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Paper Citation Record · LEDGER

Improving Steering Vectors by Targeting Sparse Autoencoder Features

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 25 inbound Pith citation observations for arXiv:2411.02193.

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

pith.paper-citation-record.v1
2411.02193 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 25 of 25 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:34:26.909588Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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  • malformed identifier0
  • metadata mismatch0

External citation measurements

1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation d87ac576-f7f9-4db6-9b55-bd6313842b14 · inbound

Interpretable Steering of Large Language Models with Feature Guided Activation Additions cites this paper.

Interpretable Steering of Large Language Models with Feature Guided Activation Additions Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 3

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unresolved
no resolver link, observed 2026-08-10T19:34:26.909588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T19:34:26.909588Z digest=sha256:00481d45b5f3cddd7e94fd7a5f76d4b26aafdc56063a556c3a67a611e80a48af

Observation 8e0726db-180b-438b-a167-df0d0d9fc048 · inbound

Analyze Feature Flow to Enhance Interpretation and Steering in Language Models cites this paper.

Analyze Feature Flow to Enhance Interpretation and Steering in Language Models Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 5

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no resolver link, observed 2026-08-09T10:11:51.456407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T10:11:51.456407Z digest=sha256:a92c6a59428054c1f7d6a543eb982e249bf1ad7ad17444a9ef7969722e032a48

Observation 3159d892-b602-495b-89bc-6bd7b45f991a · inbound

Steering Large Language Models for Machine Translation Personalization cites this paper.

Steering Large Language Models for Machine Translation Personalization Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 5

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unresolved
no resolver link, observed 2026-08-07T15:01:47.266440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:01:47.266440Z digest=sha256:d06a5c0864fdb0e43bd286989f87a0038e16b795f6181dd3c9745d29f0a12c9f

Observation d04aa17b-e3fd-4de2-a6cf-85e93322aba3 · inbound

Position: Mechanistic Interpretability Should Prioritize Feature Consistency in SAEs cites this paper.

Position: Mechanistic Interpretability Should Prioritize Feature Consistency in SAEs Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 9

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unresolved
no resolver link, observed 2026-08-07T14:02:59.154435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:02:59.154435Z digest=sha256:777cf16387de1fa6b5f46930d9867fcdbcf92d50ff39700cd5d446389b124b02

Observation 3d775816-7bcf-4e05-8ed6-7fdbe7c05813 · inbound

Beyond Prompt Engineering: Robust Behavior Control in LLMs via Steering Target Atoms cites this paper.

Beyond Prompt Engineering: Robust Behavior Control in LLMs via Steering Target Atoms Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 2024

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unresolved
no resolver link, observed 2026-08-07T14:38:52.048185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:38:52.048185Z digest=sha256:a4e1e2084f47ff8943462ecb25639d9ef1a8a9e6ca27efb406a7fb55a89c4b5c

Observation b2788b2d-648a-43fe-ad66-258085818b62 · inbound

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning cites this paper.

Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 7

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unresolved
no resolver link, observed 2026-08-07T12:30:03.859840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:30:03.859840Z digest=sha256:9c537b0da5118b803a5bb79548b5ee56fc9cc484d4a6bfb98d67dd1a0b18e658

Observation 249a05ac-306b-4253-be12-a13783ea0df7 · inbound

ReGA: Model-Based Safeguard for LLMs via Representation-Guided Abstraction cites this paper.

ReGA: Model-Based Safeguard for LLMs via Representation-Guided Abstraction Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 63

Resolution
verified exact
arxiv_id, observed 2026-05-19T11:37:16.005446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-19T11:34:09.428653Z digest=sha256:59ac7d29cdcd16741c818b28943f4341325a55b05d0dd64ceae07c421b44c1ad

Observation d8ea653f-a2ff-40a9-9f0f-2877412ba779 · inbound

Interpretation Meets Safety: A Survey on Interpretation Methods and Tools for Improving LLM Safety cites this paper.

Interpretation Meets Safety: A Survey on Interpretation Methods and Tools for Improving LLM Safety Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T10:24:26.327706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:24:26.327706Z digest=sha256:701ca480d7442e5a57e7080395fd7e8bab1885949e48c5dbf8c7bd50600027e1

Observation 5ecc1534-6c9f-49e4-81b8-68ce454375a6 · inbound

RACC: Representation-Aware Coverage Criteria for LLM Safety Testing cites this paper.

RACC: Representation-Aware Coverage Criteria for LLM Safety Testing Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-16T08:17:36.642532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-16T08:12:55.296932Z digest=sha256:dbf34feb2a222c15276bd5aefdadc86bb74896d7e62d12cc615b23ac56a85db6

Observation efe046f6-92c2-46b7-9b2f-cee2a16178d3 · inbound

The Cylindrical Representation Hypothesis for Language Model Steering cites this paper.

The Cylindrical Representation Hypothesis for Language Model Steering Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 4

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metadata mismatch
arxiv_id, observed 2026-07-01T00:15:09.223743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-01T00:10:29.122196Z digest=sha256:a988b76862ed8e60617beca85e913caabce64654c692e48d10b251ce30fac369

Observation 65f92ce2-2593-4cf3-a524-e6b9fcbb500a · inbound

All Circuits Lead to Rome: Rethinking Functional Anisotropy in Circuit and Sheaf Discovery for LLMs cites this paper.

All Circuits Lead to Rome: Rethinking Functional Anisotropy in Circuit and Sheaf Discovery for LLMs Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 139

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metadata mismatch
arxiv_id, observed 2026-05-14T20:52:57.527901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-14T20:52:47.074893Z digest=sha256:90979768b5e51abbf4cab50394b6e7b46d31d66d20e42e4ab834b26e2f393d2d

Observation f511845b-8969-4720-adb8-b16a3ba7c1c8 · inbound

REALISTA: Realistic Latent Adversarial Attacks that Elicit LLM Hallucinations cites this paper.

REALISTA: Realistic Latent Adversarial Attacks that Elicit LLM Hallucinations Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 27

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verified exact
arxiv_id, observed 2026-05-14T20:17:56.346581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-14T20:13:10.814899Z digest=sha256:aeda8f17614a00ffcf83c83107d8e5c3daa3581654eadbc5348c03fa3ea41870

Observation d2d3e1cc-94f8-4272-aa30-04606ceac725 · inbound

Multilingual Steering by Design: Multilingual Sparse Autoencoders and Principled Layer Selection cites this paper.

Multilingual Steering by Design: Multilingual Sparse Autoencoders and Principled Layer Selection Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:36:39.360944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-25T05:35:04.688774Z digest=sha256:de8fa8a03c67fc707596870b278df9afd35e90dd8c18a253ea8eb904c565a8ff

Observation 3bc28867-5b0b-4ff6-a2ce-5d611bb1657e · inbound

Steered Generation via Gradient-Based Optimization on Sparse Query Features cites this paper.

Steered Generation via Gradient-Based Optimization on Sparse Query Features Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:36:40.347296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-25T05:31:29.510639Z digest=sha256:5888a359583a669222b6e37fe2b2a843c9baebddf4d420676945b8402b177966

Observation ed9e2903-39d0-4779-bc04-32b6c2fb40e4 · inbound

Activation Steering for Synthetic Data Generation: The Role of Diversity in Downstream Safety Detection cites this paper.

Activation Steering for Synthetic Data Generation: The Role of Diversity in Downstream Safety Detection Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-06-29T14:03:29.915587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-29T13:53:27.306664Z digest=sha256:764c5a1688b7bd7d40dfd68d8f89174378e595a189623b1b80a2a0b94ffdf8b3

Observation 492e8566-3c24-4653-9b73-e8ab6757d336 · inbound

Sense Representations Are Inducible Interfaces cites this paper.

Sense Representations Are Inducible Interfaces Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 1

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T12:43:25.927568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-29T12:35:57.341052Z digest=sha256:63a87066aa41ec04539f0ec1e9647ad276e5b1cb0467cc1c8b1352a573215c42

Observation e7aa1c0c-293d-4012-957d-9cecb84c59f7 · inbound

Perplexity Can Miss SAE Feature Damage Under Quantization cites this paper.

Perplexity Can Miss SAE Feature Damage Under Quantization Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T01:36:25.775517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-28T11:41:18.460538Z digest=sha256:d49eebd7d5a923b9210162905d22ea8ad439d45de2bda796d9116540f0ba66fa

Observation 3caf54b0-a883-4c84-85a5-80e605dc1aeb · inbound

SAEExplainer: Interpreting SAE Features with Activation-Guided Preference Optimization cites this paper.

SAEExplainer: Interpreting SAE Features with Activation-Guided Preference Optimization Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-07-02T22:57:25.979965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-27T18:35:47.513717Z digest=sha256:e7655e3ed56f16d7c8a9c03728d083305e158a2df7259a4a2b8e920dce720270

Observation 57e5a1e5-e8bb-437e-9e79-25a1da05a53e · inbound

Data-Efficient Adaptation of LLMs via Attention Head Reweighting cites this paper.

Data-Efficient Adaptation of LLMs via Attention Head Reweighting Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 2020

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unresolved
no resolver link, observed 2026-08-02T05:16:33.834746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:16:33.834746Z digest=sha256:3026e614c645cf6b921b125f301aae516e8a04a94287a1ba0513c592d7b2f7ca

Observation e6ed6efa-fd40-47f7-9eb6-a9242dcde22b · inbound

Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models cites this paper.

Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-02T12:14:22.541696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T12:14:22.541696Z digest=sha256:7eab5413ac02e7e130f38e775ae0964f3f73ca0c01fb0121df89b691848729d4

Observation 889572a1-6481-45a4-8454-7b08237fae3b · inbound

Are Single-Token Sparse Autoencoder Features Causally Necessary? Layer-Depth and SAE-Family Effects cites this paper.

Are Single-Token Sparse Autoencoder Features Causally Necessary? Layer-Depth and SAE-Family Effects Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 10

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unresolved
no resolver link, observed 2026-08-01T10:03:54.246937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T10:03:54.246937Z digest=sha256:030550aa32005ec559c943bd84f16dc6d5fdc7a36bcb261b903c7742b86962cd

Observation c4d31c6b-6113-4383-8ef4-9414b4106360 · inbound

Toward Mechanistic Interpretability of an AI Foundation Model Fine-Tuned for Atmospheric Chemistry cites this paper.

Toward Mechanistic Interpretability of an AI Foundation Model Fine-Tuned for Atmospheric Chemistry Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 10

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unresolved
no resolver link, observed 2026-08-01T09:29:08.246807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T09:29:08.246807Z digest=sha256:08eb7ddc7d63c5403b3f67b78d50e8e2419d6ef6583497edbeeb31ddcfb63ef1

Observation e5ddab83-8554-4767-b1f0-ac42b38d2f86 · inbound

Where Steering Signals Come From: Activation Source Selection in Activation Steering cites this paper.

Where Steering Signals Come From: Activation Source Selection in Activation Steering Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 51

Resolution
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no resolver link, observed 2026-08-01T03:00:44.857125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:00:44.857125Z digest=sha256:e883a15899ee29878d7bc9a1db3ed2dd544d9a5d0773cb57639135cb4fe53b32

Observation 4d4d3ffb-4e11-41ee-9a8b-d23e084a3566 · inbound

Strengthening Target-Language Features: SAE-Based Steering for Multilingual Inference cites this paper.

Strengthening Target-Language Features: SAE-Based Steering for Multilingual Inference Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T13:56:22.619018Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T13:56:22.619018Z digest=sha256:866259011b8e43aa151af8c43643d130f54a344277639bd4e8b9fc8c58d4631b

Observation 2a5b0956-a5ef-4e89-837b-69cc09f4c8ac · inbound

Strengthening Target-Language Features: SAE-Based Steering for Multilingual Inference cites this paper.

Strengthening Target-Language Features: SAE-Based Steering for Multilingual Inference Improving Steering Vectors by Targeting Sparse Autoencoder Features

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-08T17:24:54.634750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:24:54.634750Z digest=sha256:67eaaa146f96cb0a160dc19940c9f2954186e452326fa95573e0996de58c3cd0