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Paper Citation Record · LEDGER

BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2405.17631.

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

pith.paper-citation-record.v1
2405.17631 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T17:02:06.887726Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

16
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 8631d709-1d52-4242-8694-bdf5ce168268 · inbound

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics cites this paper.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-09T17:02:06.887726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T17:02:06.887726Z digest=sha256:31720b04c5756037a40adea446af4da9b91f7e34325fbb0dacbadd793fda38ed

Observation a4a99c9f-cb07-497d-9135-748da9a7f875 · inbound

Large Language Model Agent: A Survey on Methodology, Applications and Challenges cites this paper.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments

Reference 273

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.265744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:28ee1e7e73eb0f7ce19f2fa224976cd51f524c12e03b6e9120c599bc7be897f9

Observation b5e3ed40-6122-4fe6-a32a-9bdfc24f77f5 · inbound

ToolRL: Reward is All Tool Learning Needs cites this paper.

ToolRL: Reward is All Tool Learning Needs BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments

Reference 28

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T00:26:48.507995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-14T00:26:48.291431Z digest=sha256:99aa76175947a766258f9d75b3b5793b0b84fe72d475a16984a65b51188f0ed5

Observation 9639fb9a-8020-40af-9ab3-ae59f1313afa · inbound

The Curious Language Model: Strategic Test-Time Information Acquisition cites this paper.

The Curious Language Model: Strategic Test-Time Information Acquisition BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T04:58:46.627887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:58:46.627887Z digest=sha256:f747194af8d0e59b7f1155aacc497873c0e78907bced930122981002127026c4

Observation 9efd8b6d-70d7-42c3-82a7-5945e2ad8afd · inbound

Multi-level Value Alignment in Agentic AI Systems: Survey and Perspectives cites this paper.

Multi-level Value Alignment in Agentic AI Systems: Survey and Perspectives BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-07T04:46:04.260208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:46:04.260208Z digest=sha256:7afba2cce10e18a62a914fe43deffac5d2ca6b3f1cca9033bfdb10d45031ff3a

Observation c02c1033-7abe-4c7c-a9da-bcc2610ca36e · inbound

Measuring Scientific Capabilities of Language Models with a Systems Biology Dry Lab cites this paper.

Measuring Scientific Capabilities of Language Models with a Systems Biology Dry Lab BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments

Reference 2014

Resolution
unresolved
no resolver link, observed 2026-08-06T20:44:34.656245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:44:34.656245Z digest=sha256:643fd7ed67466768145889a7c9f282f329b850a5fecb0caa5a0322db1ffa5fb3

Observation e12bf917-eb58-4c71-94db-18f3f2aecdf3 · inbound

How Far Are AI Scientists from Changing the World? cites this paper.

How Far Are AI Scientists from Changing the World? BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments

Reference 138

Resolution
unresolved
no resolver link, observed 2026-08-06T10:55:14.978067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T10:55:14.978067Z digest=sha256:7d976aec4fa11798b4d387b2c6ff3181bdef84b698388ea7050f5538430c87f7

Observation 1550bc0b-a0cb-45fd-9be0-c82dc72d8368 · inbound

IR-Agent: Expert-Inspired LLM Agents for Structure Elucidation from Infrared Spectra cites this paper.

IR-Agent: Expert-Inspired LLM Agents for Structure Elucidation from Infrared Spectra BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-21T23:20:45.268221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-21T23:16:08.658251Z digest=sha256:6b2db9b3efced3da5ca494590259c0aa8a8fd29ee659a5918382652d20c6f06e

Observation 100f041a-506f-4cc1-81df-be72022c951f · inbound

Artificial Intelligence for Food Innovation cites this paper.

Artificial Intelligence for Food Innovation BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments

Reference 111

Resolution
verified exact
arxiv_id, observed 2026-05-18T13:36:24.749355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T13:36:03.477677Z digest=sha256:50579cd4d38650ddf1c97d605e26d6f5a78f0fe32dbaa1e110574d1fc676c302

Observation 6f3786f5-3c1d-4f28-ab9f-351559487114 · inbound

Agentic Exploration of Physics Models cites this paper.

Agentic Exploration of Physics Models BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-04T13:51:31.086073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T13:51:31.086073Z digest=sha256:c5b0eb4964a1758decf662846e694beaacd18f319b83d7a0da7866b9a95ed0d2

Observation 1eca329c-859c-4513-99de-483dbca6f94f · inbound

DiscoverPhysics: Benchmarking LLMs for Out-of-the-Box Scientific Thinking cites this paper.

DiscoverPhysics: Benchmarking LLMs for Out-of-the-Box Scientific Thinking BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-06-29T22:54:01.645604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T20:32:43.417695Z digest=sha256:36046294058690e77a03746d446bb397831f4b34731a808aa1252cc4c972790f

Observation aa86f253-04e8-41dc-a5bc-f419bc33eacb · inbound

Closed-Loop Molecular Design with Calibrated Deference cites this paper.

Closed-Loop Molecular Design with Calibrated Deference BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments

Reference 5

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T09:23:16.460755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T09:18:03.906441Z digest=sha256:69531b6680fd666d88da00680b7cfe0e4ab3924fa8517196a9ed91e9461ee054

Observation 10356228-9a92-41f3-8b9a-53e6471e7e75 · inbound

OPD-Evolver: Cultivating Holistic Agent Evolver via On-Policy Distillation cites this paper.

OPD-Evolver: Cultivating Holistic Agent Evolver via On-Policy Distillation BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments

Reference 97

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T20:48:56.384946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-27T01:07:49.603969Z digest=sha256:0705026b385be690db6ac772e76fdde55945e8107118b958a28a5955f04b12c6

Observation aa4d3e4c-4d8b-41fe-8146-676519244949 · inbound

Artificial Intelligence and the Generative Science of Food Formulation cites this paper.

Artificial Intelligence and the Generative Science of Food Formulation BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments

Reference 56

Resolution
unresolved
no resolver link, observed 2026-07-13T02:22:20.803008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T02:22:20.803008Z digest=sha256:406d8c1bde155066c381d0653944c8335c13ed23fc12b5c192e5b9a510343e89