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Paper Citation Record · LEDGER

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

As of 8 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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T10:22:59.086934Z digest=sha256:bbac74421021e91223288c4b1b9330bd93e83723596a653cfa398c9898946b9e

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T10:22:59.177562Z digest=sha256:352baba4124cffa1ef7d531a47488b2725c70fb2c1d045f33df0cb2929df6318

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T10:22:59.269687Z digest=sha256:8fb6b546ff2017f02a015f14972f8bce556d1691ae76b8df5ab3422fb337fb5e

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:f663e35d930a3ad098aecd76308e62294535dcea558491ac5f148de54f999ea7

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T10:22:59.420029Z digest=sha256:5ddaa5b10890d29b9415bad0b6a5ae86ce93329381424dde7f71672187557041

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T10:22:59.489594Z digest=sha256:ea462eaa5e1e9de7b71170ebc7105cb130fc9e70b3b1c6135fb359ed73fe732c

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=sha256:189316bcac56d0945d03a3d30f610e99550eba5374b4e94390e0c1c18e15f7df

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T10:22:59.632831Z digest=sha256:f2ba4555fd80db6506ae15a5ad48f0f81f1c9a6ec34a4f332c7e54c5f1bc3e4e

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=sha256:30d5f21b827047aaec0595f577d506c4e6791019c087c9cd61646c4f309fab04

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=sha256:17d4340025319d2464e49edcd5d3e3fefbf7b778b3fce7c1883bb70c46e17967

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=sha256:908d0a97aad568bbffe72fb00b8e025fb4239caa21e45c942d61ffc8b7e2fd74

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T10:22:59.855577Z digest=sha256:57c5639ad376f07691b2c001eee8e20aa9aab7ae726e968681fa367190dc451b

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T10:22:59.918002Z digest=sha256:cd03f2379fcd61b39b52e3dae3074c99fc804cc0748d7b9ef867c20a86f0b7e0

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T10:22:59.969473Z digest=sha256:f0da891f8e9af826b181fd1dd9ca78249ef80b734cf2434bdf4233f2c180c159

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=sha256:2dc7d5ed3f9f5a1a9c954210e5decb699d13a6811cc996ad7ec9e4f0ab7bf4ba

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=sha256:3d8d6fc9ff854330c292cec8f9fa0f8d241aadb6fcad6d145fdca5d5db869431

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:f084c7f44ef0c9ae770d2597d21a9fb4eb6ed09ddae07c1d43a2c24d7c3c45b9

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T10:23:00.198105Z digest=sha256:bc662542f6d404cfae50d132bcc9de9e57f006e274eb6de52219bc326f0199cf

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T10:23:00.254676Z digest=sha256:3386a0db3f7b7001bbcbe314e0f38a29ed3273796387a0f952d54ab6f71a0943

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=sha256:36c2650ab00b84865622c3ddc6493c16f1781732a30ae03aa4a255c4893f4764

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T10:23:00.375030Z digest=sha256:e800203eb0dffac42abbe8dd6da32e7e83e7035398a7d6dcd7129f7220dd3408

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T10:23:00.428870Z digest=sha256:caed386cfb8f82d74ee26eb1ed27f2448d15330acc5db7feb10f839762aacce4

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T10:23:00.499608Z digest=sha256:57b29c9b1829e6c7fd706c35b30e753c7e2dfb8ee210022885247221155ea85f

Pith citing papers

No inbound Pith citation observations are available.