Paper Citation Record · LEDGER

Learning Elementary Cellular Automata with Transformers

As of 19 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 1 inbound Pith citation observation for arXiv:2412.01417.

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

pith.paper-citation-record.v1
2412.01417 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T04:27:33.694814Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:50:40.866406Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T21:50:41.162852Z

Reference resolution

36 of 36 outbound references displayed

verified exact0
verified fuzzy19
unresolved17
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1b952f01-70ce-485f-844f-7ae6c0053235 · outbound

This paper cites Learning to reason with llms.

Learning Elementary Cellular Automata with Transformers Learning to reason with llms

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T04:27:33.527788Z

Source-reported events for the cited work

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Observation e7c74e89-b831-434b-a610-efb054451b35 · outbound

This paper cites Faith and fate: Limits of transformers on compositionality.

Learning Elementary Cellular Automata with Transformers Faith and fate: Limits of transformers on compositionality

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T04:27:33.533212Z

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Observation 3f93f98d-05f0-43ee-9e88-30e24ee0a716 · outbound

This paper cites LogicAsker: Evaluating and Improving the Logical Reasoning Ability of Large Language Models.

Learning Elementary Cellular Automata with Transformers LogicAsker: Evaluating and Improving the Logical Reasoning Ability of Large Language Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T04:27:33.538092Z

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Observation b96b3f47-6c40-4000-b62d-fba51ec6580b · outbound

This paper cites Conditional and Modal Reasoning in Large Language Models.

Learning Elementary Cellular Automata with Transformers Conditional and Modal Reasoning in Large Language Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T04:27:33.543555Z

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Observation fd67d47e-bdc7-4f3f-84fd-d59615ca9845 · outbound

This paper cites Inductive Learning of Logical Theories with LLMs: An Expressivity-Graded Analysis.

Learning Elementary Cellular Automata with Transformers Inductive Learning of Logical Theories with LLMs: An Expressivity-Graded Analysis

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T04:27:33.548838Z

Source-reported events for the cited work

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Observation 503d58db-f912-4555-8245-8818d895c830 · outbound

This paper cites Liar, Liar, Logical Mire: A Benchmark for Suppositional Reasoning in Large Language Models.

Learning Elementary Cellular Automata with Transformers Liar, Liar, Logical Mire: A Benchmark for Suppositional Reasoning in Large Language Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T04:27:33.554033Z

Source-reported events for the cited work

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Observation d279f28a-95cc-4e03-8fe1-11ac98c8230e · outbound

This paper cites Llms still can’t plan; can lrms? a preliminary evaluation of openai’s o1 on planbench, 2024.

Learning Elementary Cellular Automata with Transformers Llms still can’t plan; can lrms? a preliminary evaluation of openai’s o1 on planbench, 2024

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:27:34.426011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d59e03af-e484-4af4-aac1-36a7d6e079a4 · outbound

This paper cites Attention is All you Need.

Learning Elementary Cellular Automata with Transformers Attention is All you Need

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:27:34.409606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8b281bd1-3071-44e9-b299-67e2035c949b · outbound

This paper cites Approximations by superpositions of a sigmoidal function.

Learning Elementary Cellular Automata with Transformers Approximations by superpositions of a sigmoidal function

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:27:34.394330Z

Source-reported events for the cited work

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Observation d32bc398-426d-4bea-b357-bd65e661ee49 · outbound

This paper cites Multilayer feedforward networks are universal approximators.

Learning Elementary Cellular Automata with Transformers Multilayer feedforward networks are universal approximators

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb614542-6b76-4fc1-a6f8-a55fb35bd9f5 · outbound

This paper cites Are Transformers universal approximators of sequence-to-sequence functions?.

Learning Elementary Cellular Automata with Transformers Are Transformers universal approximators of sequence-to-sequence functions?

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T04:27:33.578985Z

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Unavailable: canonical work link unavailable.

Observation 58f4bba4-6865-4dba-be74-ae36a8ea0cb7 · outbound

This paper cites Representational strengths and limitations of transformers.

Learning Elementary Cellular Automata with Transformers Representational strengths and limitations of transformers

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:27:34.367354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation eb5794ee-ce39-4e09-af3a-571f3b6ef403 · outbound

This paper cites Uni- versal transformers.

Learning Elementary Cellular Automata with Transformers Uni- versal transformers

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:27:34.352840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9be132c5-0d99-4745-b608-25468cad540b · outbound

This paper cites On the Computational Power of Transformers and its Implications in Sequence Modeling.

Learning Elementary Cellular Automata with Transformers On the Computational Power of Transformers and its Implications in Sequence Modeling

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T04:27:33.593229Z

Source-reported events for the cited work

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Observation c4b59e39-3568-4c7a-8638-08d7324d584f · outbound

This paper cites Attention is turing-complete.

Learning Elementary Cellular Automata with Transformers Attention is turing-complete

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:27:34.336415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3b5fceb4-cc64-4918-9a6b-9ac1f439a8df · outbound

This paper cites What Formal Languages Can Transformers Express? A Survey.

Learning Elementary Cellular Automata with Transformers What Formal Languages Can Transformers Express? A Survey

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T04:27:33.602672Z

Source-reported events for the cited work

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Observation 82a08b74-7c91-45d6-a822-5596ea922997 · outbound

This paper cites Deep Learning for Symbolic Mathematics.

Learning Elementary Cellular Automata with Transformers Deep Learning for Symbolic Mathematics

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T04:27:33.607454Z

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Observation 80bca968-db99-4e38-8899-4e8f54497e01 · outbound

This paper cites End-to-end symbolic regression with transformers.

Learning Elementary Cellular Automata with Transformers End-to-end symbolic regression with transformers

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:27:34.298848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 425a7b6f-5d05-43e0-b566-b570ddba0f1f · outbound

This paper cites Deep Symbolic Regression for Recurrent Sequences.

Learning Elementary Cellular Automata with Transformers Deep Symbolic Regression for Recurrent Sequences

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T04:27:33.615939Z

Source-reported events for the cited work

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Observation 5a4eb420-6838-4845-8fb1-c535daba2b86 · outbound

This paper cites an unresolved cited work.

Learning Elementary Cellular Automata with Transformers Unresolved cited work

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T04:27:33.620588Z

Source-reported events for the cited work

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Observation e0b28e52-8256-40e8-b80c-499c72dfda35 · outbound

This paper cites Learning cellular automaton dynamics with neural networks.

Learning Elementary Cellular Automata with Transformers Learning cellular automaton dynamics with neural networks

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:27:34.266803Z

Source-reported events for the cited work

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Observation 68507808-6180-4647-8b6c-04885b38a388 · outbound

This paper cites Cellular automata as convolutional neural networks.

Learning Elementary Cellular Automata with Transformers Cellular automata as convolutional neural networks

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:27:34.251254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 99a49fd3-d140-4479-983b-58ad426a1997 · outbound

This paper cites Generalization over different cellular automata rules learned by a deep feed-forward neural network, 2021.

Learning Elementary Cellular Automata with Transformers Generalization over different cellular automata rules learned by a deep feed-forward neural network, 2021

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:27:34.234475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3aa46dd3-679e-43e5-9fc2-06cf0d42c730 · outbound

This paper cites Growing neural cellular automata.

Learning Elementary Cellular Automata with Transformers Growing neural cellular automata

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:27:34.104190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3a117c51-bcc8-41f9-bf0d-26cddf304c1a · outbound

This paper cites Hierarchical neural cellular automata.

Learning Elementary Cellular Automata with Transformers Hierarchical neural cellular automata

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:27:34.082576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4e335b31-9112-41bf-8a42-642932c34725 · outbound

This paper cites Cellular automata, many-valued logic, and deep neural networks.

Learning Elementary Cellular Automata with Transformers Cellular automata, many-valued logic, and deep neural networks

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-12T04:27:33.646326Z

Source-reported events for the cited work

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Observation 16bb56b6-4340-45c4-8c58-03c7d501bd87 · outbound

This paper cites E(n)-equivariant Graph Neural Cellular Automata.

Learning Elementary Cellular Automata with Transformers E(n)-equivariant Graph Neural Cellular Automata

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-12T04:27:33.651191Z

Source-reported events for the cited work

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Observation 415311c7-e3a2-4b86-a734-7fd91e3c9ec9 · outbound

This paper cites Attention-based neural cellular au- tomata.

Learning Elementary Cellular Automata with Transformers Attention-based neural cellular au- tomata

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:27:34.064186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 57145220-aeaa-4244-81c5-8f6b34dc3965 · outbound

This paper cites Learning graph cellular automata.

Learning Elementary Cellular Automata with Transformers Learning graph cellular automata

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:27:34.046762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1034acef-605e-4321-9473-dcea7b259bb8 · outbound

This paper cites Learning spatio- temporal patterns with neural cellular automata.

Learning Elementary Cellular Automata with Transformers Learning spatio- temporal patterns with neural cellular automata

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:27:34.026711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6469ac0b-d071-49ad-bdfa-423ab4d8da56 · outbound

This paper cites Learning locally interacting discrete dynamical systems: Towards data-efficient and scalable prediction.

Learning Elementary Cellular Automata with Transformers Learning locally interacting discrete dynamical systems: Towards data-efficient and scalable prediction

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:27:33.999011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5bf69565-4864-4782-9ebc-4fd714cce07c · outbound

This paper cites It’s hard for neural networks to learn the game of life.

Learning Elementary Cellular Automata with Transformers It’s hard for neural networks to learn the game of life

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:27:33.981732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 168d163f-715a-4f06-a6ea-ef04eef68ddf · outbound

This paper cites Data-Centric Approach to Constrained Machine Learning: A Case Study on Conway's Game of Life.

Learning Elementary Cellular Automata with Transformers Data-Centric Approach to Constrained Machine Learning: A Case Study on Conway's Game of Life

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-12T04:27:33.680360Z

Source-reported events for the cited work

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Observation 07153d5b-8b79-439d-b9b1-15102e2977e2 · outbound

This paper cites Reconstructing cellular automata rules from observations at nonconsecutive times.

Learning Elementary Cellular Automata with Transformers Reconstructing cellular automata rules from observations at nonconsecutive times

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:27:33.965861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 07d0d9fd-9205-4375-a605-fb56e1ba4866 · outbound

This paper cites LifeGPT: Topology-Agnostic Generative Pretrained Transformer Model for Cellular Automata.

Learning Elementary Cellular Automata with Transformers LifeGPT: Topology-Agnostic Generative Pretrained Transformer Model for Cellular Automata

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-12T04:27:33.689916Z

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Observation 97198ba9-ace4-41fc-b58c-238a5972ada1 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

Learning Elementary Cellular Automata with Transformers Chain-of-thought prompting elicits reasoning in large language models

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:27:33.950026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation bbcd724a-c5e4-4b84-b386-beec263fe372 · inbound

ARC-NCA: Towards Developmental Solutions to the Abstraction and Reasoning Corpus cites this paper.

ARC-NCA: Towards Developmental Solutions to the Abstraction and Reasoning Corpus Learning Elementary Cellular Automata with Transformers

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-15T21:50:41.169736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.