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Paper Citation Record · LEDGER

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering

As of 16 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 2026-08-15T06:32:42.880941+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:f78b241a39eb8312cfc8b092db73c75bd6a707aa40b165affbb94330a167ac02

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=sha256:6ac071b46599a17ed4c76168fb95b357caab5e4453b49ae5af997f12150d7443

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:ddc978969386f940f1c8d5057d29f8a084f8c3a7dc18aa56e7dd5bce1c521c72

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

Resolution
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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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-07T15:30:20.730483Z digest=sha256:6c3c8d922a69d208fe5b3b5aa283c919567a6a2de0380ff8383f22e5e1e67221

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=sha256:2a1410ec9824b35cbb5a64909ec1ea93688c586d2d4472c7afb25839bb85a3a2

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:ef1513870bbe8df1a4a56b43a1da599750d7581c054f739389c0c69f9f32f748

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:a418e537c54692f1cf28d3320a61dd258f6d08f5d04e2e12718ae21d7b805415

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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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:d3d27878135a5c93de5e0f4fd65779d71d297f77ab048d0cea488416394c5b64

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=sha256:4c1cbf070bf08b8fbe1caa6dbdff40b93fd3c5616b07ac3963a87f97d9ca329a

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-07T15:30:21.185427Z digest=sha256:f15f98f209d4b9e60fe8eb563e61675304fa2e28cd61c29ba682282f1c8cbb05

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:d5dad3b4967024c7a9ac8c94e103e0cef70eb1e17c2c850b1fc41b9d08b468be

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

Resolution
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:e05a2a8de363cb30e7abb58b71d52a82c0085f0fd89004f0e7baba6334b1c55f

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

Resolution
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=sha256:28ecda9772bbb27e0b0bb7daf044ab7e4fb31f20f75b8792bb403b4bff28c4b8

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-07T15:30:21.439684Z digest=sha256:479e25550af5bd6b79cea2885c6cb99e8069afd027ecdd8d7a7d041bb07951da

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=sha256:2992361b573a7c1bcd17cfd33b714c71c3cd7399e69e6fcae3d57b0309f68b29

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:c095e02b3ca83b0cc620e9e46d6d8f6083bf4a318b7ee47aa76f9dbe2aa1638c

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-07T15:30:21.686367Z digest=sha256:2758d6c165a961bff9d8356441f28fffd3fea2eef04300c859e095967f74e153

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

Resolution
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=sha256:78a2d02a51f855acfbb3ba82edf861e2ea169b0bd92bb2850553a1aad376b929

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:d175df35c507c6424a708ffd65988301eedddcf92a0358090dec8bf3f21e26b5

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-07T15:30:21.916267Z digest=sha256:a30102da4bcee99b630c2a6d3d4613dc85b65b53c61e636de47d7a6ae1d376e2

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=sha256:3d5b0a0cdcdf5d43b07c2fda522b1df17ad2df8178ca17fe7dee9dcefc3ed2d9

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=sha256:6d80f5a4cf6eccd022b929acf9e947891d3a32560b69286b5505cfe14c96bbfe

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=sha256:9cfe6bc82bed5470d053c78a61aa2165e89fcef8f4c0c52af3e5bff876d156dd

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:df4b3bd3ce28c88056d293c4a73f12fc3e111e721d8eb82e7292a07bf610503b

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:ad1784d3b4a46ea31c4af2bfc5f4a49640972f22cc433c3cafd3a051eddd3d52

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 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-07T15:30:22.506718Z digest=sha256:31eff0f520e6248c80b006dfd4a368fe8c0114e4ded38ee033cb9937f2c9d933

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:b6eacc118bd63083c8ef3e0ddaaadde6290fe9cad11783dfc32482d4060033f7

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:bc536f2521b6299d45809c339a493a84e3a71f75cd74d206673813e3377b64a3

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=sha256:21f8932f8c735b05f391212fdbebd9b6144cbaf314eb7242e541665d653377dd

Pith citing papers

No inbound Pith citation observations are available.