Paper Citation Record · LEDGER

What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2305.18365.

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

pith.paper-citation-record.v1
2305.18365 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T16:00:23.669441Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T00:40:51.487410Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
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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 dfeafab7-d72b-436c-92db-c32654602738 · inbound

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

Large Language Model based Multi-Agents: A Survey of Progress and Challenges What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks

Reference 21

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T06:58:55.284078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 390abceb-9afd-42e9-aa47-1b552688e341 · inbound

Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry cites this paper.

Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks

Reference 208

Resolution: unresolved; no resolver link, observed 2026-08-12T16:00:23.669441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49abe2a6-c0e6-408c-b880-3ff61518f8f6 · inbound

M$^{3}$-20M: A Large-Scale Multi-Modal Molecule Dataset for AI-driven Drug Design and Discovery cites this paper.

M$^{3}$-20M: A Large-Scale Multi-Modal Molecule Dataset for AI-driven Drug Design and Discovery What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T20:23:44.512969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ddd54f2d-b16d-4d98-8853-18671dd89a5d · inbound

Decompose, Plan in Parallel, and Merge: A Novel Paradigm for Large Language Models based Planning with Multiple Constraints cites this paper.

Decompose, Plan in Parallel, and Merge: A Novel Paradigm for Large Language Models based Planning with Multiple Constraints What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T11:23:18.426703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c093cd24-2a2c-48c4-92a6-d3b3ee53b8f6 · inbound

Foundation Model Empowered Synesthesia of Machines (SoM): AI-native Intelligent Multi-Modal Sensing-Communication Integration cites this paper.

Foundation Model Empowered Synesthesia of Machines (SoM): AI-native Intelligent Multi-Modal Sensing-Communication Integration What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T05:33:51.609306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09365e61-30d5-4848-8b67-e85dec92e0f2 · inbound

NOCL: Node-Oriented Conceptualization LLM for Graph Tasks without Message Passing cites this paper.

NOCL: Node-Oriented Conceptualization LLM for Graph Tasks without Message Passing What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T13:24:01.598400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 532e4619-8257-4dc0-b5aa-368fdea44713 · inbound

Fine-Tuning and Prompt Engineering of LLMs, for the Creation of Multi-Agent AI for Addressing Sustainable Protein Production Challenges cites this paper.

Fine-Tuning and Prompt Engineering of LLMs, for the Creation of Multi-Agent AI for Addressing Sustainable Protein Production Challenges What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T22:49:21.044088Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49499938-8688-4888-8910-ed3dd461f591 · inbound

GenoMAS: A Multi-Agent Framework for Scientific Discovery via Code-Driven Gene Expression Analysis cites this paper.

GenoMAS: A Multi-Agent Framework for Scientific Discovery via Code-Driven Gene Expression Analysis What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-22T00:40:51.490510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0ea4da65-62fd-4789-862d-09316268795d · inbound

Do Larger Models Really Win in Drug Discovery? A Benchmark Assessment of Model Scaling in AI-Driven Molecular Property and Activity Prediction cites this paper.

Do Larger Models Really Win in Drug Discovery? A Benchmark Assessment of Model Scaling in AI-Driven Molecular Property and Activity Prediction What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:16:27.759990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cb50ad2d-dc51-461d-82e3-4daedb30d7ab · inbound

Do Larger Models Really Win in Drug Discovery? A Benchmark Assessment of Model Scaling in AI-Driven Molecular Property and Activity Prediction cites this paper.

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-19T17:42:42.033712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e8aa7470-3f9a-47d0-8426-904a77dcd646 · inbound

ToolMol: Evolutionary Agentic Framework for Multi-objective Drug Discovery cites this paper.

ToolMol: Evolutionary Agentic Framework for Multi-objective Drug Discovery What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:39:26.460442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 64164e8f-b797-42d8-97c9-6c20f973272c · inbound

ToolMol: Evolutionary Agentic Framework for Multi-objective Drug Discovery cites this paper.

ToolMol: Evolutionary Agentic Framework for Multi-objective Drug Discovery What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-15T04:55:03.175165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.