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Paper Citation Record · LEDGER

Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2303.02536.

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

pith.paper-citation-record.v1
2303.02536 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 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 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:55:02.030913Z

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

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

9
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 a2fc06f0-e7a3-46f3-afb6-47d45d3628ec · inbound

Localizing Model Behavior with Path Patching cites this paper.

Localizing Model Behavior with Path Patching Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-05-16T19:38:37.793826Z

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=2026-05-16T19:38:37.751487Z digest=sha256:9d046e0e78721af77424e6d115a6fb42fcaf04fa4b0c4a841954ee3973928258

Observation 8488324c-11e8-4be5-9705-375d81cb4875 · inbound

Towards Best Practices of Activation Patching in Language Models: Metrics and Methods cites this paper.

Towards Best Practices of Activation Patching in Language Models: Metrics and Methods Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations

Reference 80

Resolution
verified exact
arxiv_id, observed 2026-05-17T11:56:11.181983Z

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=2026-05-17T11:56:11.053897Z digest=sha256:f5e561bc4769c6dd819a5fd0ac54cd86cd89eb25eda7df87cdaf0ee6380c37e2

Observation 024c1d07-87f5-4b2e-9bc5-4ecb81d25b8b · inbound

Interpretability in Parameter Space: Minimizing Mechanistic Description Length with Attribution-based Parameter Decomposition cites this paper.

Interpretability in Parameter Space: Minimizing Mechanistic Description Length with Attribution-based Parameter Decomposition Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-10T14:55:02.030913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:55:02.030913Z digest=sha256:9b97cc30ca7e8fd9e3d3588251f8e593068ba7f4cf0d13a9417b4f30a8231447

Observation 401c55ea-6fe8-4735-bc5c-fac8ed930e13 · inbound

What is a Number, That a Large Language Model May Know It? cites this paper.

What is a Number, That a Large Language Model May Know It? Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-09T15:05:03.727012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:05:03.727012Z digest=sha256:ca4d2af5bfd955b0cf2e5a4e3008d73f4727b6bedd06145868e9379a2b7d80fa

Observation 68bbd057-2773-4fa5-a82f-ded588030d21 · inbound

Activation Reward Models for Few-Shot Model Alignment cites this paper.

Activation Reward Models for Few-Shot Model Alignment Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-06T21:02:42.463921Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:02:42.463921Z digest=sha256:e231e197af812dac7de51a2c01c3a2a39eb730e9014b881c8d2d0c9855cf89be

Observation 2a1e138e-84c0-4cc9-bea9-3ed10f1220bd · inbound

Local Linearity of LLMs Enables Activation Steering via Model-Based Linear Optimal Control cites this paper.

Local Linearity of LLMs Enables Activation Steering via Model-Based Linear Optimal Control Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-05-10T02:32:49.534799Z

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=2026-05-10T02:31:07.932802Z digest=sha256:940e2a2b218dc3ef87ac97542bca07386bd3d39a127ef6e76e0a2c29b0cb888a

Observation 816d3d25-ddd9-4c28-bbf9-050b72c14ae2 · inbound

Perturbation Probing: A Two-Pass-per-Prompt Diagnostic for FFN Behavioral Circuits in Aligned LLMs cites this paper.

Perturbation Probing: A Two-Pass-per-Prompt Diagnostic for FFN Behavioral Circuits in Aligned LLMs Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-12T10:01:27.593672Z

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=2026-05-07T08:34:14.310656Z digest=sha256:0935a5d2e091f1332a78d52f681d1f1986a069154867cc302575faa2bce2ff19

Observation ca0342c1-706c-46aa-b8d3-f0f377628d56 · inbound

Decodable but Not Corrected by Fixed Residual-Stream Linear Steering: Evidence from Medical LLM Failure Regimes cites this paper.

Decodable but Not Corrected by Fixed Residual-Stream Linear Steering: Evidence from Medical LLM Failure Regimes Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-11T19:31:10.260228Z

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=2026-05-08T11:42:16.090162Z digest=sha256:2b9e72069a548622cc4fd1dc584daeff6798e77b20b54d42732cc845f2cd725d

Observation 3ca91b54-05de-4028-90bd-1be1c889cbd0 · inbound

From Mechanistic to Compositional Interpretability cites this paper.

From Mechanistic to Compositional Interpretability Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations

Reference 148

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T02:46:18.305880Z

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=2026-05-12T02:42:26.173782Z digest=sha256:b27c1e955b93a8110307eca6b7a3534a537e06e7ecab45463583e9c4f11d4ac9

Observation dc656d93-f134-406a-bc8d-c3e8ffb42b30 · inbound

Correcting Influence: Unboxing LLM Outputs with Orthogonal Latent Spaces cites this paper.

Correcting Influence: Unboxing LLM Outputs with Orthogonal Latent Spaces Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations

Reference 75

Resolution
verified exact
arxiv_id, observed 2026-05-14T20:17:54.794369Z

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=2026-05-14T20:17:01.224864Z digest=sha256:ce28cd66a84e848c0d1a51c91bd67e269e39be395326479b55a2344fdc84598a

Observation 66f400a5-dc44-4b54-8dde-ab0f3ec44b19 · inbound

Persistent Sparse Autoencoders: Learning Feature Timescales in Language Models cites this paper.

Persistent Sparse Autoencoders: Learning Feature Timescales in Language Models Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-01T19:02:31.790237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T19:02:31.790237Z digest=sha256:87c68f69711c08312bd0b277bd52600d1ce669e235af22bf37223fd6e8d4295d

Observation 9d75ec05-917e-428b-b71f-ce40c9a25fc6 · inbound

Emergent Misalignment Recruits a Pre-existing Persona Subspace cites this paper.

Emergent Misalignment Recruits a Pre-existing Persona Subspace Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations

Reference 132

Resolution
unresolved
no resolver link, observed 2026-08-01T07:46:16.527795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T07:46:16.527795Z digest=sha256:c390514c32ba8855443cd18e2813430925fc515ca39d1c1f7357690e64e9bd47

Observation 4d4552c1-0b11-4981-8e23-faf7b4de599b · inbound

LAWFUL: Law-Aligned Witness for Faithful Use of Latents cites this paper.

LAWFUL: Law-Aligned Witness for Faithful Use of Latents Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-03T00:47:34.695081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T00:47:34.695081Z digest=sha256:f40ecd939889e1113fccaa41682a09bf7badd8db7f09b7abba5e8b701e83f7b2