Paper Citation Record · LEDGER

Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 27 inbound Pith citation observations for arXiv:2210.13382.

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

pith.paper-citation-record.v1
2210.13382 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 27 of 27 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 27 of 27 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:25:27.253885Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T17:50:00.028255Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a1568c85-77e4-474e-9bd5-cdaedc671faf · inbound

Eliciting Latent Predictions from Transformers with the Tuned Lens cites this paper.

Eliciting Latent Predictions from Transformers with the Tuned Lens Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 55

Resolution: verified exact; arxiv_id, observed 2026-05-12T16:54:37.577329Z

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 1ed8737b-4b4e-4a77-88f8-27b58863fe40 · inbound

The Limits of Predicting Agents from Behaviour cites this paper.

The Limits of Predicting Agents from Behaviour Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T11:25:27.253885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 518385f5-3e20-4dca-90d7-550c1e0b9c62 · inbound

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

Linear Spatial World Models Emerge in Large Language Models Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T11:17:25.775461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa5136ea-e474-4262-9704-c6ce7250c71b · 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 World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T10:46:20.099522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 591e9dd7-ea97-4d11-bdf5-183f5444bd15 · inbound

What Does it Mean for a Neural Network to Learn a "World Model"? cites this paper.

What Does it Mean for a Neural Network to Learn a "World Model"? Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T12:44:45.677714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01083eb2-8c1a-4811-8a71-b9d33b3ec5e0 · inbound

Transformers converge to invariant algorithmic cores cites this paper.

Transformers converge to invariant algorithmic cores Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-02T20:46:33.272201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09d1195a-4523-4dfc-aa6c-6d4378b25182 · inbound

Cell-Based Representation of Relational Binding in Language Models cites this paper.

Cell-Based Representation of Relational Binding in Language Models Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-11T13:06:04.700561Z

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 5a27e9ff-5550-4f43-a99b-ed2c2584ffba · inbound

A paradox of AI fluency cites this paper.

A paradox of AI fluency Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 21

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T23:46:52.637251Z

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 b979e584-ffc1-433c-9c49-37a3e7c9dbac · inbound

Causal Probing for Internal Visual Representations in Multimodal Large Language Models cites this paper.

Causal Probing for Internal Visual Representations in Multimodal Large Language Models Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T19:26:09.064639Z

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 8bab98c9-86a9-4146-9b61-7e1ae77f8050 · inbound

Do multimodal models imagine electric sheep? cites this paper.

Do multimodal models imagine electric sheep? Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 15

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T03:26:19.581626Z

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 f5df6857-390b-484e-9938-0ba246124b5f · 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 World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:16:30.180962Z

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 605e4a9f-71bf-48f4-8039-4377959b3011 · inbound

In-context learning enables continental-scale subsurface temperature prediction from sparse local observations cites this paper.

In-context learning enables continental-scale subsurface temperature prediction from sparse local observations Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 29

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T19:28:54.971182Z

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 2270d402-49ef-46f0-bb6d-b27690abb0ae · inbound

Scale-Dependent Collective Adaptation in Self-Amending LLM Societies: A Cross-Family Study of Emergent Governance cites this paper.

Scale-Dependent Collective Adaptation in Self-Amending LLM Societies: A Cross-Family Study of Emergent Governance Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 75

Resolution: verified exact; arxiv_id, observed 2026-05-19T22:32:49.749168Z

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 51977abd-64f1-4082-82da-2a8245d9da39 · inbound

Mechanisms of Misgeneralization in Physical Sequence Modeling cites this paper.

Mechanisms of Misgeneralization in Physical Sequence Modeling Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-05-21T07:44:48.740916Z

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 297480b0-b494-4dd7-807e-f3f0d9253e58 · inbound

Why We Need World Models for AGI: Where LLMs Fail and How World Models May Outperform cites this paper.

Why We Need World Models for AGI: Where LLMs Fail and How World Models May Outperform Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 35

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T14:25:46.620559Z

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 64198019-20ed-4935-8790-699524bf31ec · 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 World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-06-29T22:54:01.522638Z

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 e72c8513-fd5a-4fb1-a8a2-61b64aa40bd3 · inbound

Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet cites this paper.

Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 45

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T07:53:13.490170Z

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 acd87c02-b614-438e-9b5c-0629e04eb78e · 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 World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 13

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T01:46:26.382521Z

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 900f93e2-11e4-4c91-a68c-cb59e6ff81ef · inbound

Arithmetic Pedagogy for Language Models cites this paper.

Arithmetic Pedagogy for Language Models Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-07-02T07:46:46.578114Z

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 c6cbb07d-674d-4401-b13a-2f9c303faafe · inbound

A retrieval conditioned rebinding circuit for dynamic entity tracking in large language models cites this paper.

A retrieval conditioned rebinding circuit for dynamic entity tracking in large language models Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:27:26.327050Z

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 4f8922b5-8ab8-4aee-899f-6135c64c2eda · inbound

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

The New Associationism: Lessons from Deep Learning Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 90

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T18:35:00.213885Z

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 b7b63f46-56e1-4667-b384-bcd4407b909b · inbound

LaGO: Latent Action Guidance for Online Reinforcement Learning cites this paper.

LaGO: Latent Action Guidance for Online Reinforcement Learning Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 15

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T17:50:00.030034Z

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 d8798367-990c-44a3-ab10-804525acdcbc · inbound

Radical AI Interpretability cites this paper.

Radical AI Interpretability Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-07-04T13:09:51.112443Z

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 fa634671-a636-4fdb-9cd2-c61e061da5f7 · inbound

Input Pathways Shape Few-Shot, Not Zero-Shot, Binding in Tiny Transformers: A Fully-Enumerable Study cites this paper.

Input Pathways Shape Few-Shot, Not Zero-Shot, Binding in Tiny Transformers: A Fully-Enumerable Study Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-11T11:22:48.469230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab15d13c-c081-44ce-aa44-bde93a5c7f76 · 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 World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T07:20:39.972178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70711ee3-d8b9-46c4-ad76-a423b7fb57f6 · inbound

Reality Monitoring in Large Language Models: Self-Knowledge That Transforms with Conversation Memory cites this paper.

Reality Monitoring in Large Language Models: Self-Knowledge That Transforms with Conversation Memory Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-31T23:35:43.023390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c1296d9-1216-4d05-84ae-7424d195e9ae · inbound

Learning Implicit Causal World Models from Multi-Agent Demonstrations cites this paper.

Learning Implicit Causal World Models from Multi-Agent Demonstrations Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-01T00:17:30.828734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.