186d022a0f47d6cde1095cd6028a2a3637900c42830f3f63c91e817da8a18b3

Observation e6c215ae-d0f6-4af7-932a-4e592580214c · outbound

This paper cites Assessing the brittleness of safety alignment via pruning and low-rank modifications.

Transmuting prompts into weights Assessing the brittleness of safety alignment via pruning and low-rank modifications

Reference 17

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no resolver link, observed 2026-08-04T10:49:03.422601Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:03.422601Z digest=sha256:ff81aa2e922807b3db2c293b91ca3bd8908b892759aed3e9dedea95efcb9711f

Observation 1e7b303a-11e5-4576-b2d4-4b3603562e6a · outbound

This paper cites Model editing as a robust and denoised variant of DPO: A case study on toxicity.

Transmuting prompts into weights Model editing as a robust and denoised variant of DPO: A case study on toxicity

Reference 18

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no resolver link, observed 2026-08-04T10:49:03.507053Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:03.507053Z digest=sha256:be867609fd31854304a1b1745715dc2465c2d0d8a74cefb822615391ef1c8751

Observation 440c5b6a-3a8f-4e95-92d2-e84a1fe31bbc · outbound

This paper cites Editing models with task arithmetic.

Transmuting prompts into weights Editing models with task arithmetic

Reference 19

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no resolver link, observed 2026-08-04T10:49:03.580933Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:03.580933Z digest=sha256:e30146b695de7c50687fc42265e5455506b79c9d1f8267e8bb60291feba71e4a

Observation 3d2c7d07-81de-4afc-8b65-282310bd94d9 · outbound

This paper cites What can transformers learn in-context? a case study of simple function classes.

Transmuting prompts into weights What can transformers learn in-context? a case study of simple function classes

Reference 20

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source=pdf_text observed=2026-08-04T10:49:03.624189Z digest=sha256:e6595e9fd155078bf2bc039151454d2bcb1ad6c126fbceacbd107dc24f005397

Observation 954e001c-f001-4f15-a437-ddbcd6302fbe · outbound

This paper cites Gemma 3 Technical Report.

Transmuting prompts into weights Gemma 3 Technical Report

Reference 21

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source=pdf_text observed=2026-08-04T10:49:03.689025Z digest=sha256:86781ff1343d2a10ee91b65951af30a121734a2201676593c4a85b2affc4c308

Observation bdbe1ac6-6bb3-4cdc-a9f6-240e93c78d5d · outbound

This paper cites , yn is a basis of the space (which implies that n=d ), then the inverse takes the form Z= X i ωiωT i , where the vectors ωi are the rows of Y −1.

Transmuting prompts into weights , yn is a basis of the space (which implies that n=d ), then the inverse takes the form Z= X i ωiωT i , where the vectors ωi are the rows of Y −1

Reference 22

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:03.776511Z digest=sha256:7b51b4b1482a23689e28433630d5cb0f6972e0b2ff1d0f0ba4617797a0a43248

Observation 7f74b036-c9ed-4d17-90f7-c52554010969 · outbound

This paper cites , yn is an orthonormal basis (n=d) of the space Z −1 =I.

Transmuting prompts into weights , yn is an orthonormal basis (n=d) of the space Z −1 =I

Reference 23

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no resolver link, observed 2026-08-04T10:49:03.834442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:03.834442Z digest=sha256:980807df5ac97984a761599ac4a7e3075b8892d86a0079ddde3240698f20a448

Observation e8467624-2cba-4aad-ac6b-1ef08f6fcb37 · outbound

This paper cites , yn are vectors independently sampled from a spherical distribution, then for nlarge enough Z −1 = 1 σ2n I, whereσ 2 is the distribution variance.

Transmuting prompts into weights , yn are vectors independently sampled from a spherical distribution, then for nlarge enough Z −1 = 1 σ2n I, whereσ 2 is the distribution variance

Reference 24

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no resolver link, observed 2026-08-04T10:49:03.893003Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:03.893003Z digest=sha256:b4f9b43aa9f1009a33756f8ce4e3909ed3493752f294fa57731ad1ce96ccc212

Pith citing papers

No inbound Pith citation observations are available.