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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 2026-08-11T06:34:44.6726+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 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-16T19:38:37.751487Z digest=sha256:93b5e2b654c4ab50ca81db1b45a7dd9fa6484e5a1f68191382c9e9b88f8ac0c0

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 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-17T11:56:11.053897Z digest=sha256:f5f80114008a581cb6a9ac5bbd83e43a7831d7840b0e25ee82074ded57b2f637

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=sha256:667e3e39580df7390e9ea522ba1f815bb1438465ddd7d6400a8e1440ac832f37

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 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-10T02:31:07.932802Z digest=sha256:0edd1ae348c740531dba40d4b6226aaeddd3002f3d4dd47fc45ad0ee6a0541bb

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-07T08:34:14.310656Z digest=sha256:5e6d411dca0067c5227a6ee67d2369bbe9745c7347170cd7ec91696b197e7f30

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 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-08T11:42:16.090162Z digest=sha256:590ff02fbecf5413a90544402bccd703eb9a5d837c9465ba666e73974d52ac13

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 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-12T02:42:26.173782Z digest=sha256:18f731f2c3610f0ed717d95a6bf37498c856cf8db7670af0311dae6f13f2d4db

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 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-14T20:17:01.224864Z digest=sha256:0d83dbe4b9ea35f2957a7bf25272e8e3388b33ff950f15abeca33e04aac11413

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