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Paper Citation Record · LEDGER

Large Language Models for Automated Open-domain Scientific Hypotheses Discovery

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2309.02726.

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

pith.paper-citation-record.v1
2309.02726 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:35:44.300728Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T08:59:43.440127Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation c9125a4f-d4b5-4e60-bba5-e0b386f19d13 · inbound

The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery cites this paper.

The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery Large Language Models for Automated Open-domain Scientific Hypotheses Discovery

Reference 109

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T04:42:32.097468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-11T04:42:31.555355Z digest=sha256:47842cc914a91921b0327bf356f16300926904b8ce7d2e0c4fc894a721b5651d

Observation ac650f2b-899c-4d49-a0ba-9dcbdf241ec6 · inbound

Toward Reliable Scientific Hypothesis Generation: Evaluating Truthfulness and Hallucination in Large Language Models cites this paper.

Toward Reliable Scientific Hypothesis Generation: Evaluating Truthfulness and Hallucination in Large Language Models Large Language Models for Automated Open-domain Scientific Hypotheses Discovery

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-07T15:35:44.300728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:35:44.300728Z digest=sha256:396cd9e529a32953cf25e8765e8ad2780c0ca2a68530037cb021c6f1284737de

Observation 6fb2e8a8-951b-43ec-919c-4261fd134151 · inbound

InternAgent: When Agent Becomes the Scientist -- Building Closed-Loop System from Hypothesis to Verification cites this paper.

InternAgent: When Agent Becomes the Scientist -- Building Closed-Loop System from Hypothesis to Verification Large Language Models for Automated Open-domain Scientific Hypotheses Discovery

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:37.438336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:56:37.438336Z digest=sha256:1e7593a82f4472d4c8f23801c0212961f941533f6cfc8ae3677fa9e6a85dee58

Observation 85cd80b3-c692-491e-aa1f-7f008841dfc3 · inbound

Harnessing Large Language Models for Scientific Novelty Detection cites this paper.

Harnessing Large Language Models for Scientific Novelty Detection Large Language Models for Automated Open-domain Scientific Hypotheses Discovery

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-07T12:23:14.533610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:23:14.533610Z digest=sha256:249a4ef2c9261480bb43ede0e2dd0bb049385d2fd4ce368fe5a6da45eaa0ab36

Observation b08b640b-8ed6-40b7-b74d-227664800a37 · inbound

EXP-Bench: Can AI Conduct AI Research Experiments? cites this paper.

EXP-Bench: Can AI Conduct AI Research Experiments? Large Language Models for Automated Open-domain Scientific Hypotheses Discovery

Reference 103

Resolution
unresolved
no resolver link, observed 2026-08-07T12:20:48.644954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:20:48.644954Z digest=sha256:4414a4c8ee93655220910560498cb3af3b18405783627d6af4229504919a3f56

Observation c07242ec-f284-474b-bfe2-cd91b620d38e · inbound

Smotrom tvoja pa ander drogoj verden! Resurrecting Dead Pidgin with Generative Models: Russenorsk Case Study cites this paper.

Smotrom tvoja pa ander drogoj verden! Resurrecting Dead Pidgin with Generative Models: Russenorsk Case Study Large Language Models for Automated Open-domain Scientific Hypotheses Discovery

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T12:08:35.592330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:08:35.592330Z digest=sha256:3db56c49e63a4e6c60ed6083d233204eb88645d2fa3d9746c299ac9caad47f8a

Observation 6930e9a7-e5e6-45d1-934c-2717e0f08367 · inbound

THE-Tree: Can Tracing Historical Evolution Enhance Scientific Verification and Reasoning? cites this paper.

THE-Tree: Can Tracing Historical Evolution Enhance Scientific Verification and Reasoning? Large Language Models for Automated Open-domain Scientific Hypotheses Discovery

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T22:24:49.346260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:24:49.346260Z digest=sha256:9fc87a214506f2efb0eabdddb9e6ff8ab1f9ea9208ad29bb1ca652774be89d16

Observation 403ef7dd-3617-46af-a8a4-dac0cfcc14c5 · inbound

ShinkaEvolve: Towards Open-Ended And Sample-Efficient Program Evolution cites this paper.

ShinkaEvolve: Towards Open-Ended And Sample-Efficient Program Evolution Large Language Models for Automated Open-domain Scientific Hypotheses Discovery

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-05-16T13:58:58.793735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-16T13:58:58.627748Z digest=sha256:78d7cb85d93cc9685a1690b9ba9a5c86175e2cd5b42e185897067475363c77ed

Observation 89c97a68-bf83-41f0-9085-01e7a0065c2f · inbound

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models cites this paper.

RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models Large Language Models for Automated Open-domain Scientific Hypotheses Discovery

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-04T08:39:44.933593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T08:39:44.933593Z digest=sha256:d89bae1be81233ee40d11f1893c3c4fc921fb242cc99891ef331346545c32123

Observation e59c4de4-408b-49ec-82f4-bf2a70a4fddb · inbound

Unlocking LLM Creativity in Science through Analogical Reasoning cites this paper.

Unlocking LLM Creativity in Science through Analogical Reasoning Large Language Models for Automated Open-domain Scientific Hypotheses Discovery

Reference 52

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T01:57:05.594053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-13T01:53:26.159310Z digest=sha256:de9793072bb873cd6c99e1531792b8fe2f0b0addd8d629b6ca0c36a53604098f

Observation 2185a596-76b6-4500-ac01-78015ac13c5e · inbound

Sakana Fugu Technical Report cites this paper.

Sakana Fugu Technical Report Large Language Models for Automated Open-domain Scientific Hypotheses Discovery

Reference 82

Resolution
verified exact
arxiv_id, observed 2026-07-04T06:39:36.898472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-26T14:22:37.596720Z digest=sha256:859e0764c5e83d23be960e0ff551b10edff7fe7b55da844dadd35af946a4d9d8

Observation 8edc1e13-d7fd-4612-ab9a-904de4729753 · inbound

PaperClaw: Harnessing Agents for Autonomous Research and Human-in-the-Loop Refinement cites this paper.

PaperClaw: Harnessing Agents for Autonomous Research and Human-in-the-Loop Refinement Large Language Models for Automated Open-domain Scientific Hypotheses Discovery

Reference 63

Resolution
verified exact
arxiv_id, observed 2026-07-04T08:59:43.442220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-26T10:36:14.840581Z digest=sha256:47fceca0855e8ae9366cf548b969a95524cc3f4b78ea22b29a49d197f69c75fb