Paper Citation Record · LEDGER

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

As of 23 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 11 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 66 of 66 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:09:41.199937Z

measured 77 of 77 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:54:43.202074Z

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

66 of 66 outbound references displayed

verified exact0
verified fuzzy20
unresolved46
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

8
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation e2bdbc7b-cc63-4a46-9094-e4851ea81ad3 · outbound

This paper cites & Hinton, G.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles & Hinton, G

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:09:41.905647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c06c27be-15fc-42d8-91b5-f295b40be046 · outbound

This paper cites & Schmidhuber, J.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles & Schmidhuber, J

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:40.957115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9e6a44c-6be7-4e53-9bc7-4e68cc7a3287 · outbound

This paper cites S.The Structure of Scientific Revolutions (University of Chicago Press, 1962).

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles S.The Structure of Scientific Revolutions (University of Chicago Press, 1962)

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:09:41.894302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation aa93cf3f-5ebd-4966-b71c-51be84c1a140 · outbound

This paper cites & Stanley, K.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles & Stanley, K

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:09:41.882623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation bf12487f-32e5-4fdd-ac40-0c8c60b1182f · outbound

This paper cites Towards Scientific Discovery with Generative AI: Progress, Opportunities, and Challenges.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles Towards Scientific Discovery with Generative AI: Progress, Opportunities, and Challenges

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:40.970691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35b974c8-7115-4d41-9ec0-ec33a063dea8 · outbound

This paper cites an unresolved cited work.

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

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:40.974611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e95e28d4-3c8b-4dca-b634-f38baa1ffe4c · outbound

This paper cites an unresolved cited work.

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

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:09:41.871439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation fe7917bd-02c7-4b33-bd9a-9c80daed2d79 · outbound

This paper cites & Lipson, H.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles & Lipson, H

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:40.982664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45172b77-c8f8-4c8d-978a-fa758ac97bc4 · outbound

This paper cites Graph-Aware Isomorphic Attention for Adaptive Dynamics in Transformers.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles Graph-Aware Isomorphic Attention for Adaptive Dynamics in Transformers

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:40.986204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30117ef4-e0d9-4e41-afde-eb15749a668a · outbound

This paper cites Self-Organizing Graph Reasoning Evolves into a Critical State for Continuous Discovery Through Structural-Semantic Dynamics.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles Self-Organizing Graph Reasoning Evolves into a Critical State for Continuous Discovery Through Structural-Semantic Dynamics

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:40.989836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4995349-87e1-4cce-9d57-e705acdd7880 · outbound

This paper cites PRefLexOR: Preference-based Recursive Language Modeling for Exploratory Optimization of Reasoning and Agentic Thinking.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles PRefLexOR: Preference-based Recursive Language Modeling for Exploratory Optimization of Reasoning and Agentic Thinking

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:40.993899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a43f4042-0295-4c04-a7fa-0407cb901b0f · outbound

This paper cites In-situ graph reasoning and knowledge expansion using Graph-PReFLexOR.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles In-situ graph reasoning and knowledge expansion using Graph-PReFLexOR

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:40.998196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6900691-3624-4d17-bfa7-8631bd5b841e · outbound

This paper cites an unresolved cited work.

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

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:09:41.858283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 332c9410-31a9-4687-b993-85a990bf26f1 · outbound

This paper cites & Bradley, P.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles & Bradley, P

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:09:41.847468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 76ef1783-9561-4983-9796-79aff18089a1 · outbound

This paper cites & Buehler, M.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles & Buehler, M

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:09:41.837126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b4147fd8-094c-4ba7-a24f-0eb7c1f94cb8 · outbound

This paper cites & Buehler, M.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles & Buehler, M

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:09:41.825325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation df375921-8db5-40bd-acbb-7549dc32fecf · outbound

This paper cites an unresolved cited work.

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

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:09:41.815140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e6570308-2bde-496e-947a-1bbb6657dff7 · outbound

This paper cites De novo protein design—from new structures to programmable functions.Cell 187, 526–544 (2024).

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles De novo protein design—from new structures to programmable functions.Cell 187, 526–544 (2024)

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:09:41.802188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1574e50a-2084-47c8-bdc5-caf1d3f1cabe · outbound

This paper cites Highly accurate protein structure prediction with AlphaFold.Nature 596, 583–589 (2021).

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles Highly accurate protein structure prediction with AlphaFold.Nature 596, 583–589 (2021)

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:09:41.792083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a9919e7d-3c66-4621-a699-4c7df1f691a1 · outbound

This paper cites an unresolved cited work.

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

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:09:41.780849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 96ef5518-bc47-43d2-967c-5abd64e3039c · outbound

This paper cites an unresolved cited work.

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

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:09:41.770523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0a8e2f52-2c3e-4f7f-8646-0a63f4bab749 · outbound

This paper cites an unresolved cited work.

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

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:09:41.759875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c1359810-4059-4d50-8c45-1097b419b5bb · outbound

This paper cites an unresolved cited work.

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

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:41.038399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38f7004f-a11c-40d8-9f10-c527b768d5fc · outbound

This paper cites GPT-4 Technical Report.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles GPT-4 Technical Report

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:41.041715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95c169ee-b1f6-4c83-8c23-c47947b5cd29 · outbound

This paper cites GPT-4o System Card.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles GPT-4o System Card

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:41.045306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d3611cc-17a6-4f64-b680-da6f342d2fb4 · outbound

This paper cites OpenAI o1 System Card.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles OpenAI o1 System Card

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:41.048861Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55925088-bc9e-4f16-8b1e-0a5082522a81 · outbound

This paper cites Sparks of Artificial General Intelligence: Early experiments with GPT-4.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles Sparks of Artificial General Intelligence: Early experiments with GPT-4

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:41.053359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2e7474a-8d44-4bb4-8fa1-7809aae4bd53 · outbound

This paper cites Attention is all you need.Advances in neural information processing systems30 (2017).

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles Attention is all you need.Advances in neural information processing systems30 (2017)

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:09:41.741184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 92035011-d4f7-4ea6-9cdb-c2e30e39182e · outbound

This paper cites Emergent Abilities of Large Language Models.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles Emergent Abilities of Large Language Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:41.060380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c30171b-a7e0-410d-84c5-087cf456533b · outbound

This paper cites Towards Reasoning in Large Language Models: A Survey.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles Towards Reasoning in Large Language Models: A Survey

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:41.063989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8e113da-db77-4b2e-a404-deea6dae2fe6 · outbound

This paper cites an unresolved cited work.

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

Reference 31

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:09:41.730339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d47f4ed5-bf4a-4013-813b-0e54e9704867 · outbound

This paper cites Large Language Model based Multi-Agents: A Survey of Progress and Challenges.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles Large Language Model based Multi-Agents: A Survey of Progress and Challenges

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:41.071191Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f1e1ded0-e34e-4595-8856-117825b88c6b · outbound

This paper cites & Buehler, M.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles & Buehler, M

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:41.074724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c70c325e-338c-4956-a950-32ec13936ecc · outbound

This paper cites & Buehler, M.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles & Buehler, M

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:09:41.714152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 89ca37d6-2f94-47a0-af2d-e21b6dfb25f5 · outbound

This paper cites M., Schwaller, P., Ortega-Guerrero, A.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles M., Schwaller, P., Ortega-Guerrero, A

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:09:41.703190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 25b574d7-ff0e-451f-b42a-6b30c262f7a0 · outbound

This paper cites an unresolved cited work.

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

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:09:41.692033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6c7269bb-6a58-4228-bad0-7023d0050dc7 · outbound

This paper cites & Buehler, M.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles & Buehler, M

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:41.090083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd3279a5-d2c4-4f43-a79d-225b4c06948f · outbound

This paper cites A., MacKnight, R., Kline, B.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles A., MacKnight, R., Kline, B

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:41.093438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a31831d-83af-412a-9dc5-d149b225d279 · outbound

This paper cites Bran, A.et al.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles Bran, A.et al

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:41.096931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af2be385-bb53-4141-8d2b-66c18157869c · outbound

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

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:41.101607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e331a08-0c0a-44c2-8604-88ccd4be6575 · outbound

This paper cites Agent Laboratory: Using LLM Agents as Research Assistants.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles Agent Laboratory: Using LLM Agents as Research Assistants

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:41.105344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fcfd3698-2b0e-457d-99ac-f17e24c39361 · outbound

This paper cites Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:41.108764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 956b026b-8c2c-4a8a-8a94-d14c8f1ef266 · outbound

This paper cites ChemCrow: Augmenting large-language models with chemistry tools.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles ChemCrow: Augmenting large-language models with chemistry tools

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:41.112743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05dfb3a6-2519-436c-a76a-d9fc00f6e3b2 · outbound

This paper cites Towards an AI co-scientist.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles Towards an AI co-scientist

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:41.116869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ad8f968-f572-4950-9f46-c31bfb2e82b9 · outbound

This paper cites Autonomous mobile robots for exploratory synthetic chemistry.Nature 1–8 (2024).

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles Autonomous mobile robots for exploratory synthetic chemistry.Nature 1–8 (2024)

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:09:41.662137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7615c336-8805-4888-b020-c7cd6f9f5064 · outbound

This paper cites an unresolved cited work.

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

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-16T10:09:41.124103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 082563ee-9c9e-4d15-ad4a-0bb8526c48e4 · outbound

This paper cites an unresolved cited work.

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

Reference 47

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:09:41.644563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 594ed733-e143-431b-9a1f-75eb54fcf3cb · outbound

This paper cites High-resolution de novo structure prediction from primary sequence.BioRxiv 2022–07 (2022).

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles High-resolution de novo structure prediction from primary sequence.BioRxiv 2022–07 (2022)

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:09:41.634888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d83fb9ef-46b9-4537-ac23-d65c51d0e94f · outbound

This paper cites & Sander, C.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles & Sander, C

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:09:41.623357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9d55bd2e-3640-4e0a-95a2-3ce88cfb53f5 · outbound

This paper cites an unresolved cited work.

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

Reference 50

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:09:41.613240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 84799ce7-9919-4cac-9150-398358f09dc4 · outbound

This paper cites an unresolved cited work.

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

Reference 51

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:09:41.602614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e0548af2-fde0-4a39-b5fa-44bd96aa0be1 · outbound

This paper cites an unresolved cited work.

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

Reference 52

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:09:41.593105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2a3c5f55-5ea8-492a-ae7e-79ab53a04780 · outbound

This paper cites H": "30",.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles H": "30",

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:09:41.581818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ceafc526-dc09-4acc-ae6a-1545262600e7 · outbound

This paper cites an unresolved cited work.

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

Reference 54

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:09:41.570126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 13e2cb2b-f8ff-4232-8ec1-36320361ff3a · outbound

This paper cites an unresolved cited work.

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

Reference 55

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:09:41.558142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9fd3f57a-3149-459d-8703-9bad2738c791 · outbound

This paper cites an unresolved cited work.

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

Reference 56

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:09:41.547091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8923bca7-0f19-42cf-9da5-b44467d2b4a0 · outbound

This paper cites an unresolved cited work.

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

Reference 57

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:09:41.535164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d78592ec-f3f6-4420-bdcd-42b94a704e3b · outbound

This paper cites an unresolved cited work.

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

Reference 58

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:09:41.523540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 24cb1399-50e2-4117-aaae-ab255ce14db3 · outbound

This paper cites Groups with insuﬃcient samples were targeted for additional design attempts.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles Groups with insuﬃcient samples were targeted for additional design attempts

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:09:41.511455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1dd0dcd4-48ae-44f8-b05b-dbd6ac9813ee · outbound

This paper cites an unresolved cited work.

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

Reference 60

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:09:41.498926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 42e72b41-d369-4f2a-882a-94507420b3f2 · outbound

This paper cites an unresolved cited work.

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

Reference 61

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:09:41.488325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3059d43a-49ef-4e1e-a88c-a0dcf8ce2fe8 · outbound

This paper cites an unresolved cited work.

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

Reference 62

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:09:41.475613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation eb26024e-74f9-4d7e-b395-cc535e040d93 · outbound

This paper cites After each round, the sample counts were recomputed, and only deﬁcient groups were targeted in subsequent rounds.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles After each round, the sample counts were recomputed, and only deﬁcient groups were targeted in subsequent rounds

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:09:41.464259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a5db5c83-1bd2-4d5a-b3b7-3091b2eb2dfd · outbound

This paper cites Across the entire 40–120 amino acid range, the median RMSD for β-rich proteins remains tightly clustered between 2.59 and 2.86 ˚A, with IQRs consistently below 1 .7 ˚A.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles Across the entire 40–120 amino acid range, the median RMSD for β-rich proteins remains tightly clustered between 2.59 and 2.86 ˚A, with IQRs consistently below 1 .7 ˚A

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:09:41.452195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5653ace7-aaec-438c-95b4-a2b0091e86c5 · outbound

This paper cites The median RMSD for α designs increases from 2 .86 ˚A at 40 aa to a peak of 4 .00 ˚A at 60 aa, then declines to 2.44–2.80 ˚A at 100–120 aa.

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles The median RMSD for α designs increases from 2 .86 ˚A at 40 aa to a peak of 4 .00 ˚A at 60 aa, then declines to 2.44–2.80 ˚A at 100–120 aa

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:09:41.439627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 28a1f335-5aff-4a1a-8557-8547b4f7b80b · outbound

This paper cites Frustration Zone.

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

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:09:41.427342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

Observation fa3c66c4-c51e-41b1-8a4a-2c8358401af4 · inbound

El Agente: An Autonomous Agent for Quantum Chemistry cites this paper.

El Agente: An Autonomous Agent for Quantum Chemistry Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-16T00:54:43.202074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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.