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Paper Citation Record · LEDGER

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data

As of 20 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2506.05542.

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

pith.paper-citation-record.v1
2506.05542 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:23:00.499608Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

23 of 23 outbound references displayed

  • verified exact11
  • verified fuzzy3
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9e56f02b-0b86-476c-be9f-99f7bd41961a · outbound

This paper cites A Multivocal Literature Review on the Benefits and Limitations of Automated Machine Learning Tools.

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data A Multivocal Literature Review on the Benefits and Limitations of Automated Machine Learning Tools

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-08-07T10:23:02.492620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T10:22:59.086934Z digest=sha256:932f62770600c9558b3ee9e371f1acc2ae96ada67fa78240eab20b6653af0859

Observation 50b5e8c4-2b4b-4801-92a7-6698ea1b95bc · outbound

This paper cites Siddique, K.

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data Siddique, K

Reference 2

Resolution
verified exact
doi, observed 2026-08-07T10:23:01.496679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T10:22:59.177562Z digest=sha256:4ce1e1fd6b9e62b00ac9fa9fe8bf8cbdd0dd832e6e6220c90a1edb38b1491bf4

Observation af612994-66e5-40eb-8023-5bb5bb5e2fd7 · outbound

This paper cites Beyond Random Split for Assessing Statistical Model Performance.

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data Beyond Random Split for Assessing Statistical Model Performance

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-08-07T10:23:02.366725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T10:22:59.269687Z digest=sha256:0358477f7884527d34cb1b2a08e1e0fc16877d99acdda79c0fb3f9b62debe498

Observation 00a96ab0-57aa-4f08-a269-a73cf4789e00 · outbound

This paper cites MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering.

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T10:22:59.340621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:22:59.340621Z digest=sha256:e10fbb9b961fe51c5205ea12bbaaace6ba47c9fa2f5c3a5ef740477395982331

Observation 9ed190dd-76a0-4763-8d88-dd755368d411 · outbound

This paper cites Auto-sklearn 2.0: hands-free automl via meta-learning.

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data Auto-sklearn 2.0: hands-free automl via meta-learning

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:23:03.007895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T10:22:59.420029Z digest=sha256:b987e20f479a726d4a6f55c5c595e6d1154bbea5a895fef85683a7f2549ec030

Observation 77ac9dbd-f500-49ce-8a4c-46a3c1f090ec · outbound

This paper cites Genomic benchmarks: a collection of datasets for genomic sequence classification.

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data Genomic benchmarks: a collection of datasets for genomic sequence classification

Reference 6

Resolution
verified exact
doi, observed 2026-08-07T10:23:01.391299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T10:22:59.489594Z digest=sha256:8658a6250929ffdf4f36bbb552c2972b46bf0744bf7b529ca10732e497100a88

Observation e6dfa7e8-e547-4993-b105-acb4afda7ac5 · outbound

This paper cites Data Interpreter: An LLM Agent For Data Science.

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data Data Interpreter: An LLM Agent For Data Science

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T10:22:59.545205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:22:59.545205Z digest=sha256:d570705ff5b47f4c967c531577b9374eeaa1d54979973ab80aa404ec223e1ccb

Observation 3e1e8689-d57b-4d30-a5a8-29a4ff54ae8c · outbound

This paper cites Meta GPT : Meta programming for a multi-agent collaborative framework.

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data Meta GPT : Meta programming for a multi-agent collaborative framework

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:23:02.846231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T10:22:59.632831Z digest=sha256:2538df23d08ee7f5147e0750fcaa435818d195bcec747add5ae15eb8d2636498

Observation c0913741-ea1a-45d3-8443-1b3869f10af8 · outbound

This paper cites MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation.

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T10:22:59.699319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:22:59.699319Z digest=sha256:5a60937056109b52f9531fa1b8e9052b68f9e7a7c4e12587ce2d22dac9478dfe

Observation 25f0b18d-ab58-4cf2-aefe-23fc21cb1dce · outbound

This paper cites Understanding the planning of LLM agents: A survey.

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data Understanding the planning of LLM agents: A survey

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T10:22:59.766246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:22:59.766246Z digest=sha256:0dc29d15d0e53df4d42d5686f3f235b04f39bd1b3aef5b0aea9df6fe9db40b26

Observation c6d613a1-0e68-47a9-aa12-449bcdf2b773 · outbound

This paper cites AIDE: AI-Driven Exploration in the Space of Code.

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data AIDE: AI-Driven Exploration in the Space of Code

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T10:22:59.807346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:22:59.807346Z digest=sha256:006eb66a24a8b2d1f1c30cafc587b8b298c6c7bf3368b46d7b953ae0589ee007

Observation ebe9fc7f-fa4f-4d2b-a32e-00191f17e3d9 · outbound

This paper cites Model Decides How to Tokenize: Adaptive DNA Sequence Tokenization with MxDNA.

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data Model Decides How to Tokenize: Adaptive DNA Sequence Tokenization with MxDNA

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-08-07T10:23:02.080819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T10:22:59.855577Z digest=sha256:47bd03f1503ed10f8eb11a8330b9245a933ea7bd9f0310ae8d52daf1314747f9

Observation c65b1d1f-6ed4-4814-bec1-f9e733d5ec4f · outbound

This paper cites mirbench: novel benchmark datasets for microrna binding site prediction that mitigate against prevalent microrna frequency class bias.

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data mirbench: novel benchmark datasets for microrna binding site prediction that mitigate against prevalent microrna frequency class bias

Reference 13

Resolution
verified exact
doi, observed 2026-08-07T10:23:01.193781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T10:22:59.918002Z digest=sha256:f6cc008c73e62ec5595a05b5fa426b2703090bf4ade43fdd3198f4695b11fb36

Observation 1c57215a-2941-4369-a7d7-8ab868fc762c · outbound

This paper cites Robinson, and Giorgio Valentini.

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data Robinson, and Giorgio Valentini

Reference 14

Resolution
verified exact
doi, observed 2026-08-07T10:23:01.051419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T10:22:59.969473Z digest=sha256:c0506ade8f9a513a6fb9075b5f641b9c6be6df82d3513b73d0f2964316df25c4

Observation 1a292430-24ad-486d-9b38-9fe9d1d2f7af · outbound

This paper cites Reflexion: Language Agents with Verbal Reinforcement Learning.

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data Reflexion: Language Agents with Verbal Reinforcement Learning

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T10:23:00.034729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:23:00.034729Z digest=sha256:3bb4375a7e70e614ebe2a292a043aab599c4403c71b3e5878e985eab5f284675

Observation f1df6b41-d702-4ca7-8eee-64ad766e406b · outbound

This paper cites A survey on large language model-based agents for statistics and data science, 2024.

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data A survey on large language model-based agents for statistics and data science, 2024

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T10:23:00.093882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:23:00.093882Z digest=sha256:8cedca8bef950b752b0d4cd56c896294670312a2b35d9f40e34a6b286606c12d

Observation 0c9f7701-e6a7-4bac-980e-33351b78ee4c · outbound

This paper cites Automl in the wild: Obstacles, workarounds, and expectations.

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data Automl in the wild: Obstacles, workarounds, and expectations

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T10:23:00.143701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:23:00.143701Z digest=sha256:06d68b09dd37f3e13ded847bfdb1eebc9fa80e66f711d8aedd771fffdb99c750

Observation d4cda6b8-ddc1-4adf-a2b9-6e9438a57a10 · outbound

This paper cites MSAM amba: Adapting subquadratic models to long-context DNA MSA analysis.

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data MSAM amba: Adapting subquadratic models to long-context DNA MSA analysis

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:23:02.645026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T10:23:00.198105Z digest=sha256:f360b53216669fede9945da49df183b5b40848392541bf05d8576bae73216b4d

Observation 418ee899-6124-4cb4-b814-29aafe2607e7 · outbound

This paper cites o rheide, Jan Krumsiek, Gabi Kastenm\.

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data o rheide, Jan Krumsiek, Gabi Kastenm\

Reference 19

Resolution
verified exact
doi, observed 2026-08-07T10:23:00.941453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T10:23:00.254676Z digest=sha256:6a3ba4f03bcbc0fff9443b8f0466ecb7c49ad4c0faf7bd458b671a04f4b91a58

Observation 8b183457-efd2-48e3-a771-36694bf8731e · outbound

This paper cites Revealing the Barriers of Language Agents in Planning.

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data Revealing the Barriers of Language Agents in Planning

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T10:23:00.321242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:23:00.321242Z digest=sha256:a2f2e4d5a6a3698339bc8294e9874ed681c928b4f819dab7702d500c580998a2

Observation 1ae42ab4-71ff-49ab-b469-675ace5e06eb · outbound

This paper cites an unresolved cited work.

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data Unresolved cited work

Reference 21

Resolution
verified exact
doi, observed 2026-08-07T10:23:00.787589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T10:23:00.375030Z digest=sha256:7f55bb09e967fa7ce1fe17cb0fb3fabd96168d4d32bc21ca2b44b4ba12160470

Observation d8c729f5-d9c2-4d35-aca4-1b72a2533855 · outbound

This paper cites Self-Distillation Improves DNA Sequence Inference.

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data Self-Distillation Improves DNA Sequence Inference

Reference 22

Resolution
verified exact
local_arxiv, observed 2026-08-07T10:23:01.679651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T10:23:00.428870Z digest=sha256:a4f3dd83a2cecc9188d95f4dabeb213a608f90e1253981fff686117b34ec1fcf

Observation 65dcbd98-fda2-4ed7-b5f1-02e55a0ebeee · outbound

This paper cites Assessing and mitigating batch effects in large-scale omics studies.

Agentomics-ML: Autonomous Machine Learning Experimentation Agent for Genomic and Transcriptomic Data Assessing and mitigating batch effects in large-scale omics studies

Reference 23

Resolution
verified exact
doi, observed 2026-08-07T10:23:00.672015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T10:23:00.499608Z digest=sha256:25b9230893c3502759fbce04e13d002920f36c3b23a088414fdc26abd718bf54

Pith citing papers

No inbound Pith citation observations are available.