Paper Citation Record · LEDGER

System of Agentic AI for the Discovery of Metal-Organic Frameworks

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2504.14110.

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

pith.paper-citation-record.v1
2504.14110 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:16:54.267650Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T16:52:40.143775Z

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 d7e412eb-ceb3-4df9-a5ee-c2728d617c39 · inbound

MOFGPT: Generative Design of Metal-Organic Frameworks using Language Models cites this paper.

MOFGPT: Generative Design of Metal-Organic Frameworks using Language Models System of Agentic AI for the Discovery of Metal-Organic Frameworks

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T12:16:54.267650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 079a8687-5886-4c25-96b5-66a72d9b5050 · inbound

QUASAR: A Universal Autonomous System for Atomistic Simulation and a Benchmark of Its Capabilities cites this paper.

QUASAR: A Universal Autonomous System for Atomistic Simulation and a Benchmark of Its Capabilities System of Agentic AI for the Discovery of Metal-Organic Frameworks

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-16T09:50:49.283955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1b89a98f-cbad-4196-b408-24cdfaeaf87b · inbound

El Agente Quntur: A research collaborator agent for quantum chemistry cites this paper.

El Agente Quntur: A research collaborator agent for quantum chemistry System of Agentic AI for the Discovery of Metal-Organic Frameworks

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-05-16T06:50:42.391085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8b39df69-eb2d-4ed7-9fbd-0e03bcf45cba · inbound

LEGO-MOF: Equivariant Latent Manipulation for Editable, Generative, and Optimizable MOF Design cites this paper.

LEGO-MOF: Equivariant Latent Manipulation for Editable, Generative, and Optimizable MOF Design System of Agentic AI for the Discovery of Metal-Organic Frameworks

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-10T13:10:26.648459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation febf4801-43dd-423d-aaac-51c7e7a5d9af · inbound

CrystalReasoner: Reasoning and RL for Property-Conditioned Crystal Structure Generation cites this paper.

CrystalReasoner: Reasoning and RL for Property-Conditioned Crystal Structure Generation System of Agentic AI for the Discovery of Metal-Organic Frameworks

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-19T16:52:40.145496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 43e8d9d8-b5a6-45e7-844a-51dabd5d6d23 · inbound

Dyna-Mat: End-to-end benchmarking of foundation machine learning interatomic potentials in finite-temperature ensembles cites this paper.

Dyna-Mat: End-to-end benchmarking of foundation machine learning interatomic potentials in finite-temperature ensembles System of Agentic AI for the Discovery of Metal-Organic Frameworks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-12T02:31:03.871783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.