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Paper Citation Record · LEDGER

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework

As of 21 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 2 inbound Pith citation observations for arXiv:2411.15356.

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

pith.paper-citation-record.v1
2411.15356 v2

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:29:25.715009Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:21:12.098591Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T20:06:33.905997Z

Reference resolution

43 of 43 outbound references displayed

  • verified exact1
  • verified fuzzy29
  • unresolved13
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7648dd48-5600-47cd-8609-e75fde507652 · outbound

This paper cites Transforming Medical Regulations into Numbers: Vectorizing a Decade of Medical Device Regulatory Shifts in the USA, EU, and China.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Transforming Medical Regulations into Numbers: Vectorizing a Decade of Medical Device Regulatory Shifts in the USA, EU, and China

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-12T14:29:25.536206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3388928a-f2de-4c76-b043-143e236f099f · outbound

This paper cites How does medical device regulation perform in the united states and the european union? a systematic review,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework How does medical device regulation perform in the united states and the european union? a systematic review,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:29:26.314418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.541211Z digest=sha256:824c5d88f544ef3725491e380b1c31dc9f8a5b7f0da5669163e61230081cfa39

Observation dddb6a0b-eafd-4044-ba06-88c03c448ec0 · outbound

This paper cites Evaluation of large language models for the classification of medical device software,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Evaluation of large language models for the classification of medical device software,

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-12T14:29:26.301762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.545397Z digest=sha256:20d0207156defbf51aad8b7383836ca446b4cf48635a0a72730453ad7d59fbf3

Observation d8c5514a-7eab-4adf-8130-93b377a7c536 · outbound

This paper cites Perspective: Complexity theory and organization science,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Perspective: Complexity theory and organization science,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:29:26.287592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.549519Z digest=sha256:fff33c4fe43855f8e5aee9c57f8cb818d881f0f5b64fe62ae6bb4b282eecd29e

Observation ba0191d8-e993-4ce3-96de-a3a5abd2913c · outbound

This paper cites Business dynamics: Systems thinking and modeling for a complex world,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Business dynamics: Systems thinking and modeling for a complex world,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:29:26.274212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.553599Z digest=sha256:a68691db09d91fec07a147e291896c4211fbe21b23483dcc1020f673102567e4

Observation 97b2d635-a1e1-461b-b512-fa7d8876e438 · outbound

This paper cites an unresolved cited work.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:29:26.261302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.557747Z digest=sha256:a442d35a34cee0e4b3d32f322e1b4a3e854be4d680d44739a2efc55828f59263

Observation 7fe91b08-747f-444d-afc1-ac9ee6883f95 · outbound

This paper cites How to do agent-based simulations in the future: From modeling social mechanisms to emergent phenomena and interactive systems design,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework How to do agent-based simulations in the future: From modeling social mechanisms to emergent phenomena and interactive systems design,

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-12T14:29:26.248993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.562225Z digest=sha256:eab310dd6dc1a27bcd9057d3ceabf91fbe178598d3d594462a5d3ad969cafe3a

Observation 7535b4a2-779c-4f7e-980b-7413b61519eb · outbound

This paper cites Navigating the regulatory pathway for medical devices—a conversation with the fda, clinicians, researchers, and industry experts,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Navigating the regulatory pathway for medical devices—a conversation with the fda, clinicians, researchers, and industry experts,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:29:26.235998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.566183Z digest=sha256:56a63bed8043f181b8c74a71c647451ba4844f8e3836c1d3b10f87160bb109aa

Observation 9ffd22a6-0bc8-41d8-bfbb-1f78c17ea516 · outbound

This paper cites Wooldridge, An introduction to multiagent systems.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Wooldridge, An introduction to multiagent systems

Reference 9

Resolution
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raw_fallback, observed 2026-08-12T14:29:26.222555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.570391Z digest=sha256:27e9269a345a5376a8c35a015508d953668753d9eb783f4557b94be49ca4873a

Observation ae9d9c4f-5f8a-40da-939d-4c9c6b688447 · outbound

This paper cites Multi- agent systems for the simulation of land-use and land-cover change: a review,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Multi- agent systems for the simulation of land-use and land-cover change: a review,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:29:26.207724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.574193Z digest=sha256:9b51474fbf48d5961d8b435d8b05c0bb6bb6c644766a66af57d3520f799e7da4

Observation ce52d78c-5cad-4c44-b4b3-0596f6fa9b54 · outbound

This paper cites A Multi-Agent Rollout Approach for Highway Bottleneck Decongestion in Mixed Autonomy.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework A Multi-Agent Rollout Approach for Highway Bottleneck Decongestion in Mixed Autonomy

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-08-12T14:29:25.821849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.578122Z digest=sha256:95a22a5f9305d2246a839ccb6350609f19eb0bef1bbea1bb872ab127116fe698

Observation f3d9e552-2e75-4f66-9fa1-3c6e1f5e1248 · outbound

This paper cites Large Multimodal Agents: A Survey.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Large Multimodal Agents: A Survey

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-12T14:29:25.582460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:29:25.582460Z digest=sha256:9891632e022f0efdf6dcf1577b8ddb3e6b712b3aed56814cb23b562efb229e0b

Observation b7a9b01e-7d76-40eb-83f7-d1738344d9be · outbound

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

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Large Language Model based Multi-Agents: A Survey of Progress and Challenges

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-12T14:29:25.586673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:29:25.586673Z digest=sha256:1f733a01ad41f50b236cb1da6fa987ed8509d17a83557e545e603261fd0577b3

Observation 5b58577a-0b69-4a76-94d9-bc5d4ab89f58 · outbound

This paper cites Complexity theory: An overview with potential applications for the social sciences,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Complexity theory: An overview with potential applications for the social sciences,

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-12T14:29:26.192514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.591264Z digest=sha256:7b4f48c3a90b62effe6dc8f8e6613f482583821ca8f891d8d24dd0fe0f07fd7f

Observation a4f92c62-3fec-483d-8f34-2ac4f9e9de51 · outbound

This paper cites Everything you need to know about agent-based modelling and simulation,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Everything you need to know about agent-based modelling and simulation,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:29:26.178628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.595752Z digest=sha256:f860c03b2e66859811ca122071dc8dc5d80119dfa3f151278099ae84b6bbb712

Observation 30d389c3-21bb-4814-81c9-8c2c526ab332 · outbound

This paper cites Axelrod and M.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Axelrod and M

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:29:26.162789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.599889Z digest=sha256:16354f93240edae20daf0e09c3321beb5e07542b82309194758fb4b35dec8ac7

Observation ebd04420-51c7-4637-8017-300c65432d7b · outbound

This paper cites Causal mechanisms in the social sciences,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Causal mechanisms in the social sciences,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:29:26.149432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.603659Z digest=sha256:9993c56557fb8d8de081d304eaef15af7613012ddad13fcd064f36185a4dd8da

Observation ae6462f7-b00e-444d-b666-3ca84becff65 · outbound

This paper cites Reinforcement Learning from Human Feedback for Lane Changing of Autonomous Vehicles in Mixed Traffic.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Reinforcement Learning from Human Feedback for Lane Changing of Autonomous Vehicles in Mixed Traffic

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-12T14:29:25.607927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:29:25.607927Z digest=sha256:be1f53faf9aa20cecbfa7908a59ea4e25c6ce79b4606ce14f358956d9fa4cdcf

Observation 491365ed-ad42-47d0-906e-8fcf97374090 · outbound

This paper cites Editor’s commentary: regulatory science and the science of safety,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Editor’s commentary: regulatory science and the science of safety,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:29:26.135151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.613380Z digest=sha256:ee6ac3ee783a2044f2cf894e6e6a3cf07f7ed49750af634d0f898bf3ec491dcd

Observation ebdff0a5-b643-433c-bab3-0f25246b0b75 · outbound

This paper cites More than red tape: exploring complexity in medical device regulatory affairs,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework More than red tape: exploring complexity in medical device regulatory affairs,

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-12T14:29:25.617431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:29:25.617431Z digest=sha256:1a93851ee9511c5859bee1171a0627f82175f58417bb04a7bb2bcb04e75cfd0e

Observation a17714ae-3522-484f-93ec-d7f4aad26d1c · outbound

This paper cites Revolutionizing Pharma: Unveiling the AI and LLM Trends in the Pharmaceutical Industry.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Revolutionizing Pharma: Unveiling the AI and LLM Trends in the Pharmaceutical Industry

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-12T14:29:25.620806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:29:25.620806Z digest=sha256:3132ab63827b09d694fb46a53c47bd9d45f70c1da2a932d1636564a2b07223c9

Observation 5c7eed0d-ec04-4f7c-9afa-a0e07e05cb2d · outbound

This paper cites The use of readability metrics in legal text: A systematic literature review,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework The use of readability metrics in legal text: A systematic literature review,

Reference 22

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raw_fallback, observed 2026-08-12T14:29:26.114166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.624856Z digest=sha256:f96239411e9b2a1c6df8e9e9603d44336cb70201db2bbb8da5cc45436897bb38

Observation 036c2bef-6266-4f23-9eab-e51f2e7d99a0 · outbound

This paper cites Pbpk absorption modeling: establishing the in vitro–in vivo link—industry per- spective,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Pbpk absorption modeling: establishing the in vitro–in vivo link—industry per- spective,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:29:26.101647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.628180Z digest=sha256:2d41ef34053c4f2ef1e06aa3ab21ade1986e86fd9f34d2da5579d86e1e850eee

Observation 58d46835-f895-44a7-9ef6-6c2763310a07 · outbound

This paper cites Advancing regulatory science with computational modeling for medical devices at the fda’s office of science and engineering laboratories,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Advancing regulatory science with computational modeling for medical devices at the fda’s office of science and engineering laboratories,

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-12T14:29:26.088940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.631411Z digest=sha256:9476227649bf187424b05d3e6b3b3452bd1cad93f8b86a40fc6c94e90c053631

Observation 5d040e55-0804-4e08-90dc-9e9e30d2bdab · outbound

This paper cites Ispor, the fda, and the evolving regulatory science of medical device products,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Ispor, the fda, and the evolving regulatory science of medical device products,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:29:26.073950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.634479Z digest=sha256:602bf9e3e24ec628cf62cbce56fc0348959de7bad466fa0cc1e03758065e2af9

Observation 268808eb-e412-403d-9aa1-8e5267e4e5f0 · outbound

This paper cites Analytical chemistry in the regulatory science of medical devices,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Analytical chemistry in the regulatory science of medical devices,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:29:26.061812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.637717Z digest=sha256:592e2ebfe017f7c2bbf0492384df207477d7f17684ad97a1665d94b95e3fa17e

Observation 8ce74fb4-70f3-4b6e-b30b-68bf0f178db0 · outbound

This paper cites ICH Harmonised Tripartite Guideline: Quality Risk Management Q9,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework ICH Harmonised Tripartite Guideline: Quality Risk Management Q9,

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-12T14:29:26.050263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.641623Z digest=sha256:a43a90b8e4b76559e41217c0fc046cba8e64db781a45b0dd82fc1b8cc2e84286

Observation 73e29121-6586-44eb-a103-6aec1a3676f3 · outbound

This paper cites Guidance for industry: Q10 quality systems approach to pharmaceutical cgmp regulations,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Guidance for industry: Q10 quality systems approach to pharmaceutical cgmp regulations,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:29:26.037142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.646164Z digest=sha256:a35b3da2ffa4009ad979ef5df4f1fb4f122883df56132550ead8dfcda7455d8a

Observation 882c3c46-e543-403a-afa4-723641644c9e · outbound

This paper cites The risk-based approach under the new eu data protection regulation: a critical perspective,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework The risk-based approach under the new eu data protection regulation: a critical perspective,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:29:26.024966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.650240Z digest=sha256:58ace990dba659cfe249f537b14c755740f5d2a71efa4818fdd0b8ab78d94d8b

Observation 665764d0-b161-466f-a02a-87b1a5504019 · outbound

This paper cites Structured benefit-risk assessment across the product lifecycle: practical considerations,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Structured benefit-risk assessment across the product lifecycle: practical considerations,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:29:26.012600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.654471Z digest=sha256:a0effaf1a481bb81f58bfdc9218d41d9bd500855d4e768e7edf2367bba36d5d5

Observation 900020aa-5e80-48d2-83b5-a3868d1468f1 · outbound

This paper cites Foundations of cost-effectiveness analysis for health and medical practices,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Foundations of cost-effectiveness analysis for health and medical practices,

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-12T14:29:26.000268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.658496Z digest=sha256:772662c1308ad97cee84d317907d8659cfbb426027c4fe854c2d6a794b83c725

Observation 4ccd4d11-31c1-4d4f-a7fd-3221e115abba · outbound

This paper cites an unresolved cited work.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Unresolved cited work

Reference 32

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:29:25.988346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.662665Z digest=sha256:eb6b3c20dac7fa81fd3a4ad6071790ab858661181b9125d5b06bccbcfb5893f2

Observation 709ae7ff-04d3-4ff9-bb89-32a8d68d9ea7 · outbound

This paper cites Analysis of a stochastic model for coordinated platooning of heavy-duty vehicles,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Analysis of a stochastic model for coordinated platooning of heavy-duty vehicles,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:29:25.976077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.666599Z digest=sha256:0d1afdd6c4e2f4d38c9f4bcebc289cf48ce0fa4d417b58ac3c93cc63724680d4

Observation 95940202-0bff-420c-b178-24b2db3349b9 · outbound

This paper cites A dynamic model for gmp compliance and regulatory science,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework A dynamic model for gmp compliance and regulatory science,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:29:25.964294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.673240Z digest=sha256:d7cefb2fb81cc0dcf81e2c10c2e02a98d91a51457f7797c63b932c8e0114f5d1

Observation 3e2897cf-23d9-4411-84dd-919a8b7b9c46 · outbound

This paper cites Empowering biomedical discovery with ai agents,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Empowering biomedical discovery with ai agents,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:29:25.952486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.677755Z digest=sha256:4d6638e3fbe0a18a2a571b3b30700465fe32bc63836c963afa84c371e13dc680

Observation 95da299c-4210-4a39-bedc-156fb0f6d58b · outbound

This paper cites Structured benefit–risk evaluation for medicinal products: review of quantitative benefit–risk assessment findings in the literature,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Structured benefit–risk evaluation for medicinal products: review of quantitative benefit–risk assessment findings in the literature,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:29:25.941111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.682795Z digest=sha256:69bac573e1ca6dc4f91e48260ffa5584b3d18c6188ae7b5c1bc0f194cc7b35c2

Observation a9d765b4-8f44-4e54-a7ac-60ee8a96d5b2 · outbound

This paper cites Camel: Communicative agents for.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Camel: Communicative agents for

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:29:25.928402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.686780Z digest=sha256:ae6fe9cf16c0aa3540eb11bdb3c9daf19863ce2ea9d275f84ef4405d9824d7c8

Observation e759274c-9e7d-4a75-81d3-18d5375aefe9 · outbound

This paper cites an unresolved cited work.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:29:25.914212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.691387Z digest=sha256:6c7e79146fc1a70acb7c6b296ff13b9eb6428c44c150c46487d2f380fd765659

Observation da2dd96e-00bd-4b30-a46c-ce5d7ef10f98 · outbound

This paper cites an unresolved cited work.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Unresolved cited work

Reference 39

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:29:25.899245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.695851Z digest=sha256:571043708a1677afb1d47e7ec2abc36cc51839c7c1849ce8673901a2ceba4727

Observation 29aaea13-5aec-4841-9c20-9c49f8442d93 · outbound

This paper cites an unresolved cited work.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:29:25.885614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.699922Z digest=sha256:5176f0a26cfdc4b9e66a3d0b7ec3ef14f19d88ac2303732f68c458ab43a30d86

Observation 471c5d66-809b-4953-bdcb-6d50712967ef · outbound

This paper cites an unresolved cited work.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:29:25.873020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.705241Z digest=sha256:701cf69baf8feabfa48535d76760574451600a037875b79163241c703e6e2ba1

Observation d3025029-4eb8-4fa8-8d0c-54e6d1417179 · outbound

This paper cites an unresolved cited work.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:29:25.860990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.710613Z digest=sha256:db03209e0635c99f7228fb592c721a01cdadf7e6daf8eb81acea5a6a2cab8e23

Observation c3f1abbe-39ec-41e4-9cb3-353a70c444fb · outbound

This paper cites Least squares parameter estimation and multi-innovation least squares meth- ods for linear fitting problems from noisy data,.

Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework Least squares parameter estimation and multi-innovation least squares meth- ods for linear fitting problems from noisy data,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:29:25.848332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T14:29:25.715009Z digest=sha256:1e665f438d09b8941a10977207a4eeda6256e87081e9934b23235ae1e52d1d22

Pith citing papers

Observation ec0e52f2-9c72-4c14-9f3c-288ed5794132 · inbound

Standard Applicability Judgment and Cross-jurisdictional Reasoning: A RAG-based Framework for Medical Device Compliance cites this paper.

Standard Applicability Judgment and Cross-jurisdictional Reasoning: A RAG-based Framework for Medical Device Compliance Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T23:21:12.098591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:21:12.098591Z digest=sha256:1456bbdfd136ce0abf62a06aca4c887c4beb2a2533bcac49efe8668efdd28935

Observation 3899f339-b645-400d-b937-98aef1746582 · inbound

Compliance Management for Federated Data Processing cites this paper.

Compliance Management for Federated Data Processing Regulator-Manufacturer AI Agents Modeling: Mathematical Feedback-Driven Multi-Agent LLM Framework

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-15T20:06:33.909050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-15T20:05:06.786688Z digest=sha256:ffb856e9aac689c5518bf80f0af6e98ffcf8b940465bd0b4fcd7dde40ca14ab6