Paper Citation Record · LEDGER

Emergent Linear Representations in World Models of Self-Supervised Sequence Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 33 inbound Pith citation observations for arXiv:2309.00941.

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

pith.paper-citation-record.v1
2309.00941 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 33 of 33 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 33 of 33 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T22:12:50.147169Z

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

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External citation measurements

3
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 3f00660a-c05a-4d35-880b-9576977177c2 · 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 Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 105

Resolution: verified exact; arxiv_id, observed 2026-05-17T11:56:11.112344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation aa5dbfb8-87c1-4f2e-92d5-5171947b60d0 · inbound

Refusal in Language Models Is Mediated by a Single Direction cites this paper.

Refusal in Language Models Is Mediated by a Single Direction Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 164

Resolution: verified exact; arxiv_id, observed 2026-05-13T10:47:56.057846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7b55d802-9926-4402-8e5f-7d467a5a5e89 · inbound

When Do Neural Networks Learn World Models? cites this paper.

When Do Neural Networks Learn World Models? Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 63

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Observation d40b9a34-3608-482d-b5ea-b4fee4a0d62e · inbound

The Origins of Representation Manifolds in Large Language Models cites this paper.

The Origins of Representation Manifolds in Large Language Models Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 34

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Observation cc192d4b-c79b-4d19-b930-07014592f85c · inbound

Understanding the learned look-ahead behavior of chess neural networks cites this paper.

Understanding the learned look-ahead behavior of chess neural networks Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T14:17:47.799785Z

Source-reported events for the cited work

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Observation 2e442602-811d-4164-be37-aae9d9a4c077 · inbound

Linear Spatial World Models Emerge in Large Language Models cites this paper.

Linear Spatial World Models Emerge in Large Language Models Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 36

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Observation 740cb4f6-0837-459f-8fa0-a3c2cf3d6896 · inbound

A Statistical Physics of Language Model Reasoning cites this paper.

A Statistical Physics of Language Model Reasoning Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 26

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Source-reported events for the cited work

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Observation a388cbc4-65e3-4248-a348-4ebebf3db623 · inbound

Behavioural vs. Representational Systematicity in End-to-End Models: An Opinionated Survey cites this paper.

Behavioural vs. Representational Systematicity in End-to-End Models: An Opinionated Survey Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 65

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Source-reported events for the cited work

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Observation 5c47d229-72dc-4e54-b230-71e1415343d1 · inbound

Large Language Models and Emergence: A Complex Systems Perspective cites this paper.

Large Language Models and Emergence: A Complex Systems Perspective Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 46

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Source-reported events for the cited work

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Observation d8e17bff-78d6-4c8d-abc4-234872b33d56 · inbound

Model Organisms for Emergent Misalignment cites this paper.

Model Organisms for Emergent Misalignment Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 21

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Observation fee3b4a4-6da7-44de-8224-344f435dc658 · inbound

Convergent Linear Representations of Emergent Misalignment cites this paper.

Convergent Linear Representations of Emergent Misalignment Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 19

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Observation a4c48831-74c0-4ab2-9716-4f8cd3ae78a1 · inbound

Distinct Computations Emerge From Compositional Curricula in In-Context Learning cites this paper.

Distinct Computations Emerge From Compositional Curricula in In-Context Learning Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T00:41:54.894904Z

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Observation 509a0729-c1e0-46ab-a923-9a4e81bc055d · inbound

The Geometry of Harmfulness in LLMs through Subconcept Probing cites this paper.

The Geometry of Harmfulness in LLMs through Subconcept Probing Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 18

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Source-reported events for the cited work

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Observation 575fcf43-1924-448c-a64e-02a093430aec · inbound

A Single Direction of Truth: An Observer Model's Linear Residual Probe Exposes and Steers Contextual Hallucinations cites this paper.

A Single Direction of Truth: An Observer Model's Linear Residual Probe Exposes and Steers Contextual Hallucinations Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 24

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Observation fa8db5d3-17e2-430c-a5c2-6ca8a5913e43 · inbound

Towards Atoms of Large Language Models cites this paper.

Towards Atoms of Large Language Models Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 23

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Source-reported events for the cited work

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Observation 55666767-d57f-4334-8c97-2d11836bae3a · inbound

Higher Embedding Dimension Creates a Stronger World Model for a Simple Sorting Task cites this paper.

Higher Embedding Dimension Creates a Stronger World Model for a Simple Sorting Task Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T08:56:14.257028Z

Source-reported events for the cited work

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Observation c8e86fc7-8a12-47aa-aae1-5a78966ba4d8 · inbound

Predicting Where Steering Vectors Succeed cites this paper.

Predicting Where Steering Vectors Succeed Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:00:03.826975Z

Source-reported events for the cited work

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Observation 05340939-5c79-4805-a1c8-b24010b6a93e · 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 Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:31:10.553775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fcced561-ab36-4422-ab5f-2a862aeebb69 · inbound

Tool Calling is Linearly Readable and Steerable in Language Models cites this paper.

Tool Calling is Linearly Readable and Steerable in Language Models Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 62

Resolution: verified exact; arxiv_id, observed 2026-05-11T03:10:52.673298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 60a25d7d-07af-4ecc-86d3-6ce70228e3c1 · inbound

Tensor Product Representation Probes Reveal Shared Structure Across Linear Directions cites this paper.

Tensor Product Representation Probes Reveal Shared Structure Across Linear Directions Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 18

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Source-reported events for the cited work

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Observation 46399647-6412-41c2-9375-464b7a27c16a · inbound

Stories in Space: In-Context Learning Trajectories in Conceptual Belief Space cites this paper.

Stories in Space: In-Context Learning Trajectories in Conceptual Belief Space Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:22:18.847386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 93d65bcf-d254-4999-8e07-1370d471365f · inbound

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

Correcting Influence: Unboxing LLM Outputs with Orthogonal Latent Spaces Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 246

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T20:17:55.562942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 887951cc-fc69-40d6-bad8-eb2f4fc74d7b · inbound

Multi-Turn Neural Transparency: Surfacing Neural Activations Improves User Calibration to LLM Behavioral Drift cites this paper.

Multi-Turn Neural Transparency: Surfacing Neural Activations Improves User Calibration to LLM Behavioral Drift Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-19T14:42:37.684579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7525c5af-6a0e-4bc3-9d34-bea755b8333f · inbound

GeoMathCode: Understanding Interleaved Math-Code Reasoning for Geometry Problem Solving cites this paper.

GeoMathCode: Understanding Interleaved Math-Code Reasoning for Geometry Problem Solving Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-06-29T22:54:01.534874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4ccf0d14-90fa-4316-b1d9-7486f15f7dc6 · inbound

A Close Look At World Model Recovery In Supervised Fine-Tuned LLM Planners cites this paper.

A Close Look At World Model Recovery In Supervised Fine-Tuned LLM Planners Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-07-02T01:46:26.459346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 24c95a46-b8c4-488e-b2ab-619d73d9267f · inbound

The New Associationism: Lessons from Deep Learning cites this paper.

The New Associationism: Lessons from Deep Learning Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 89

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3eeb4439-99ef-4f66-86f2-60f638a08696 · inbound

Investigating The Security of Modern AI and Cloud Infrastructure cites this paper.

Investigating The Security of Modern AI and Cloud Infrastructure Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 102

Resolution: verified exact; arxiv_id, observed 2026-07-04T08:29:42.330969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fd4f8eb0-375e-4397-aab1-6c786969f6ab · inbound

How are linear representations learned? Exact solutions to the dynamics of abstraction cites this paper.

How are linear representations learned? Exact solutions to the dynamics of abstraction Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 2

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Source-reported events for the cited work

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Observation 5eea63f0-ffb2-4e6d-9c24-8bcfaddf1b5e · inbound

Exposure is not manifestation: measurement target and output resolution jointly determine which behavioural-faithfulness evaluator wins cites this paper.

Exposure is not manifestation: measurement target and output resolution jointly determine which behavioural-faithfulness evaluator wins Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 43

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Observation a6f867a3-47ed-48fb-b57b-18bc59e0d013 · inbound

Inside the Unfair Judge: A Mechanistic Interpretability Account of LLM-as-Judge Bias cites this paper.

Inside the Unfair Judge: A Mechanistic Interpretability Account of LLM-as-Judge Bias Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 55

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Observation df5dc5b4-399b-4d3d-9142-6db19f2e0a8b · inbound

When Does Reward Teach State? A Hidden-Automaton Instrument and the Group-Language Boundary cites this paper.

When Does Reward Teach State? A Hidden-Automaton Instrument and the Group-Language Boundary Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 11

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Observation f3671bb1-a417-463a-ad44-4b3f8319f5e1 · inbound

Geometry-Guided Constraint Learning for LLM Safety Classification cites this paper.

Geometry-Guided Constraint Learning for LLM Safety Classification Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 14

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Observation a66ec76f-6e1e-4d73-b0b1-5f9605e8ca97 · inbound

Context Is King: How In-Context Specification Shapes the Geometry of Concepts cites this paper.

Context Is King: How In-Context Specification Shapes the Geometry of Concepts Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 14

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Unavailable: canonical work link unavailable.