Paper Citation Record · LEDGER

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models

As of 14 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2607.19618.

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

pith.paper-citation-record.v1
2607.19618 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T12:16:37.093720Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

31 of 31 outbound references displayed

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unresolved31
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External citation measurements

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Outbound references

Observation fb044b90-aaa1-4ad2-8f48-2f4c2f4e7127 · outbound

This paper cites Nucleotide transformer: building and evaluating robust foundation models for human genomics.Nature Methods, 22(2):287–297, 2025.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Nucleotide transformer: building and evaluating robust foundation models for human genomics.Nature Methods, 22(2):287–297, 2025

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:32.922651Z

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Observation 5f430a50-b29f-4e8b-aba9-fa7c06e3b787 · outbound

This paper cites Dnabert-2: Ef- ficient foundation model and benchmark for multi-species genomes.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Dnabert-2: Ef- ficient foundation model and benchmark for multi-species genomes

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:33.031053Z

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Observation 0c44728f-372e-4732-a358-365f5e589dd6 · outbound

This paper cites Ca- duceus: Bi-directional equivariant long-range dna sequence modeling.Proceedings of machine learn- ing research, 235:43632, 2024.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Ca- duceus: Bi-directional equivariant long-range dna sequence modeling.Proceedings of machine learn- ing research, 235:43632, 2024

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:33.191187Z

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Observation d52b6a93-b981-4fa7-a825-ee44fefd34f1 · outbound

This paper cites Hyenadna: Long-range genomic sequence modeling at single nucleotide resolution.Advances in neural information processing systems, 36:43177–43201, 2023.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Hyenadna: Long-range genomic sequence modeling at single nucleotide resolution.Advances in neural information processing systems, 36:43177–43201, 2023

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:33.398054Z

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Observation 8c1d8364-6cb8-4913-bb9c-1d9f19e0272e · outbound

This paper cites Sequence modeling and design from molecular to genome scale with evo.Science, 386(6723):eado9336, 2024.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Sequence modeling and design from molecular to genome scale with evo.Science, 386(6723):eado9336, 2024

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:33.560482Z

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Observation 5703fbbf-5a71-44dd-b345-64923f84ba2e · outbound

This paper cites Dna language models are powerful predictors of genome-wide variant effects.Proceedings of the National Academy of Sciences, 120(44):e2311219120, 2023.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Dna language models are powerful predictors of genome-wide variant effects.Proceedings of the National Academy of Sciences, 120(44):e2311219120, 2023

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:33.722463Z

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Observation 0d7a0213-8070-440c-99c7-e3b5531f1129 · outbound

This paper cites Predicting effects of noncoding variants with deep learning–based sequence model.Nature methods, 12(10):931–934, 2015.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Predicting effects of noncoding variants with deep learning–based sequence model.Nature methods, 12(10):931–934, 2015

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:33.885833Z

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Observation 64b1aa95-6266-44d5-8043-2e3d85835c15 · outbound

This paper cites Sequential regulatory activity prediction across chromosomes with convolutional neural net- works.Genome research, 28(5):739, 2018.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Sequential regulatory activity prediction across chromosomes with convolutional neural net- works.Genome research, 28(5):739, 2018

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:34.060424Z

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Observation f111d83d-d385-4b91-b6b6-237d5d04596c · outbound

This paper cites Effective gene expression prediction from sequence by integrating long-range interactions.Nature methods, 18(10): 1196–1203, 2021.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Effective gene expression prediction from sequence by integrating long-range interactions.Nature methods, 18(10): 1196–1203, 2021

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:34.266081Z

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Observation be6d67a4-a2b4-40a6-a182-a59c852a6d9e · outbound

This paper cites Toy Models of Superposition.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Toy Models of Superposition

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:34.407838Z

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Observation 83591c5e-cbbd-4632-a300-2fcbcab7aeba · outbound

This paper cites Obtaining genetics insights from deep learning via explainable artificial intelligence.Nature Reviews Genetics, 24(2):125–137, 2023.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Obtaining genetics insights from deep learning via explainable artificial intelligence.Nature Reviews Genetics, 24(2):125–137, 2023

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:34.562095Z

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Observation 2abb9f6f-74ab-4e44-8722-818e6e44705d · outbound

This paper cites Sparse Autoencoders Find Highly Interpretable Features in Language Models.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Sparse Autoencoders Find Highly Interpretable Features in Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:34.694492Z

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Observation e132f4da-d754-4f41-9877-280d2c1859c0 · outbound

This paper cites Burke, Tristan Hume, Shan Carter, Tom Henighan, and Chris Olah.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Burke, Tristan Hume, Shan Carter, Tom Henighan, and Chris Olah

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:34.846333Z

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Observation 582211e0-3f10-406e-9c6c-98084acad808 · outbound

This paper cites Scaling monosemanticity: Extracting interpretable features from Claude 3 Sonnet.Transformer Circuits Thread, 2024.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Scaling monosemanticity: Extracting interpretable features from Claude 3 Sonnet.Transformer Circuits Thread, 2024

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:34.966306Z

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Observation 4dc6e423-a2e8-4042-b16f-96c0183b8b60 · outbound

This paper cites Scaling and evaluating sparse autoencoders.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Scaling and evaluating sparse autoencoders

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:35.095933Z

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Observation f6cca4f3-54c7-49c8-b0e2-5b7888ea7041 · outbound

This paper cites Alu elements: know the sines.Genome biology, 12(12):236, 2011.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Alu elements: know the sines.Genome biology, 12(12):236, 2011

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:35.186571Z

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Observation 415661c3-cfa9-481e-85cf-bbb9322a2c86 · outbound

This paper cites Multiparameter functional diversity of human c2h2 zinc finger proteins.Genome research, 26(12):1742, 2016.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Multiparameter functional diversity of human c2h2 zinc finger proteins.Genome research, 26(12):1742, 2016

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:35.312201Z

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Observation 17b35e76-1d5c-47bc-81f1-91f49fc17b65 · outbound

This paper cites Dnabert: pre-trained bidirectional en- coder representations from transformers model for dna-language in genome.Bioinformatics, 37(15): 2112–2120, 2021.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Dnabert: pre-trained bidirectional en- coder representations from transformers model for dna-language in genome.Bioinformatics, 37(15): 2112–2120, 2021

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:35.479285Z

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Observation 12d28eca-cdf5-4222-8533-b816b8cf0dd7 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:35.646853Z

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Observation 0a98ea9c-6856-4a72-b460-87bc97d880e1 · outbound

This paper cites Evaluating the representational power of pre- trained dna language models for regulatory genomics.Genome Biology, 26(1):203, 2025.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Evaluating the representational power of pre- trained dna language models for regulatory genomics.Genome Biology, 26(1):203, 2025

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:35.815063Z

Source-reported events for the cited work

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Observation e42cda79-b191-427e-a345-4522d862f051 · outbound

This paper cites Learning important features through prop- agating activation differences.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Learning important features through prop- agating activation differences

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:35.932538Z

Source-reported events for the cited work

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Observation 38de2337-9600-477e-8840-8da853aec41a · outbound

This paper cites A unified approach to interpreting model predictions.Advances in neural information processing systems, 30, 2017.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models A unified approach to interpreting model predictions.Advances in neural information processing systems, 30, 2017

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:36.067591Z

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Observation 42acdb4a-e4b9-4177-9a95-b9cccb32a8b6 · outbound

This paper cites Investigating gender bias in language models using causal mediation analysis.Advances in neural information processing systems, 33:12388–12401, 2020.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Investigating gender bias in language models using causal mediation analysis.Advances in neural information processing systems, 33:12388–12401, 2020

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:36.177273Z

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Observation cde3efe9-ed70-49cb-a283-5bd7332304d1 · outbound

This paper cites Locating and editing factual associa- tions in gpt.Advances in neural information processing systems, 35:17359–17372, 2022.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Locating and editing factual associa- tions in gpt.Advances in neural information processing systems, 35:17359–17372, 2022

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:36.308397Z

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Observation bcdf71e9-cc86-477b-9c51-d653a6dc43fa · outbound

This paper cites Is This the Subspace You Are Looking for? An Interpretability Illusion for Subspace Activation Patching.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Is This the Subspace You Are Looking for? An Interpretability Illusion for Subspace Activation Patching

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:36.421738Z

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Observation 7ba3fb27-6152-4c79-a2b0-4ec2f1553f46 · outbound

This paper cites Jaspar 2024: 20th anniversary of the open-access database of transcription factor binding profiles.Nucleic acids research, 52(D1):D174–D182, 2024.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Jaspar 2024: 20th anniversary of the open-access database of transcription factor binding profiles.Nucleic acids research, 52(D1):D174–D182, 2024

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:36.534317Z

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Observation f3564bfa-afef-4d65-b711-c176d327879a · outbound

This paper cites Hocomoco in 2024: a rebuild of the curated collection of binding models for human and mouse transcription factors.Nucleic Acids Research, 52(D1):D154–D163, 2024.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Hocomoco in 2024: a rebuild of the curated collection of binding models for human and mouse transcription factors.Nucleic Acids Research, 52(D1):D154–D163, 2024

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:36.632073Z

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Observation 9a06e53d-8ac9-4ed4-9dd4-23991c3fb1e3 · outbound

This paper cites An integrated encyclopedia of dna elements in the human genome.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models An integrated encyclopedia of dna elements in the human genome

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:36.726940Z

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Observation a0632d3d-e9ae-44b4-a894-f77a315cde68 · outbound

This paper cites Expanded encyclopaedias of dna elements in the human and mouse genomes.Nature, 583(7818):699–710, 2020.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Expanded encyclopaedias of dna elements in the human and mouse genomes.Nature, 583(7818):699–710, 2020

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:36.861231Z

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Observation 1697eb0a-f32c-44f6-adc6-5864c168cd0e · outbound

This paper cites Ctcf: an architectural protein bridging genome topology and function.Nature Reviews Genetics, 15(4):234–246, 2014.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models Ctcf: an architectural protein bridging genome topology and function.Nature Reviews Genetics, 15(4):234–246, 2014

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:36.971118Z

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Observation 4af3c25d-8ec8-4614-9d43-d0d6f493b103 · outbound

This paper cites On a test of whether one of two random variables is stochasti- cally larger than the other.The annals of mathematical statistics, pages 50–60, 1947.

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models On a test of whether one of two random variables is stochasti- cally larger than the other.The annals of mathematical statistics, pages 50–60, 1947

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-01T12:16:37.093720Z

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Pith citing papers

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