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Paper Citation Record · LEDGER

Transmuting prompts into weights

As of 5 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 2026-08-05T06:32:48.257954+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

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  • 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

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:01.294460Z digest=sha256:044fe4dee792385f8a5404bba11cabeb0671acce09ddc3e4d17822a06950dc1a

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:01.348027Z digest=sha256:723244e4d91e0219c738c2955cd55e189f4c7670197c5162248b13e75aad06ab

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=sha256:55bd0311ac9923b1bf960a0d6f6164df0ae3a1675554322f642cea56772b6d84

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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source=pdf_text observed=2026-08-04T10:49:01.578153Z digest=sha256:87d6787a5b89a288f9ab3e02fcc56eb59dfd5663b2d059018d2282d68367f653

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=sha256:2c9d9774e4aba6e91b0672a0ec6fe2e778b5d383e49e896329f591771086b80d

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=sha256:8dfab71af18318b28aa9f2182280c3fd4140dd04cb8f6cd909ec7411757e4f2c

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

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:02.042021Z digest=sha256:b0a75e36758112af7652de67eb28418fa7650bbf6595cb3810d07eb3844460e3

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

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:02.215814Z digest=sha256:ef134492e7573e2020e60cf5f5b6b473d762ba03a3e8d4d07f3c924c943ad759

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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source=pdf_text observed=2026-08-04T10:49:02.391531Z digest=sha256:d41f1cdbf2bc32db975fe18413ca6759d630cfe41ebd8fa9675004ba91c2fe7f

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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source=pdf_text observed=2026-08-04T10:49:02.565274Z digest=sha256:8873400410884dec2042ebbc2cbde08cdf47b74585b9c8673e54727caecf2dd0

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=sha256:334261ec7a13539a0b570f48f19f8ab171c2a56b31914b1dbc2175fc002c6096

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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source=pdf_text observed=2026-08-04T10:49:02.853156Z digest=sha256:f5cf56ef3ec4dbff8ce00ac8e5a6a129416e51a2a68d29df24d1a7ad6cac8890

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:f3cc49f1c02e66ef8ab19abeb89aa4034b6c7db0139a776485cc6d63a7d0bdfb

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

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:03.079086Z digest=sha256:9cc8d5160767e4bdad0a9fefe697b713f21cdef8fc06e9036e4055ab30e17e30

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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source=pdf_text observed=2026-08-04T10:49:03.217802Z digest=sha256:b9097fe395156e1918f671a766405eab9ec48b7d907ae608411fadcb1de46293

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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source=pdf_text observed=2026-08-04T10:49:03.336844Z digest=sha256:10823587ae40023414da9cc83addb3c3a138d0a570e11ba2e8a22361af70bc84

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:f642380c218f962ff089eb65fecefda1dbc90aa5691ea490f016c4a87c7ed0ff

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=sha256:54a44262cfd5ae52babae1bf08d0401e5208231c0feba5bd26572483d1da972c

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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source=pdf_text observed=2026-08-04T10:49:03.580933Z digest=sha256:0880ab29ba773e25bc7e347d0dde96d4165200311836301629e25c2557dfa178

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:f8663b821a668cb52345a9bb1dea7ce9d15b12c0da7839014f811936eb77c9b4

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=sha256:7baf9838c2941b0d3a5ba3cc0ebc3a16cd9f5d50830a8a04e987980c610b0dea

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=sha256:430db9591ffe063bad7424fb071719c4470a503bd11a6edc6d10b467cbabbcfa

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

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:49:03.834442Z digest=sha256:da525bfeff20bca8066c1e1188297a66dd84f53013ecfaea47672cf8a59de4e3

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:b63b7dee66bfc0a58d426c23634b3b70ff362f1cd0fa71d882a7ddd8ef5b12dc

Pith citing papers

No inbound Pith citation observations are available.