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Paper Citation Record · LEDGER

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT

As of 21 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 1 inbound Pith citation observation for arXiv:2501.08053.

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

pith.paper-citation-record.v1
2501.08053 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:34:17.495261Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T21:33:15.206087Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T21:33:15.633092Z

Reference resolution

35 of 35 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 22169cce-1db9-409d-ad16-f0f1f5543ed5 · outbound

This paper cites Deep learning,.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Deep learning,

Reference 1

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Observation b081a0ea-cd6c-4459-99db-902f1bdb942e · outbound

This paper cites Deep Learning: A Critical Appraisal.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Deep Learning: A Critical Appraisal

Reference 2

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Observation b70176ac-3cee-4aea-912e-7d0d37b4c2ae · outbound

This paper cites Attention is all you need,.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Attention is all you need,

Reference 3

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Observation 8730195b-7d16-4751-b40d-86c4bd56daab · outbound

This paper cites Cognitive computational neuro- science,.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Cognitive computational neuro- science,

Reference 4

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Observation 8bdea2e9-d43c-4f05-bb4f-bc91eace66e6 · outbound

This paper cites Predictive coding and stochastic resonance as fundamental principles of auditory phantom perception,.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Predictive coding and stochastic resonance as fundamental principles of auditory phantom perception,

Reference 5

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Observation 5bbccd30-8289-442d-b388-6589f053fde6 · outbound

This paper cites Neural network based successor representations to form cognitive maps of space and language,.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Neural network based successor representations to form cognitive maps of space and language,

Reference 6

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Observation 1b9d8e40-5a7c-4df0-b52d-ab14bc395920 · outbound

This paper cites Neural network based formation of cognitive maps of semantic spaces and the putative emergence of abstract concepts,.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Neural network based formation of cognitive maps of semantic spaces and the putative emergence of abstract concepts,

Reference 7

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Observation 20904977-296e-4dbe-be38-97c9ffb8b4dc · outbound

This paper cites Multi-modal cognitive maps based on neural networks trained on successor representations,.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Multi-modal cognitive maps based on neural networks trained on successor representations,

Reference 8

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Observation 0d5250a8-6e0a-4360-a573-0d43223c0d5d · outbound

This paper cites Word class representations spontaneously emerge in a deep neural network trained on next word prediction,.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Word class representations spontaneously emerge in a deep neural network trained on next word prediction,

Reference 9

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Observation 9f6d7636-0299-44bf-9645-b8619a045be3 · outbound

This paper cites Biological constraints on neural network models of cognitive function,.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Biological constraints on neural network models of cognitive function,

Reference 10

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Source-reported events for the cited work

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Observation d26dda59-63b3-4fe5-846e-ae4bc06ad167 · outbound

This paper cites Sparsity through evolutionary pruning prevents neuronal networks from overfit- ting,.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Sparsity through evolutionary pruning prevents neuronal networks from overfit- ting,

Reference 11

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Observation bdf54182-467a-4358-80f8-2403ef390b4a · outbound

This paper cites Integration of leaky-integrate-and-fire neurons in standard machine learning architectures to generate hybrid networks: A surrogate gradient approach,.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Integration of leaky-integrate-and-fire neurons in standard machine learning architectures to generate hybrid networks: A surrogate gradient approach,

Reference 12

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Source-reported events for the cited work

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Observation 8ba8dcef-27f6-454e-ad26-bab07bbd14af · outbound

This paper cites Leaky-integrate- and-fire neuron-like long-short-term-memory units as model system in computational biology,.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Leaky-integrate- and-fire neuron-like long-short-term-memory units as model system in computational biology,

Reference 13

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Source-reported events for the cited work

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Observation ac229087-1b7e-410e-a1e9-b9e0a434f0bd · outbound

This paper cites Coincidence detection and integration behavior in spiking neural networks,.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Coincidence detection and integration behavior in spiking neural networks,

Reference 14

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Source-reported events for the cited work

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Observation ee4ba72b-c074-4953-9387-c86dee0f8afd · outbound

This paper cites Can we open the black box of ai?.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Can we open the black box of ai?

Reference 15

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Source-reported events for the cited work

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Observation 30a13322-d9c8-4a53-99b2-1c74c29b490a · outbound

This paper cites BERT: Pre- training of deep bidirectional transformers for language understanding,.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT BERT: Pre- training of deep bidirectional transformers for language understanding,

Reference 16

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Observation b3bd8c60-ba91-4ca1-9544-525e39e708d2 · outbound

This paper cites Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models

Reference 17

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Observation 33517ddb-20ff-437e-bc69-adbc851b1bb8 · outbound

This paper cites Multidimensional scaling: I. theory and method,.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Multidimensional scaling: I. theory and method,

Reference 18

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Observation 48cfbde3-1c55-4b15-b758-19bc96b84194 · outbound

This paper cites Nonmetric multidimensional scaling: a numerical method,.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Nonmetric multidimensional scaling: a numerical method,

Reference 19

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Observation 9a08d333-5d69-410f-9ff3-a34bd1000af6 · outbound

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Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Unresolved cited work

Reference 20

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Observation 50b6dc3d-8c8e-4486-82f9-66db487e6c52 · outbound

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Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Multidimensional scaling,

Reference 21

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Observation 039cfaaa-79fc-4f7b-8fab-80b7e313e9e1 · outbound

This paper cites Sleep as a random walk: a super-statistical analysis of eeg data across sleep stages,.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Sleep as a random walk: a super-statistical analysis of eeg data across sleep stages,

Reference 22

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Observation 48756eb9-301e-4aa2-95f3-bbc61d21fc6a · outbound

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Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Extracting continuous sleep depth from eeg data without machine learning,

Reference 23

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Observation 4c5a2002-c90c-4e9b-aa5f-9d2a9057cfa0 · outbound

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Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Classification at the accuracy limit: facing the problem of data ambiguity,

Reference 24

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Observation 1f3ee240-2012-4b42-901f-737ac8d7c9dd · outbound

This paper cites Analysis of continuous neuronal activity evoked by natural speech with computational corpus linguistics methods,.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Analysis of continuous neuronal activity evoked by natural speech with computational corpus linguistics methods,

Reference 25

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Observation cfec5fb6-2ccd-4ab6-8e38-f88bbff143e7 · outbound

This paper cites Quantify- ing the separability of data classes in neural networks,.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Quantify- ing the separability of data classes in neural networks,

Reference 26

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Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Analysis and visualization of sleep stages based on deep neural networks,

Reference 27

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This paper cites Analysis of structure and dynamics in three-neuron motifs,.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Analysis of structure and dynamics in three-neuron motifs,

Reference 28

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Observation ca7420e9-53eb-477b-8ef8-d31f35f29baa · outbound

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Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Recurrence reso- nance

Reference 29

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Observation 1bfe9b77-1002-45d3-9eca-6032e8d17ed1 · outbound

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Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Weight statistics controls dynamics in recurrent neural networks,

Reference 30

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Observation 5fe9cef3-8509-4492-ad73-250395a3b674 · outbound

This paper cites Quantifying and maximizing the information flux in recurrent neural networks.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Quantifying and maximizing the information flux in recurrent neural networks

Reference 31

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Observation ac579ca3-5eca-4a2e-b55c-f1cd780b14be · outbound

This paper cites A statistical method for analyzing and comparing spatiotemporal cortical activation patterns,.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT A statistical method for analyzing and comparing spatiotemporal cortical activation patterns,

Reference 32

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Observation 0b2c9b0b-2af5-4893-a2fc-87aaa04fbece · outbound

This paper cites Analysis of multichannel eeg patterns during human sleep: a novel approach,.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Analysis of multichannel eeg patterns during human sleep: a novel approach,

Reference 33

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Source-reported events for the cited work

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Observation 598d4188-68d6-4922-bebc-78b7245d0fb0 · outbound

This paper cites Microstructure of cortical activity during sleep reflects respiratory events and state of daytime vigilance,.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Microstructure of cortical activity during sleep reflects respiratory events and state of daytime vigilance,

Reference 34

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Observation 3232365c-513e-4674-a0d1-73325bf35afb · outbound

This paper cites Analyzing Narrative Processing in Large Language Models (LLMs): Using GPT4 to test BERT.

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Analyzing Narrative Processing in Large Language Models (LLMs): Using GPT4 to test BERT

Reference 35

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Pith citing papers

Observation 78f243d5-75e8-4552-93e0-0a63069aef0f · inbound

Probing Internal Representations of Multi-Word Verbs in Large Language Models cites this paper.

Probing Internal Representations of Multi-Word Verbs in Large Language Models Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-08-08T21:33:15.637021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-08T21:33:15.206087Z digest=sha256:a9fa69bb05f12911b507476cd942028bd5b9179986c54eb507e58a2074409bb9