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Paper Citation Record · LEDGER

Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models

As of 9 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2607.19364.

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

pith.paper-citation-record.v1
2607.19364 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T12:14:24.446760Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

43 of 43 outbound references displayed

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External citation measurements

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Outbound references

Observation 15182ca5-23b2-4f7b-82d3-d82937361f24 · outbound

This paper cites Steering.

Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Steering

Reference 1

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Observation 6fa75ba0-a1b2-4f85-8fbe-94ca28e2b801 · outbound

This paper cites Steering Language Models With Activation Engineering.

Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Steering Language Models With Activation Engineering

Reference 2

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Observation 0974d567-9609-41da-bd64-7444ef0aebaa · outbound

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

Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Representation Engineering: A Top-Down Approach to

Reference 3

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Observation 6b281c3c-e5b4-4b40-9f28-4af75bf808f3 · outbound

This paper cites Refusal in Language Models Is Mediated by a Single Direction.

Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Refusal in Language Models Is Mediated by a Single Direction

Reference 4

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Observation 16fd195e-e8f7-4d6b-b70d-a90d254b73f0 · outbound

This paper cites Transformer Circuits Thread , year =.

Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Transformer Circuits Thread , year =

Reference 5

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Observation 6accbf9d-4ea4-4973-b48c-6e49216c7753 · outbound

This paper cites Transformer Circuits Thread , year =.

Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Transformer Circuits Thread , year =

Reference 6

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Observation f10210d7-9d47-42bb-a375-492b6f050f97 · outbound

This paper cites Scaling Monosemanticity: Extracting Interpretable Features from.

Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Scaling Monosemanticity: Extracting Interpretable Features from

Reference 7

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Observation f0ebb4d0-3a09-4f25-9a14-de85f5dfeffa · outbound

This paper cites Proceedings of the International Conference on Learning Representations (ICLR) , year =.

Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Proceedings of the International Conference on Learning Representations (ICLR) , year =

Reference 8

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Observation 266b7f8e-0d09-4056-b598-8e60d15df008 · outbound

This paper cites Proceedings of the International Conference on Learning Representations (ICLR) , year =.

Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Proceedings of the International Conference on Learning Representations (ICLR) , year =

Reference 9

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Observation 7e5ea7f8-9dd2-4201-9731-1a45f81ba0e3 · outbound

This paper cites Jumping Ahead: Improving Reconstruction Fidelity with JumpReLU Sparse Autoencoders.

Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Jumping Ahead: Improving Reconstruction Fidelity with JumpReLU Sparse Autoencoders

Reference 10

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Observation 3afb1d55-7274-4e81-94bc-bf46262e7fcd · outbound

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

Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on

Reference 11

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Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models 2025 , howpublished =

Reference 12

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Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models 2025 , pages =

Reference 13

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Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Enhancing

Reference 14

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Observation c3448cfe-826c-4350-808b-586e658cea6b · outbound

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Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Controllable

Reference 15

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Observation e109703e-fc9d-4f8a-ac41-132bda4543cd · outbound

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Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Physical Review E , volume =

Reference 16

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Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models 1988 , edition =

Reference 17

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Observation ee64df51-8ca7-49b1-8b87-8b06d0a931ad · outbound

This paper cites Journal of the Royal Statistical Society: Series B (Methodological) , volume =.

Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Journal of the Royal Statistical Society: Series B (Methodological) , volume =

Reference 18

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Observation fa3ad426-cef9-4869-8615-7f25c5b97661 · outbound

This paper cites Proceedings of the International Conference on Learning Representations (ICLR) , year =.

Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Proceedings of the International Conference on Learning Representations (ICLR) , year =

Reference 19

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Observation a7dc648c-4d5c-491e-8450-421747a268fc · outbound

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Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Unresolved cited work

Reference 20

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Observation 6b4a7a5c-2135-4358-977b-d46e30f93189 · outbound

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Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models OpenAI , year =

Reference 21

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Observation 2d307d59-1cf3-4264-ab3d-6cb28d0408a0 · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Gemma 2: Improving Open Language Models at a Practical Size

Reference 22

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Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Gemma 3 Technical Report

Reference 23

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

Reference 24

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Observation 6dcb7ec1-0357-4a43-8209-0ec9264f0332 · outbound

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Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Are Sparse Autoencoders Useful?

Reference 25

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Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Advances in Neural Information Processing Systems (NeurIPS) , year =

Reference 26

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Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models The Twelfth International Conference on Learning Representations , year =

Reference 27

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Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Aligning

Reference 28

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Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics , year =

Reference 29

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Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models 2022 , url =

Reference 30

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Observation 3d72ae91-9eb6-4282-95d2-bc056b0b658b · outbound

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Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics , year =

Reference 31

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Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Advances in Neural Information Processing Systems (NeurIPS) , year =

Reference 32

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This paper cites Analyzing the Generalization and Reliability of Steering Vectors.

Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Analyzing the Generalization and Reliability of Steering Vectors

Reference 33

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Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Open Problems in Mechanistic Interpretability

Reference 34

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Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models LogicBench: Towards Systematic Evaluation of Logical Reasoning Ability of Large Language Models

Reference 35

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Observation b0adfa73-84e8-4dc7-bc0e-7cb71b4b09c5 · outbound

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Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP '24) , year =

Reference 36

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Observation 64cab25c-598e-4005-8635-7c1863a873b2 · outbound

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Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Steering Llama 2 via Contrastive Activation Addition

Reference 37

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Observation 18c9bebb-d649-444d-b9e2-18013fac474c · outbound

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Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Advances in Neural Information Processing Systems , volume=

Reference 38

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T12:14:23.810797Z digest=sha256:ac1491737e341066cd66a3805d22412eee26b5749f35fe967fe3647fc84ddad6

Observation 64765344-6614-483e-a00e-b1ab61e8109f · outbound

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

Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Representation Engineering: A Top-Down Approach to AI Transparency

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-02T12:14:23.966994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T12:14:23.966994Z digest=sha256:0048397a141478fca40ed0b87da95cbfa4c308a7b44dc6c4e401fd35b21a5a9d

Observation 4081ecb0-9d9b-46e6-a17d-7109f1caa528 · outbound

This paper cites arXiv preprint arXiv:2502.02716 , year=.

Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models arXiv preprint arXiv:2502.02716 , year=

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-02T12:14:24.065960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T12:14:24.065960Z digest=sha256:d484d6494bcb0126fa74db96dce9a51c8a115fc0e4a4b9e9d86362a46bc2d109

Observation 14f91b66-05e3-4fb9-9ae9-c6a1569db8e1 · outbound

This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.

Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 41

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unresolved
no resolver link, observed 2026-08-02T12:14:24.226481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T12:14:24.226481Z digest=sha256:4a31e2aa63d89f1dc208f60bb6ccafffe8c6ea5a94abeefe0619d0c3b70c8e4f

Observation bf1277df-9268-4535-af31-3014a5ce0122 · outbound

This paper cites 2026 , month = mar, howpublished =.

Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models 2026 , month = mar, howpublished =

Reference 42

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unresolved
no resolver link, observed 2026-08-02T12:14:24.351786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T12:14:24.351786Z digest=sha256:3e3db2b1bdd20f0ddb2ee40f549d767158696c4653b99c65a4858d22d5ec43ee

Observation 0bcf11f5-5547-4fca-8f12-e20b19d03d7c · outbound

This paper cites an unresolved cited work.

Statistically Grounded Sparse-Feature Interventions for Activation-Space Control in Large Language Models Unresolved cited work

Reference 43

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unresolved
no resolver link, observed 2026-08-02T12:14:24.446760Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T12:14:24.446760Z digest=sha256:dc49d0db27256430240cd7e9e2d99ff9b6591056c4de12bbae0df4d77a88248b

Pith citing papers

No inbound Pith citation observations are available.