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Paper Citation Record · LEDGER

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows

As of 22 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2608.06961.

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

pith.paper-citation-record.v1
2608.06961 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:37:17.097124Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

32 of 32 outbound references displayed

  • verified exact6
  • verified fuzzy6
  • unresolved19
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

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Outbound references

Observation 016345c2-07da-4f0b-a4ef-0131e099fe2d · outbound

This paper cites Baker, Ian A.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows Baker, Ian A

Reference 1

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Observation 436ee965-5887-46a6-9af5-b341d2792443 · outbound

This paper cites An ai system to help scientists write expert-level empirical software.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows An ai system to help scientists write expert-level empirical software

Reference 2

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source=pdf_text observed=2026-08-10T17:37:16.974948Z digest=sha256:c6ea70c4f6d8beaf91a78f6779df9a6571bd28127390f80d3c73b15a964b40c0

Observation 3253aaaa-18cb-4771-a5a8-e66c8e437447 · outbound

This paper cites Bran, Sam Cox, Oliver Schilter, Carlo Baldassari, Andrew D.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows Bran, Sam Cox, Oliver Schilter, Carlo Baldassari, Andrew D

Reference 3

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source=pdf_text observed=2026-08-10T17:37:16.978957Z digest=sha256:7f88d3c371158027254901558ed1e7780aa3bc61a238c0489185caa8adf0e1a7

Observation 875ce8d5-5e5b-468c-8572-1d8afeea60f6 · outbound

This paper cites SynFlowNet: Design of Diverse and Novel Molecules with Synthesis Constraints.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows SynFlowNet: Design of Diverse and Novel Molecules with Synthesis Constraints

Reference 4

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no resolver link, observed 2026-08-10T17:37:16.983177Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-10T17:37:16.983177Z digest=sha256:62265d4fb3ea015e3e3f6e48e3ce369286c823ae8f57ab9050cf2ad457f13620

Observation c33bcf7f-8891-47c5-bcfa-396944502bba · outbound

This paper cites Macrocyclization of linear molecules by deep 12 learning to facilitate macrocyclic drug candidates discovery.Nature Communications, 14: 4552, 2023.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows Macrocyclization of linear molecules by deep 12 learning to facilitate macrocyclic drug candidates discovery.Nature Communications, 14: 4552, 2023

Reference 5

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verified exact
doi, observed 2026-08-10T17:37:17.267333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-10T17:37:16.988139Z digest=sha256:b9b03336af81a1b608b0d4a3952794f533a4749e3c77e7dc252f3d9e1049b525

Observation 4902ea56-30dd-4476-b755-360e6e2af474 · outbound

This paper cites Machine learning-aided generative molecular design.Nature Machine Intelligence, 6:589–604, 2024.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows Machine learning-aided generative molecular design.Nature Machine Intelligence, 6:589–604, 2024

Reference 6

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source=pdf_text observed=2026-08-10T17:37:16.992353Z digest=sha256:1b0c28f94ca8fb1fd61a8a612b19e1f2871b645bd5425993f28abf30e27883ca

Observation 5fab8849-9d56-4963-b73c-d1bef46ff7d7 · outbound

This paper cites Translation between molecules and natural language.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows Translation between molecules and natural language

Reference 7

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source=pdf_text observed=2026-08-10T17:37:16.996411Z digest=sha256:dddfd2d742d3cf4869c6fbbd09237a0f501110b31401920d97e276097f5a1e3d

Observation 4a46d21c-9e17-4088-bb27-bc44af859e02 · outbound

This paper cites Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models

Reference 8

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source=pdf_text observed=2026-08-10T17:37:17.000099Z digest=sha256:24e77a39fef371ce1a1d1fef9e698ede0d0ac8639371a946514de71f8e8df6ed

Observation 4f9a696b-844a-4168-936d-d6a3f8447b90 · outbound

This paper cites Generation of 3d molecules in pockets via language model.Nature Machine Intelligence, 6:62–73, 2024.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows Generation of 3d molecules in pockets via language model.Nature Machine Intelligence, 6:62–73, 2024

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-10T17:37:17.004131Z digest=sha256:ff2d8f071163cc22a40e415545683a119abee9ca9e296a48baa8bfd9a36c9669

Observation 51c05c3e-7686-4530-a1d5-b6fcb300517e · outbound

This paper cites TxAgent: An AI Agent for Therapeutic Reasoning Across a Universe of Tools.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows TxAgent: An AI Agent for Therapeutic Reasoning Across a Universe of Tools

Reference 10

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source=pdf_text observed=2026-08-10T17:37:17.007929Z digest=sha256:bce2d2d0e67d037a18f690317c7e00c5798e431e38cf0285220daabe7e8cbe08

Observation 6d35cf80-0751-49f4-b50c-bc68a3627099 · outbound

This paper cites Ghareeb et al.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows Ghareeb et al

Reference 11

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source=pdf_text observed=2026-08-10T17:37:17.011773Z digest=sha256:bc0c2447b9baf58d57a36305014b329f6c797799033f68f148ad07c1c7502ebc

Observation 1bcab8cc-4c3c-4143-aa85-bc5ad709a0cf · outbound

This paper cites Accelerating scientific discovery with co-scientist.Nature, 655:487– 496, 2026.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows Accelerating scientific discovery with co-scientist.Nature, 655:487– 496, 2026

Reference 12

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source=pdf_text observed=2026-08-10T17:37:17.015207Z digest=sha256:2950c3631830f871401cd9e2f78396601c14b74abd5f8c4600d450aa18762c81

Observation 9e0a1acc-e2af-4f69-b1d0-b5a9f6109286 · outbound

This paper cites Decompdiff: Diffusion models with decomposed priors for structure- based drug design.Proceedings of the 40th International Conference on Machine Learning, 202: 11827–11846, 2023.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows Decompdiff: Diffusion models with decomposed priors for structure- based drug design.Proceedings of the 40th International Conference on Machine Learning, 202: 11827–11846, 2023

Reference 13

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-10T17:37:17.018996Z digest=sha256:e2e1686a59097e9947705eca51601ef1efac0f7cd05c01b427ca2796d53a0bc1

Observation 07a68404-379f-4a44-bfff-5fd7dd2ddb84 · outbound

This paper cites Improving de novo molecular design with curriculum learning.Nature Machine Intelligence, 4:555–563, 2022.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows Improving de novo molecular design with curriculum learning.Nature Machine Intelligence, 4:555–563, 2022

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-10T17:37:17.022590Z digest=sha256:56402874d1938575405369e40358bb236a439bcb0e1fb2c59ed6f21d3ba22965

Observation 06e806e5-c1eb-46b2-a2f8-a0f1fed5cd00 · outbound

This paper cites SMDD-Bench: Can LLMs Solve Real-World Small Molecule Drug Design Tasks?.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows SMDD-Bench: Can LLMs Solve Real-World Small Molecule Drug Design Tasks?

Reference 15

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-10T17:37:17.026142Z digest=sha256:2498c33288139fca64e5b211d3e2e2d850674764b5534b3e96bfb9d35cf0606c

Observation 39903dea-c30c-4b40-95f3-2b9817daeae6 · outbound

This paper cites Exploring the macrocyclic chemical space for heuristic drug design with deep learning models.Communications Chemistry, 8:299, 2025.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows Exploring the macrocyclic chemical space for heuristic drug design with deep learning models.Communications Chemistry, 8:299, 2025

Reference 16

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 3213613a-4cf0-408d-b8c1-7e8a9b1b00a5 · outbound

This paper cites Carter, Xin Zhou, Matthew Wheeler, Jonathan A.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows Carter, Xin Zhou, Matthew Wheeler, Jonathan A

Reference 17

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Observation c8698d59-3969-45c2-a1b8-bc90eb50bc2c · outbound

This paper cites RGFN: Synthesizable Molecular Generation Using GFlowNets.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows RGFN: Synthesizable Molecular Generation Using GFlowNets

Reference 18

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local_arxiv, observed 2026-08-10T17:37:17.203691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-10T17:37:17.037152Z digest=sha256:fd44fbce4ae3072a3ec7c9ee78b5306fc49ac189b21914dde63efc8a2ac0c04a

Observation c9779922-6a35-4ac4-92b8-052a75cffd58 · outbound

This paper cites DrugAgent: Automating AI-aided Drug Discovery Programming through LLM Multi-Agent Collaboration.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows DrugAgent: Automating AI-aided Drug Discovery Programming through LLM Multi-Agent Collaboration

Reference 19

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Observation 63a61bb1-800e-4814-a916-dddda73a74f0 · outbound

This paper cites Loeffler, Jiazhen He, Alessandro Tibo, Jon Paul Janet, Anton Voronov, Lewis H.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows Loeffler, Jiazhen He, Alessandro Tibo, Jon Paul Janet, Anton Voronov, Lewis H

Reference 20

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Observation 048e21de-bb73-41c7-8639-ecaff356ace5 · outbound

This paper cites Hermes agent.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows Hermes agent

Reference 21

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-10T17:37:17.049253Z digest=sha256:63bac2e7473c35994ab5dc6542e3b287acdc26c759d060df9f68804b67642527

Observation 8fa14778-f176-4f64-8d26-748f1d2b5696 · outbound

This paper cites Aluru, Achuth Chandrasekhar, and Amir Barati Farimani.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows Aluru, Achuth Chandrasekhar, and Amir Barati Farimani

Reference 22

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raw_fallback, observed 2026-08-10T17:37:17.540398Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation f48f6552-6f13-4322-a92c-02db72f39993 · outbound

This paper cites Addendum to openai o3 and o4-mini system card: Codex.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows Addendum to openai o3 and o4-mini system card: Codex

Reference 23

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 1750400a-b5a5-4f12-bfdb-5e2fc7d3d6c7 · outbound

This paper cites Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets

Reference 24

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Observation 1ca3b649-1269-469c-9962-7ef855ad999f · outbound

This paper cites Blum, and Lars Ruddigkeit.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows Blum, and Lars Ruddigkeit

Reference 25

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Observation b57ccfed-923b-4424-a297-fec2600ebeb7 · outbound

This paper cites Computer-based de novo design of drug-like molecules.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows Computer-based de novo design of drug-like molecules

Reference 26

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Observation ca53c23a-4701-4d8c-89e5-68e5e5bef008 · outbound

This paper cites an unresolved cited work.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows Unresolved cited work

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation f522d6a7-177b-47c0-9dbb-bb16ed394692 · outbound

This paper cites Diffdec: Structure-aware scaffold decoration with an end-to-end diffusion model.Journal of Chemical Information and Modeling, 14 64(7):2554–2564, 2024.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows Diffdec: Structure-aware scaffold decoration with an end-to-end diffusion model.Journal of Chemical Information and Modeling, 14 64(7):2554–2564, 2024

Reference 28

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Observation 5fdabc76-8ec8-424f-855f-7af4c4c58b04 · outbound

This paper cites Baker, Ziqi Chen, Xia Ning, and Huan Sun.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows Baker, Ziqi Chen, Xia Ning, and Huan Sun

Reference 29

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raw_fallback, observed 2026-08-10T17:37:17.516017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 66d384fc-afa0-4590-9044-510721dbc9ef · outbound

This paper cites MolClaw: An Autonomous Agent with Hierarchical Skills for Drug Molecule Evaluation, Screening, and Optimization.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows MolClaw: An Autonomous Agent with Hierarchical Skills for Drug Molecule Evaluation, Screening, and Optimization

Reference 31

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Observation 26f00b42-4941-4791-8382-b05acecc86d7 · outbound

This paper cites ChemLLM: A Chemical Large Language Model.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows ChemLLM: A Chemical Large Language Model

Reference 2024

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Observation 5c758455-e949-44d2-b855-e39ff12a0600 · outbound

This paper cites URLhttps://doi.org/10.1021/acs.jcim.5c02454.

CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows URLhttps://doi.org/10.1021/acs.jcim.5c02454

Reference 2026

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Pith citing papers

No inbound Pith citation observations are available.