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Paper Citation Record · LEDGER

Position: Use Sparse Autoencoders to Discover Unknowns

As of 8 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 8 inbound Pith citation observations for arXiv:2506.23845.

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

pith.paper-citation-record.v1
2506.23845 v2

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:34:33.631283Z

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 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T00:23:28.838115Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T15:37:07.048796Z

Reference resolution

12 of 12 outbound references displayed

  • verified exact0
  • verified fuzzy1
  • unresolved10
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation aff77032-7b38-4df5-8127-889103f6c7a1 · outbound

This paper cites Applying sparse autoencoders to unlearn knowledge in language models.

Position: Use Sparse Autoencoders to Discover Unknowns Applying sparse autoencoders to unlearn knowledge in language models

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T21:34:33.012045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:34:33.012045Z digest=sha256:555668fc98bf18c797c02b2798f6bb2ba15cbae025920d2a87612eb5cafe210d

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

This paper cites Are Sparse Autoencoders Useful? A Case Study in Sparse Probing.

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:b3af813c2b9c41aa5f55ba3e48de89496c068b9e920300d916f79b46a12e3d14

Observation fc6c1c5a-b1ba-4c19-b0bd-eee994a6b93e · outbound

This paper cites doi: 10.18653/v1/2021.nuse-1.5.

Position: Use Sparse Autoencoders to Discover Unknowns doi: 10.18653/v1/2021.nuse-1.5

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T21:34:33.438821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:34:33.438821Z digest=sha256:07c70b2dfd2663066eb334f6dc78f1ef6bd40c7d710a134cf4b0ef8deafc95ff

Observation 686e0ed0-7129-44b5-add7-9373dae8b45e · outbound

This paper cites AxBench: Steering LLMs? Even Simple Baselines Outperform Sparse Autoencoders.

Position: Use Sparse Autoencoders to Discover Unknowns AxBench: Steering LLMs? Even Simple Baselines Outperform Sparse Autoencoders

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T21:34:33.631283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:34:33.631283Z digest=sha256:c508c4b21782bf4eb0bde94493c5c6f8120c796b419620e31e431e3822b58310

Observation 76c31ea0-f8ce-4f69-b121-1acd8230bafc · outbound

This paper cites URL https://doi.org/10.1214/10-STS330.

Position: Use Sparse Autoencoders to Discover Unknowns URL https://doi.org/10.1214/10-STS330

Reference 2010

Resolution
malformed identifier
doi_truncated, observed 2026-08-06T21:34:33.821075Z

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=2026-08-06T21:34:33.574840Z digest=sha256:149e932560b1e43e5ff601b4bc7b230ae883476bb8fd71b3326d1302fb8bfb22

Observation 1dd42544-8ad2-47ff-8e75-92947e5ea738 · outbound

This paper cites Open Problems in Mechanistic Interpretability.

Position: Use Sparse Autoencoders to Discover Unknowns Open Problems in Mechanistic Interpretability

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-06T21:34:33.494081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:34:33.494081Z digest=sha256:abc71013833bc252c32bbd88e86e243b47eb1ff4233123da3232af49e69a99b5

Observation 1eae202c-ff10-4ee5-920c-443a6b3a9485 · outbound

This paper cites Lakkaraju, E.

Position: Use Sparse Autoencoders to Discover Unknowns Lakkaraju, E

Reference 2020

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:34:34.456080Z

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=2026-08-06T21:34:33.271278Z digest=sha256:930f675a62994b8d7fbf38c92c4c1731ee2bdd5ac38c45ace74f78d75555cfd2

Observation 383e8f1d-64a1-4b41-a70e-adb095152a5d · outbound

This paper cites ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission.

Position: Use Sparse Autoencoders to Discover Unknowns ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-06T21:34:33.136653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:34:33.136653Z digest=sha256:564bbb2f058704bbea7e171d10cd4b282501fa943e31b4f74c896be47145f190

Observation 818aeebe-7d25-46eb-8fde-c25e0cb98757 · outbound

This paper cites an unresolved cited work.

Position: Use Sparse Autoencoders to Discover Unknowns Unresolved cited work

Reference 2022

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:34:34.611963Z

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=2026-08-06T21:34:32.765854Z digest=sha256:d2a21eca7304a79ad055f4011b5eadc4e0e5090b1a4f3534654db91ccc8a2333

Observation 54227477-0cab-41df-979a-09225b22d155 · outbound

This paper cites Aggregated Individual Reporting for Post-Deployment Evaluation.

Position: Use Sparse Autoencoders to Discover Unknowns Aggregated Individual Reporting for Post-Deployment Evaluation

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-06T21:34:32.883319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:34:32.883319Z digest=sha256:de5ba21b06cb2fe07b9813404da07cc18da8095b1f7d8735dc9971aef33205f7

Observation f9add145-5007-4f88-9813-b0a3b0603be2 · outbound

This paper cites an unresolved cited work.

Position: Use Sparse Autoencoders to Discover Unknowns Unresolved cited work

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-06T21:34:32.717619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:34:32.717619Z digest=sha256:c69050a0b03d1eaca321fb0511b19e9891d7c8cb9742d244740d009da531315e

Observation e36b6e37-fcbf-493d-a596-48b3638ea18c · outbound

This paper cites an unresolved cited work.

Position: Use Sparse Autoencoders to Discover Unknowns Unresolved cited work

Reference 2025

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:34:34.271837Z

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=2026-08-06T21:34:33.371976Z digest=sha256:6dd91e3bbd6e6fdb1dee4aaee60044837605a03faeb994dd16016122062c38d2

Pith citing papers

Observation 02f7f598-a4cc-41c7-948d-5351e9db50ef · inbound

ActivationReasoning: Logical Reasoning in Latent Activation Spaces cites this paper.

ActivationReasoning: Logical Reasoning in Latent Activation Spaces Position: Use Sparse Autoencoders to Discover Unknowns

Reference 13

Resolution
metadata mismatch
arxiv_id, observed 2026-07-07T02:18:25.475903Z

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=2026-05-18T05:43:45.863209Z digest=sha256:c9d6d8fe8d781f50be2dd8745533407d82bb83c730de08be5b2a93e77bf7168f

Observation 5c89f946-0e9d-4d34-84ff-a06553e1c2de · inbound

Making Interpretable Discoveries from Unstructured Data: A High-Dimensional Multiple Hypothesis Testing Approach cites this paper.

Making Interpretable Discoveries from Unstructured Data: A High-Dimensional Multiple Hypothesis Testing Approach Position: Use Sparse Autoencoders to Discover Unknowns

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-07-07T02:18:25.475903Z

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=2026-05-18T01:56:50.978054Z digest=sha256:5560066db588f2c967d3568a174a9c388d86cafa5edac585e9c8084317bf6391

Observation 4a02ddf9-c07b-4772-9a93-520cadf6fc47 · inbound

Making Interpretable Discoveries from Unstructured Data: A High-Dimensional Multiple Hypothesis Testing Approach cites this paper.

Making Interpretable Discoveries from Unstructured Data: A High-Dimensional Multiple Hypothesis Testing Approach Position: Use Sparse Autoencoders to Discover Unknowns

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-04T00:23:28.838115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T00:23:28.838115Z digest=sha256:14e7bbb01f3ca77f4388dfaee16c307cdd80919e61b975d57e92051541e16c79

Observation a4d18132-aefc-4179-b9b0-3409402436bd · inbound

Practicing with Language Models Cultivates Human Empathic Communication cites this paper.

Practicing with Language Models Cultivates Human Empathic Communication Position: Use Sparse Autoencoders to Discover Unknowns

Reference 69

Resolution
unresolved
no resolver link, observed 2026-07-14T20:33:57.341112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T20:33:57.341112Z digest=sha256:ee7c1f8a35ed7c85ad193b46e45c4cc343e36ea549dc60fa403b66297cb221da

Observation 4f407dba-9297-49bd-b2ad-146cea760c41 · inbound

Not Just RLHF: Why Alignment Alone Won't Fix Multi-Agent Sycophancy cites this paper.

Not Just RLHF: Why Alignment Alone Won't Fix Multi-Agent Sycophancy Position: Use Sparse Autoencoders to Discover Unknowns

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-07-07T02:18:25.475903Z

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=2026-05-14T20:04:57.638215Z digest=sha256:ad239e1a4921ed0b3ab00b2239e3ed8a97980bc580e80151e040cf6d1d011274

Observation bfdeff83-9bd5-4f1a-9fe1-65bc3175b894 · inbound

Not Just RLHF: Why Alignment Alone Won't Fix Multi-Agent Sycophancy cites this paper.

Not Just RLHF: Why Alignment Alone Won't Fix Multi-Agent Sycophancy Position: Use Sparse Autoencoders to Discover Unknowns

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-07-07T02:18:25.475903Z

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=2026-05-20T21:30:30.384184Z digest=sha256:cdc446d5cc399ca6df5e35484fd2801d6c1fa6a96e268211adb7ab8bfddfd3cf

Observation fe81ce77-05de-4b15-bbea-4e270fe6b83d · inbound

Conditional Hypothesis Generation for LLM-Based Text Analysis with Researcher-Specified Covariates cites this paper.

Conditional Hypothesis Generation for LLM-Based Text Analysis with Researcher-Specified Covariates Position: Use Sparse Autoencoders to Discover Unknowns

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-07-07T02:18:25.475903Z

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=2026-06-28T10:46:13.006992Z digest=sha256:e474249498ae38d8f0f3adfd68eae0661480467ea7b1665d75fae19cab4893e9

Observation 783f5120-b894-47e9-bea2-b97809e2a5f9 · inbound

Three Years of r/ChatGPT: Societal Impact Evaluations from Social Media Data cites this paper.

Three Years of r/ChatGPT: Societal Impact Evaluations from Social Media Data Position: Use Sparse Autoencoders to Discover Unknowns

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-07-07T02:18:25.475903Z

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=2026-06-27T23:41:38.200349Z digest=sha256:4ca451f2f4cc119a0b5f6ba27b98cc5d1ed4898ecb54d2bac4af023ec48937b3