Paper Citation Record · LEDGER

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2504.19017.

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

pith.paper-citation-record.v1
2504.19017 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 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 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:45:12.724685Z

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

8
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 f34d9202-adfd-4a42-b84c-e034d745a948 · inbound

AI4Research: A Survey of Artificial Intelligence for Scientific Research cites this paper.

AI4Research: A Survey of Artificial Intelligence for Scientific Research Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles

Reference 235

Resolution: unresolved; no resolver link, observed 2026-08-06T20:45:12.724685Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b178eda4-b34a-4a7e-abe8-69f45fbf16be · inbound

AMD-Mamba: A Phenotype-Aware Multi-Modal Framework for Robust AMD Prognosis cites this paper.

AMD-Mamba: A Phenotype-Aware Multi-Modal Framework for Robust AMD Prognosis Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-06T04:49:30.630031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aae25e78-d18c-4afd-abb4-be9b2160e38d · inbound

Artificial Intelligence for Food Innovation cites this paper.

Artificial Intelligence for Food Innovation Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles

Reference 110

Resolution: verified exact; arxiv_id, observed 2026-05-18T13:36:24.685558Z

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.

Observation 610d61b7-5ee5-4a9d-a508-abf2236e032e · inbound

Reasoning4Sciences: Bridging Reasoning Language Models to All Scientific Branches cites this paper.

Reasoning4Sciences: Bridging Reasoning Language Models to All Scientific Branches Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles

Reference 90

Resolution: verified exact; arxiv_id, observed 2026-07-01T20:56:14.396373Z

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.

Observation a269df24-0b79-4762-ad7f-149e8f7b9b0d · inbound

Reasoning4Sciences: Bridging Reasoning Language Models to All Scientific Branches cites this paper.

Reasoning4Sciences: Bridging Reasoning Language Models to All Scientific Branches Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles

Reference 98

Resolution: verified exact; arxiv_id, observed 2026-07-01T08:35:34.087530Z

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.

Observation 3be25de4-e0de-4428-9b68-4ce2c2690611 · inbound

Self-Revising Discovery Systems for Science: A Categorical Framework for Agentic Artificial Intelligence cites this paper.

Self-Revising Discovery Systems for Science: A Categorical Framework for Agentic Artificial Intelligence Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-01T21:36:14.488724Z

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.

Observation 78146fbf-6448-4d10-b936-2983e8c5e7d2 · inbound

Graph-Native Reinforcement Learning Enables Traceable Scientific Hypothesis Generation through Conceptual Recombination cites this paper.

Graph-Native Reinforcement Learning Enables Traceable Scientific Hypothesis Generation through Conceptual Recombination Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles

Reference 32

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T12:26:55.833579Z

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.

Observation cbc2c852-5eb8-42b1-ae56-618a081a5fad · inbound

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

Artificial Intelligence and the Generative Science of Food Formulation Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles

Reference 24

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0780f5f7-3df9-4cfa-a236-570e0238ba35 · inbound

Reading and Steering Representations of Materials-Science Mechanisms in an Open-Weight Language Model cites this paper.

Reading and Steering Representations of Materials-Science Mechanisms in an Open-Weight Language Model Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T10:59:54.581935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fcfadf6c-3658-4ad6-bbf7-896e686b5a51 · inbound

Evaluating Agentic Bioinformatics through Function, Evidence, and Validation cites this paper.

Evaluating Agentic Bioinformatics through Function, Evidence, and Validation Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-01T05:48:20.151129Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.