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Paper Citation Record · LEDGER

MolecularGPT: Open Large Language Model (LLM) for Few-Shot Molecular Property Prediction

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2406.12950.

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

pith.paper-citation-record.v1
2406.12950 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 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 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:26:42.025148Z

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

12
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 233b0267-7111-4453-985a-8fdff864e4d2 · inbound

Retrieval-Augmented Generation with Graphs (GraphRAG) cites this paper.

Retrieval-Augmented Generation with Graphs (GraphRAG) MolecularGPT: Open Large Language Model (LLM) for Few-Shot Molecular Property Prediction

Reference 265

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T04:33:39.726939Z

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.

source=pdf_text observed=2026-05-18T04:33:39.076517Z digest=sha256:783891f82735a860e2799ad6a19aaa353aad1cab92d512bf7c99121697786a0f

Observation 3c7fa607-fb1b-4025-aa83-f34b4fb45737 · inbound

MLaGA: Multimodal Large Language and Graph Assistant cites this paper.

MLaGA: Multimodal Large Language and Graph Assistant MolecularGPT: Open Large Language Model (LLM) for Few-Shot Molecular Property Prediction

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T11:26:42.025148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:26:42.025148Z digest=sha256:824d3416d9ccea8a132ad0dbc77b7cccea29a981687ee6299893a4d078dbf45e

Observation cfb5522a-3c62-47b4-8832-92cf9181fb89 · inbound

TrustGLM: Evaluating the Robustness of GraphLLMs Against Prompt, Text, and Structure Attacks cites this paper.

TrustGLM: Evaluating the Robustness of GraphLLMs Against Prompt, Text, and Structure Attacks MolecularGPT: Open Large Language Model (LLM) for Few-Shot Molecular Property Prediction

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T04:06:59.977288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:06:59.977288Z digest=sha256:86afdaf99e3b2cfb536b9b2e8ae56c7832fc43da5859d1dda1ce3d2ec894c712

Observation 4840c676-ad96-4253-9269-052f00f9bd06 · inbound

SLASH the Sink: Sharpening Structural Attention Inside LLMs cites this paper.

SLASH the Sink: Sharpening Structural Attention Inside LLMs MolecularGPT: Open Large Language Model (LLM) for Few-Shot Molecular Property Prediction

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-12T05:56:25.026189Z

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.

source=arxiv_source observed=2026-05-12T04:48:27.666360Z digest=sha256:4889e540a8e78b97b4b0e90f5406a4d93128b437e0ba48cde90234a2361b92a7

Observation c771095a-ae54-4f2b-8eeb-efd6f1c068eb · inbound

SLASH the Sink: Sharpening Structural Attention Inside LLMs cites this paper.

SLASH the Sink: Sharpening Structural Attention Inside LLMs MolecularGPT: Open Large Language Model (LLM) for Few-Shot Molecular Property Prediction

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-13T03:32:12.344613Z

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.

source=arxiv_source observed=2026-05-13T03:29:37.732728Z digest=sha256:4370b7aff1fa0abe6f00cf580dc740b806912035a4f552f16a97b36fcad02db4

Observation d26e4510-56d5-4045-aec9-7e41de22fe7a · inbound

SLASH the Sink: Sharpening Structural Attention Inside LLMs cites this paper.

SLASH the Sink: Sharpening Structural Attention Inside LLMs MolecularGPT: Open Large Language Model (LLM) for Few-Shot Molecular Property Prediction

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-20T22:23:48.045367Z

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.

source=arxiv_source observed=2026-05-20T22:20:06.307690Z digest=sha256:4e1195954457a7944a0fc2c0bb201914a8fe6a60cb3647c6e5d1aa94509d8e9c

Observation a519e517-9c4a-4d4d-9d3f-fcd17ddf5074 · inbound

From Text to Discovery: How Large Language Models Are Reshaping Research Across Scientific and Humanistic Disciplines cites this paper.

From Text to Discovery: How Large Language Models Are Reshaping Research Across Scientific and Humanistic Disciplines MolecularGPT: Open Large Language Model (LLM) for Few-Shot Molecular Property Prediction

Reference 96

Resolution
verified exact
arxiv_id, observed 2026-06-27T17:31:07.347013Z

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.

source=pdf_text observed=2026-06-27T17:22:30.784806Z digest=sha256:226a32f2466832a86c62ea12403da8dfe10e7ee3d11bf9a63565097a6fc1fd22

Observation 9107baac-ba6b-4739-9464-7c26bda5461b · inbound

From Text to Discovery: How Large Language Models Are Reshaping Research Across Scientific and Humanistic Disciplines cites this paper.

From Text to Discovery: How Large Language Models Are Reshaping Research Across Scientific and Humanistic Disciplines MolecularGPT: Open Large Language Model (LLM) for Few-Shot Molecular Property Prediction

Reference 96

Resolution
unresolved
no resolver link, observed 2026-08-02T12:03:33.399831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T12:03:33.399831Z digest=sha256:c98d3880f0f95855eabdc32b13fdfe937a598e2fb8a292172efb39fa50a13efd