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Paper Citation Record · LEDGER

Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence

As of 7 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2607.17770.

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

pith.paper-citation-record.v1
2607.17770 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T17:08:25.162245Z

measured 19 of 19 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

19 of 19 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4523b8a5-15a8-4649-9242-9a7c0b515051 · outbound

This paper cites arXiv e-prints pp.

Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence arXiv e-prints pp

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e0502a4d-868a-491b-b465-e306c1225ff3 · outbound

This paper cites Mechanistic Interpretability for AI Safety -- A Review.

Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence Mechanistic Interpretability for AI Safety -- A Review

Reference 2

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Observation fa40db25-bb3f-46f7-bc5b-d79337df2af8 · outbound

This paper cites Transformer Circuits Thread (2023).

Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence Transformer Circuits Thread (2023)

Reference 3

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Observation 1cce40c1-227f-443d-b253-7959af414a22 · outbound

This paper cites SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders.

Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders

Reference 4

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Observation 6f14eda5-af57-4c0f-b611-c1678b412b11 · outbound

This paper cites arXiv:2508.15094 (2025).

Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence arXiv:2508.15094 (2025)

Reference 5

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Observation 4dd8c3b8-c1b4-4899-bdf6-77253f425631 · outbound

This paper cites an unresolved cited work.

Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence Unresolved cited work

Reference 6

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Observation 5f82a463-92e3-45cc-beda-e4bcb2dbfde5 · outbound

This paper cites In: Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing.

Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence In: Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing

Reference 7

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Observation e633d45e-ca0a-4e8c-84e1-e3c39ec823fe · outbound

This paper cites Scaling and evaluating sparse autoencoders.

Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence Scaling and evaluating sparse autoencoders

Reference 8

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Observation dcd39111-45cf-4b59-abd4-07662d631a9b · outbound

This paper cites arXiv:2506.19382 (2025).

Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence arXiv:2506.19382 (2025)

Reference 9

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Observation 696731d5-172d-49ae-abe5-d43e71c3fe41 · outbound

This paper cites In: The Twelfth In- ternational Conference on Learning Representations (2023).

Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence In: The Twelfth In- ternational Conference on Learning Representations (2023)

Reference 10

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Observation 2dca5fbc-2cd4-4bad-8624-8658b51b1266 · outbound

This paper cites In: International conference on machine learning.

Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence In: International conference on machine learning

Reference 11

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Observation 1dbfda0b-b9be-48c6-a183-833007727058 · outbound

This paper cites Distill3(3), e10 (2018).

Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence Distill3(3), e10 (2018)

Reference 12

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Observation 921a7648-ac66-4769-bc9d-3d26eb7f10a8 · outbound

This paper cites arXiv:2504.02821 (2025).

Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence arXiv:2504.02821 (2025)

Reference 13

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Observation 77720177-6661-4d0b-879c-b6f6fc5e4048 · outbound

This paper cites In: International conference on machine learning.

Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence In: International conference on machine learning

Reference 14

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Observation b7809fa3-b98e-4dc0-9ca3-5abd2b83d4aa · outbound

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

Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence Jumping Ahead: Improving Reconstruction Fidelity with JumpReLU Sparse Autoencoders

Reference 15

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source=pdf_text observed=2026-08-01T17:08:24.782022Z digest=sha256:122e64b49020b8cc46eabc2efae003922486426103fd5cc712b81adb31469296

Observation 4f8a3ed2-f864-4e6a-8adc-401b1d56f20b · outbound

This paper cites an unresolved cited work.

Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence Unresolved cited work

Reference 16

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Observation 220d9ea8-710d-463e-91e8-0c37a910be10 · outbound

This paper cites Psychological review84(4), 327 (1977).

Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence Psychological review84(4), 327 (1977)

Reference 17

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Observation 697ad268-1853-4b75-80ba-45d934ca0414 · outbound

This paper cites Advances in Neural Information Processing Systems29(2016).

Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence Advances in Neural Information Processing Systems29(2016)

Reference 18

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Observation 042d60b7-a730-412b-81af-7bb13f4d123c · outbound

This paper cites Interpreting CLIP with Hierarchical Sparse Autoencoders.

Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence Interpreting CLIP with Hierarchical Sparse Autoencoders

Reference 19

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Pith citing papers

No inbound Pith citation observations are available.