Paper Citation Record · LEDGER

Conditional Chemical Language Models are Versatile Tools in Drug Discovery

As of 18 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2507.10273.

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

pith.paper-citation-record.v1
2507.10273 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:42:39.192935Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

23 of 23 outbound references displayed

verified exact4
verified fuzzy6
unresolved12
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 681a7d84-0c89-4ced-9cab-142bde65650d · outbound

This paper cites C., and Murray, C.

Conditional Chemical Language Models are Versatile Tools in Drug Discovery C., and Murray, C

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:41.511244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b6a65663-03ea-4a1e-82d1-32cb79bb723c · outbound

This paper cites A Unified Approach to Interpreting Model Predictions.

Conditional Chemical Language Models are Versatile Tools in Drug Discovery A Unified Approach to Interpreting Model Predictions

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T17:42:37.818109Z

Source-reported events for the cited work

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Observation aeed70d8-3bb5-4625-9428-6bccc0447fd5 · outbound

This paper cites SAFE setup for generative molecular design.

Conditional Chemical Language Models are Versatile Tools in Drug Discovery SAFE setup for generative molecular design

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:42:39.777297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation aca15bda-4963-4ab0-ad09-b16c7837a6bd · outbound

This paper cites Fame: fragment-based conditional molecular generation for phenotypic drug discovery.

Conditional Chemical Language Models are Versatile Tools in Drug Discovery Fame: fragment-based conditional molecular generation for phenotypic drug discovery

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:41.271530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fe3f3eaa-eba3-491c-b56e-904309ea1c94 · outbound

This paper cites Analyzing the Structure of Attention in a Transformer Language Model.

Conditional Chemical Language Models are Versatile Tools in Drug Discovery Analyzing the Structure of Attention in a Transformer Language Model

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T17:42:38.155414Z

Source-reported events for the cited work

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Observation 32c58f06-a298-429c-9dfd-335069d842ef · outbound

This paper cites doi: 10.1021/ACS.JMEDCHEM.3C02070/SUPPL FILE/JM3C02070 SI 001.PDF.

Conditional Chemical Language Models are Versatile Tools in Drug Discovery doi: 10.1021/ACS.JMEDCHEM.3C02070/SUPPL FILE/JM3C02070 SI 001.PDF

Reference 15

Resolution: verified exact; doi, observed 2026-08-06T17:42:39.398948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f556e30a-b6ac-4b69-832d-c3137a13b597 · outbound

This paper cites J., Blackshaw, J., Corbett, S., Veij, M.

Conditional Chemical Language Models are Versatile Tools in Drug Discovery J., Blackshaw, J., Corbett, S., Veij, M

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:41.065985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e3bc09dd-708f-4563-9190-00e4531f1202 · outbound

This paper cites Activity Cliff Prediction: Dataset and Benchmark.

Conditional Chemical Language Models are Versatile Tools in Drug Discovery Activity Cliff Prediction: Dataset and Benchmark

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T17:42:38.643908Z

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Observation a5267fe6-d972-4679-a265-784f6cb60c47 · outbound

This paper cites doi: 10.1093/NAR/GKAD751.

Conditional Chemical Language Models are Versatile Tools in Drug Discovery doi: 10.1093/NAR/GKAD751

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T17:42:38.716841Z

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Unavailable: canonical work link unavailable.

Observation 2aab153c-133a-46d8-8d16-704a8d10d1a5 · outbound

This paper cites For context- conditioned fine-tuning, we use MoAT-DB (see Appendix A.1).

Conditional Chemical Language Models are Versatile Tools in Drug Discovery For context- conditioned fine-tuning, we use MoAT-DB (see Appendix A.1)

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:40.877265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 19c7c58c-a842-43a5-8444-c011d74c114b · outbound

This paper cites A.2.1 Pre-training on Chemical Data The first training stage involves pre-training a generative model over SAFE strings with biological context tokens masked.

Conditional Chemical Language Models are Versatile Tools in Drug Discovery A.2.1 Pre-training on Chemical Data The first training stage involves pre-training a generative model over SAFE strings with biological context tokens masked

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:40.670064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ceab660a-6f2d-488b-8880-efd67cfaaf57 · outbound

This paper cites an unresolved cited work.

Conditional Chemical Language Models are Versatile Tools in Drug Discovery Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-06T17:42:40.464726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 15760986-07a5-439d-bdbd-baa2a287e76a · outbound

This paper cites With MoA.

Conditional Chemical Language Models are Versatile Tools in Drug Discovery With MoA

Reference 23

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T17:42:40.154652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3d4e3be8-8c55-4c0f-a2d0-74e4ed87d6d6 · outbound

This paper cites Explainability Techniques for Chemical Language Models.

Conditional Chemical Language Models are Versatile Tools in Drug Discovery Explainability Techniques for Chemical Language Models

Reference 2004

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:42:39.987669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 38f7b059-dff9-47e6-9350-9285868cefd4 · outbound

This paper cites In Figure 9, we illustrate a counterfactual exploration around Tofacitinib, a known Janus kinase (JAK) inhibitor.

Conditional Chemical Language Models are Versatile Tools in Drug Discovery In Figure 9, we illustrate a counterfactual exploration around Tofacitinib, a known Janus kinase (JAK) inhibitor

Reference 2010

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:40.339369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d3f33f26-db30-4072-9e7c-ecabaf2cebab · outbound

This paper cites doi: 10.1038/nrd3926-c1.

Conditional Chemical Language Models are Versatile Tools in Drug Discovery doi: 10.1038/nrd3926-c1

Reference 2013

Resolution: verified exact; doi, observed 2026-08-06T17:42:39.595610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cd9d904c-fc1f-4a90-bb3e-3dae4b6621c6 · outbound

This paper cites TxGemma: Efficient and Agentic LLMs for Therapeutics.

Conditional Chemical Language Models are Versatile Tools in Drug Discovery TxGemma: Efficient and Agentic LLMs for Therapeutics

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-06T17:42:38.215347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dff5f3fe-aa98-4cab-abeb-96e19b935019 · outbound

This paper cites doi: 10.1093/NAR/GKX1037.

Conditional Chemical Language Models are Versatile Tools in Drug Discovery doi: 10.1093/NAR/GKX1037

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-06T17:42:38.335597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4adacd9-ec18-47d1-9fc1-17e7fe2cb955 · outbound

This paper cites Drug Discovery with Dynamic Goal-aware Fragments.

Conditional Chemical Language Models are Versatile Tools in Drug Discovery Drug Discovery with Dynamic Goal-aware Fragments

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-06T17:42:37.547884Z

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Unavailable: canonical work link unavailable.

Observation ddf61d56-7407-46e3-97ef-f720ad9cd4d2 · outbound

This paper cites Inseq: An Interpretability Toolkit for Sequence Generation Models.

Conditional Chemical Language Models are Versatile Tools in Drug Discovery Inseq: An Interpretability Toolkit for Sequence Generation Models

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-06T17:42:38.060980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 204c7421-e694-4510-a516-3660e74c3ddf · outbound

This paper cites Sample Efficiency Matters: A Benchmark for Practical Molecular Optimization.

Conditional Chemical Language Models are Versatile Tools in Drug Discovery Sample Efficiency Matters: A Benchmark for Practical Molecular Optimization

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-06T17:42:37.181383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c08b441d-59b3-4f82-a237-aed652dd3000 · outbound

This paper cites GenMol: A Drug Discovery Generalist with Discrete Diffusion.

Conditional Chemical Language Models are Versatile Tools in Drug Discovery GenMol: A Drug Discovery Generalist with Discrete Diffusion

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-06T17:42:37.634115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation adb95d9c-b9c3-4c84-abfb-8f6a76aa1ee6 · outbound

This paper cites Generating 3D Molecules for Target Protein Binding.

Conditional Chemical Language Models are Versatile Tools in Drug Discovery Generating 3D Molecules for Target Protein Binding

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-06T17:42:37.726969Z

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Pith citing papers

No inbound Pith citation observations are available.