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Paper Citation Record · LEDGER

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering

As of 7 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2505.15038.

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

pith.paper-citation-record.v1
2505.15038 v2

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:30:22.804927Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

29 of 29 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved28
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c4a512aa-97f5-420f-847b-66e00b28f24a · outbound

This paper cites Understanding intermediate layers using linear classifier probes.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering Understanding intermediate layers using linear classifier probes

Reference 1

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no resolver link, observed 2026-08-07T15:30:20.574425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:30:20.574425Z digest=sha256:9e38cfba45afac68f3b53934ea55bd2cee82cf59e91fdc40344496b216222d90

Observation 4b98db61-803d-43f1-a45c-ce8a3ff174e7 · outbound

This paper cites an unresolved cited work.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering Unresolved cited work

Reference 2

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no resolver link, observed 2026-08-07T15:30:20.624619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:30:20.624619Z digest=sha256:c0043931d199b32c366d8bc58e6c01e5751e1b81844b17cd789325100d5f5363

Observation f767a57a-6f27-4a8c-ad8d-774bb4ee4c83 · outbound

This paper cites an unresolved cited work.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering Unresolved cited work

Reference 3

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no resolver link, observed 2026-08-07T15:30:20.661697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:30:20.661697Z digest=sha256:13fc2ba454e5ae18ad0ec36dfc6b41661be2cb4524938c647bf6df7b04662fc0

Observation 9c8e84e3-b568-4947-9b8a-9ba528f8ad9b · outbound

This paper cites an unresolved cited work.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering Unresolved cited work

Reference 4

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raw_fallback, observed 2026-08-07T15:30:24.105150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T15:30:20.730483Z digest=sha256:c8140a30d3ba530e7ac143d1b2f0f725128d596bf7847ca03f8bad8c7c503a26

Observation acf4663b-dc61-4218-9511-4a37b9e26459 · outbound

This paper cites Toy Models of Superposition.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering Toy Models of Superposition

Reference 5

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no resolver link, observed 2026-08-07T15:30:20.805089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:30:20.805089Z digest=sha256:e5ff036c75186948e819e19d411cdff93def751f1805507ee7ab00e09cdc2d44

Observation c04119bf-2f90-4b9f-8b3f-e5df7b6030ed · outbound

This paper cites Scaling and evaluating sparse autoencoders.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering Scaling and evaluating sparse autoencoders

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T15:30:20.901633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:30:20.901633Z digest=sha256:a33e11c88d4026020e0534ae97af18e75b0df1802cef6311c0760ae37ae80790

Observation 94e961d9-3a53-49b2-8fec-3af767e6ca5e · outbound

This paper cites Llama Scope: Extracting Millions of Features from Llama-3.1-8B with Sparse Autoencoders.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering Llama Scope: Extracting Millions of Features from Llama-3.1-8B with Sparse Autoencoders

Reference 7

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unresolved
no resolver link, observed 2026-08-07T15:30:20.974878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:30:20.974878Z digest=sha256:efd83dd3843e99a3105a327486a094bcda0500e75ddd05469997c6c8544cd1ac

Observation d424c4f7-32fd-4dcd-9201-c843b9405c1e · outbound

This paper cites SAIF: A Sparse Autoencoder Framework for Interpreting and Steering Instruction Following of Language Models.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering SAIF: A Sparse Autoencoder Framework for Interpreting and Steering Instruction Following of Language Models

Reference 8

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unresolved
no resolver link, observed 2026-08-07T15:30:21.080448Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:30:21.080448Z digest=sha256:3e8b6931493220ea715d3535dc85c160deda75daa49ddd5d4545a59439287d59

Observation 2e96da92-1044-4c69-b58c-6500163e9fcd · outbound

This paper cites Improving Activation Steering in Language Models with Mean-Centring.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering Improving Activation Steering in Language Models with Mean-Centring

Reference 9

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no resolver link, observed 2026-08-07T15:30:21.140538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:30:21.140538Z digest=sha256:b022c0fa53c1da4d5f25683ed4bb5e6c4fcca2514adf9abb2b2837abcdad333b

Observation cd22533b-9f6c-49ed-b795-351f9708191c · outbound

This paper cites an unresolved cited work.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering Unresolved cited work

Reference 10

Resolution
unresolved
raw_fallback, observed 2026-08-07T15:30:23.972516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T15:30:21.185427Z digest=sha256:4b22513ac41b5c84a79268991e93527722cb49af921475ebb9c1459f1df21e69

Observation abe22b27-7cb0-4906-9c8a-b4bb8757cb0f · outbound

This paper cites Style Vectors for Steering Generative Large Language Model.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering Style Vectors for Steering Generative Large Language Model

Reference 11

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unresolved
no resolver link, observed 2026-08-07T15:30:21.230674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:30:21.230674Z digest=sha256:5fb15773e6534ce710b21ba5999596ac0c2afd67b7800ff91dff44c4975d5092

Observation c715f19e-34da-45d1-9d25-d3b0fab4ab85 · outbound

This paper cites an unresolved cited work.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering Unresolved cited work

Reference 12

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unresolved
no resolver link, observed 2026-08-07T15:30:21.276165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:30:21.276165Z digest=sha256:d22530fe7ba85a6c741959fc94c1bc0f72d17b60a9d6d6ea8097ac66a1dca631

Observation 201a46ff-68fa-4b96-95bd-71bb9cfebe6b · outbound

This paper cites Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2

Reference 13

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unresolved
no resolver link, observed 2026-08-07T15:30:21.356728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:30:21.356728Z digest=sha256:cc96a4ac5f4d4be0d61ae01a2ae80676a85af3cccc04e35da2354bc35feaa67d

Observation fcc47d5e-3a73-4988-8fc7-f3ca0ca8939a · outbound

This paper cites an unresolved cited work.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering Unresolved cited work

Reference 14

Resolution
unresolved
raw_fallback, observed 2026-08-07T15:30:23.793886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T15:30:21.439684Z digest=sha256:edaad6de0ef4a90530b7fd55039efb5646873b7eec7a4bea60eea6894b6c8742

Observation e6aee399-47a2-4221-90da-cf60498f4283 · outbound

This paper cites In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering

Reference 15

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unresolved
no resolver link, observed 2026-08-07T15:30:21.522969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:30:21.522969Z digest=sha256:ad0adc56ff3d7b12949b58f1fbe0e72f0509874db7ee82170de2fe98e1cfdbda

Observation d9277a90-7d53-45b4-a424-402393b8b4df · outbound

This paper cites The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T15:30:21.599322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:30:21.599322Z digest=sha256:b9cc366021263fa8d6f02aebea5b290565a2d5514642006188cf5700e0adceb8

Observation 3424a7f0-ba9a-476c-ada1-b166908d5378 · outbound

This paper cites an unresolved cited work.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering Unresolved cited work

Reference 17

Resolution
unresolved
raw_fallback, observed 2026-08-07T15:30:23.660873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T15:30:21.686367Z digest=sha256:caaa27b17ded9cec65db913abb48216ef647a7ce8483eaf6dfa69ed0c7db4050

Observation 4820c29c-ea39-43c9-9093-cab79cc64f85 · outbound

This paper cites Steering Llama 2 via Contrastive Activation Addition.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering Steering Llama 2 via Contrastive Activation Addition

Reference 18

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unresolved
no resolver link, observed 2026-08-07T15:30:21.739066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:30:21.739066Z digest=sha256:855b79316920b61d37e25ed4d550274d3c1bcc94dca71f71289b9dffe783eac4

Observation b71ef92c-986b-492d-bf4c-c50c5a7a7587 · outbound

This paper cites Open Problems in Mechanistic Interpretability.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering Open Problems in Mechanistic Interpretability

Reference 19

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unresolved
no resolver link, observed 2026-08-07T15:30:21.825428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:30:21.825428Z digest=sha256:93875f24a513b1507cdee17a3598ff687c76f74bf4b06b7585791602cca2a757

Observation 87ed623a-6a64-4efb-94fa-1a8fbe0d7058 · outbound

This paper cites an unresolved cited work.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering Unresolved cited work

Reference 20

Resolution
verified exact
raw_fallback, observed 2026-08-07T15:30:23.177980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T15:30:21.916267Z digest=sha256:258c5e3df896678faf6d7ae676ef47830bf1695e061fe9c0b9460e834c87bd78

Observation d070b568-4c8d-4f55-a4d4-d1f5b0a05c2b · outbound

This paper cites an unresolved cited work.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering Unresolved cited work

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T15:30:21.972928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:30:21.972928Z digest=sha256:806e89a6c86a57b58c1edd3069801bebc6eba4153d39004444e4540058abda6f

Observation 07e0aa73-af02-4598-9da3-79196be7edc4 · outbound

This paper cites Improving Instruction-Following in Language Models through Activation Steering.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering Improving Instruction-Following in Language Models through Activation Steering

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T15:30:22.087008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:30:22.087008Z digest=sha256:6b470837c28fb22117623c781a8e7cd1edcd398c4f71429f021fba3c4e429989

Observation 7de8091e-ac4c-4508-b0d3-378160996a71 · outbound

This paper cites an unresolved cited work.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering Unresolved cited work

Reference 23

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unresolved
no resolver link, observed 2026-08-07T15:30:22.166542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:30:22.166542Z digest=sha256:8fb93c2dd72809f943d92cc83c1b2afc39e7a08e28f40c0992ff230544dc5877

Observation 7a9fc4e6-95b4-4fb6-a4ba-502bb7e25f20 · outbound

This paper cites AxBench: Steering LLMs? Even Simple Baselines Outperform Sparse Autoencoders.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering AxBench: Steering LLMs? Even Simple Baselines Outperform Sparse Autoencoders

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T15:30:22.282961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:30:22.282961Z digest=sha256:4b9b74d8355d8156e5d9e39131a9bdf2ab3a69e3f53b9dcbe723001ccf2e036b

Observation 02064c76-1602-444d-b873-008b358aec07 · outbound

This paper cites Uncovering Latent Chain of Thought Vectors in Language Models.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering Uncovering Latent Chain of Thought Vectors in Language Models

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T15:30:22.389509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:30:22.389509Z digest=sha256:b7d18f4e5ce42b9bed28e840bba886b00d00ea099ea6cf4b25050811a68ffbeb

Observation 37472da4-fdd5-45de-8e4e-444bc9b51b85 · outbound

This paper cites an unresolved cited work.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering Unresolved cited work

Reference 26

Resolution
unresolved
raw_fallback, observed 2026-08-07T15:30:23.501130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T15:30:22.506718Z digest=sha256:12f2ddc7ace196fc8fd8fe3f7ade3a265b6623c17b92afcaab58b64ec3a7bdaf

Observation 82d1651b-11e6-416f-b5e6-6ca25a3eb113 · outbound

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

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering Representation Engineering: A Top-Down Approach to AI Transparency

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T15:30:22.604271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:30:22.604271Z digest=sha256:3ecb37a4f03d8f1b50b4f9ea0849a834c88b571b6810bc9f5918c3f8da135be7

Observation 3fe23466-4c05-46bd-9a57-9b325f8c6c3b · outbound

This paper cites online" 'onlinestring :=.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering online" 'onlinestring :=

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T15:30:22.721748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:30:22.721748Z digest=sha256:1f7f2110a288cd1ef081558525b7e769dfe2851226458d69d05c68955d51ab53

Observation c374dd58-71b9-4f75-8c3f-01ec59ca538e · outbound

This paper cites write newline.

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering write newline

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T15:30:22.804927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:30:22.804927Z digest=sha256:75c50a3be88c90c8ef1d3a872c0ff0f2d8735c366d27eda8e6b8f6a92690a6fe

Pith citing papers

No inbound Pith citation observations are available.