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Paper Citation Record · LEDGER

Are Sparse Autoencoders Useful? A Case Study in Sparse Probing

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 20 inbound Pith citation observations for arXiv:2502.16681.

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

pith.paper-citation-record.v1
2502.16681 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:44:42.625025Z

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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External citation measurements

0
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 65bad93b-77de-4a8e-b1ae-a764b8847d95 · inbound

Inference-Time Decomposition of Activations (ITDA): A Scalable Approach to Interpreting Large Language Models cites this paper.

Inference-Time Decomposition of Activations (ITDA): A Scalable Approach to Interpreting Large Language Models Are Sparse Autoencoders Useful? A Case Study in Sparse Probing

Reference 2008

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:42.625025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:42.625025Z digest=sha256:1e4b3d35f0a83df12f95a997c3c47a2ddeabb3c282e667b0d4c7684d1c46c9f0

Observation a7b3033b-cf0f-4785-b843-37bdeb121de3 · inbound

TRACE for Tracking the Emergence of Semantic Representations in Transformers cites this paper.

TRACE for Tracking the Emergence of Semantic Representations in Transformers Are Sparse Autoencoders Useful? A Case Study in Sparse Probing

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T14:42:11.515244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:42:11.515244Z digest=sha256:10415c0a79dd0c9a52fd1febe5f7a16a17a7f0f92a843095bacb5aaf60747f94

Observation cdd31f6d-49f1-4d16-9774-5f9653068ac4 · inbound

Fine-Grained Interpretation of Political Opinions in Large Language Models cites this paper.

Fine-Grained Interpretation of Political Opinions in Large Language Models Are Sparse Autoencoders Useful? A Case Study in Sparse Probing

Reference 23

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no resolver link, observed 2026-08-07T10:40:14.248537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:40:14.248537Z digest=sha256:dbe0159e92cf473dac4de88fce1234beb3f700a69614539e3e2d3395cce2afdd

Observation d1d05748-dbe8-4555-92b9-b0b5554f5658 · inbound

Cross-Layer Discrete Concept Discovery for Interpreting Language Models cites this paper.

Cross-Layer Discrete Concept Discovery for Interpreting Language Models Are Sparse Autoencoders Useful? A Case Study in Sparse Probing

Reference 20

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unresolved
no resolver link, observed 2026-08-06T23:03:04.969024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:03:04.969024Z digest=sha256:8c48a960f0f25103723171fa14d506cffda97804cf2eddbc1d3a5189694435c4

Observation 51d94de3-a079-41be-965e-73ec387a1a71 · inbound

Position: Use Sparse Autoencoders to Discover Unknowns cites this paper.

Position: Use Sparse Autoencoders to Discover Unknowns Are Sparse Autoencoders Useful? A Case Study in Sparse Probing

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T21:34:33.225648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:34:33.225648Z digest=sha256:15628a4cf61ab0e3c5e07c497062138cd6e3164a3485b8f4d41eb06d6c1faca1

Observation cba08f89-bf75-4dc6-95b1-2c0f770e5b7b · inbound

TRACE: Training and Inference-Time Interpretability Analysis for Language Models cites this paper.

TRACE: Training and Inference-Time Interpretability Analysis for Language Models Are Sparse Autoencoders Useful? A Case Study in Sparse Probing

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T20:07:55.775544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:07:55.775544Z digest=sha256:50dd7e949aa4ff6848ae9134dea7ae4428bfef41e946eb5d7d217b00f884dbf1

Observation 0afec4d0-01ee-444b-bdd3-993b6fcbf964 · inbound

BlueGlass: A Framework for Composite AI Safety cites this paper.

BlueGlass: A Framework for Composite AI Safety Are Sparse Autoencoders Useful? A Case Study in Sparse Probing

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T17:46:18.929519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:46:18.929519Z digest=sha256:2d213f7f3bdc98fb96524734132c2654a65638570b35535a05fa180d3513c872

Observation 85e4a851-3abf-439e-8848-9eda8427f7e1 · inbound

Sparse but Wrong: Incorrect L0 Leads to Incorrect Features in Sparse Autoencoders cites this paper.

Sparse but Wrong: Incorrect L0 Leads to Incorrect Features in Sparse Autoencoders Are Sparse Autoencoders Useful? A Case Study in Sparse Probing

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-05T17:18:55.289843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:18:55.289843Z digest=sha256:a582c32a83dd469b61ced6239c5399bfa772c176c8abf1ccf72f762217558f09

Observation 1793219f-8e9a-45c2-92fe-72f3cf5535db · inbound

When Benchmarks Lie: Evaluating Malicious Prompt Classifiers Under True Distribution Shift cites this paper.

When Benchmarks Lie: Evaluating Malicious Prompt Classifiers Under True Distribution Shift Are Sparse Autoencoders Useful? A Case Study in Sparse Probing

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-02T23:22:38.310667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T23:22:38.310667Z digest=sha256:dc90ebebc249a2966bb6fbced0f7774ee6f02c8694a3354aed4e210326f97670

Observation 81639659-36af-4a6f-86d8-d32d98d9d57e · inbound

SynthSAEBench: Evaluating Sparse Autoencoders on Scalable Realistic Synthetic Data cites this paper.

SynthSAEBench: Evaluating Sparse Autoencoders on Scalable Realistic Synthetic Data Are Sparse Autoencoders Useful? A Case Study in Sparse Probing

Reference 8856

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unresolved
no resolver link, observed 2026-08-02T23:11:40.793678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T23:11:40.793678Z digest=sha256:570ca2a9588f14d2050e208e124cc011f92c51f323a8a278075c15b945cd52cb

Observation 3716bb98-38c8-4b06-829f-60bbae3c630d · inbound

Stable and Steerable Sparse Autoencoders with Weight Regularization cites this paper.

Stable and Steerable Sparse Autoencoders with Weight Regularization Are Sparse Autoencoders Useful? A Case Study in Sparse Probing

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-02T18:56:19.392090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T18:56:19.392090Z digest=sha256:8c72ebab672695bf496f01492f0099d3c44849af43ef32206deb34eb3a8db298

Observation fce7c09f-e98b-4597-8bbe-d3cd6fc84864 · inbound

Improving Robustness In Sparse Autoencoders via Masked Regularization cites this paper.

Improving Robustness In Sparse Autoencoders via Masked Regularization Are Sparse Autoencoders Useful? A Case Study in Sparse Probing

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-10T23:55:51.673015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T18:47:15.830063Z digest=sha256:7235979f5916804baf681245736e12142c30198abf908eea8dfb6d4d9b44420a

Observation 335b13b9-1b4b-447e-a59d-cd3923e027fe · inbound

Linear Probe Accuracy Scales with Model Size and Benefits from Multi-Layer Ensembling cites this paper.

Linear Probe Accuracy Scales with Model Size and Benefits from Multi-Layer Ensembling Are Sparse Autoencoders Useful? A Case Study in Sparse Probing

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-10T14:10:29.180214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T13:50:14.400797Z digest=sha256:873bf011a677fdc1e0c928c2505b1bae719d0faf5e2d1552cdf13ab72172675b

Observation 683f61aa-b164-45c6-916a-6b3d51d7990e · inbound

Compared to What? Baselines and Metrics for Counterfactual Prompting cites this paper.

Compared to What? Baselines and Metrics for Counterfactual Prompting Are Sparse Autoencoders Useful? A Case Study in Sparse Probing

Reference 62

Resolution
verified exact
arxiv_id, observed 2026-05-09T19:05:10.436243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-09T19:02:46.991897Z digest=sha256:bbd677783d9bf0e1cc3b4bba5592393cc7dd59dd95d440421deef0108c370bb3

Observation 5c34db1f-fee8-448f-b5cc-4523cf656f2d · inbound

Self-ReSET: Learning to Self-Recover from Unsafe Reasoning Trajectories cites this paper.

Self-ReSET: Learning to Self-Recover from Unsafe Reasoning Trajectories Are Sparse Autoencoders Useful? A Case Study in Sparse Probing

Reference 47

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verified exact
arxiv_id, observed 2026-05-12T02:11:16.215288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-12T02:07:04.364417Z digest=sha256:07877275cdca2da2a3aad67efc4afc538011acd0a4ebd44da624f7a974f42e9b

Observation 5ea652ba-f03c-46a7-b7a2-5b2c7f4a318e · inbound

Descriptive Collision in Sparse Autoencoder Auto-Interpretability: When One Explanation Describes Many Features cites this paper.

Descriptive Collision in Sparse Autoencoder Auto-Interpretability: When One Explanation Describes Many Features Are Sparse Autoencoders Useful? A Case Study in Sparse Probing

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-14T20:27:58.959480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-14T20:27:38.363693Z digest=sha256:b7fc8b47ad08e24be54e802a32cbc0c9bcf75dfe1ab012a7dc72714aef29544c

Observation bffda916-ac55-4f8e-9127-b350ee8dee64 · inbound

Are Sparse Autoencoder Benchmarks Reliable? cites this paper.

Are Sparse Autoencoder Benchmarks Reliable? Are Sparse Autoencoders Useful? A Case Study in Sparse Probing

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-20T12:43:16.825118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-20T12:43:13.014365Z digest=sha256:a5ae6541dfdb82424c90f8a3b1d8316770a4e4353582df2b0f26d8a2be5e05b0

Observation d3b088b6-eb29-49e9-8ded-5be59d8a0083 · inbound

ICA Lens: Interpreting Language Models Without Training Another Dictionary cites this paper.

ICA Lens: Interpreting Language Models Without Training Another Dictionary Are Sparse Autoencoders Useful? A Case Study in Sparse Probing

Reference 11

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metadata mismatch
arxiv_id, observed 2026-07-03T09:37:49.257469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-27T10:21:58.878499Z digest=sha256:ab9d8c77602ebe5a1d687169e5008f2c2302fab9e3b075260eab4c3d6daf0d96

Observation 8797ce8b-d67c-4c51-baa5-3e720a96cf38 · inbound

Laguerre Geometry for Interpreting Large Language Models cites this paper.

Laguerre Geometry for Interpreting Large Language Models Are Sparse Autoencoders Useful? A Case Study in Sparse Probing

Reference 20

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unresolved
no resolver link, observed 2026-07-14T10:42:30.055074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T10:42:30.055074Z digest=sha256:7053d023df9e072c8e62dde9b7659871768d3612fa9db3e6553afe43015f553c

Observation bf1a2aca-f782-4e1f-a628-478e44c56125 · inbound

Screening of Biosecurity Features in Metagenomic Data with Evo 2 Probes cites this paper.

Screening of Biosecurity Features in Metagenomic Data with Evo 2 Probes Are Sparse Autoencoders Useful? A Case Study in Sparse Probing

Reference 14

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unresolved
no resolver link, observed 2026-08-02T02:53:55.318735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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