Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T17:42:39.192935Z
Paper Citation Record · LEDGER
As of 8 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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T17:42:39.192935Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
23 of 23 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 681a7d84-0c89-4ced-9cab-142bde65650d · outbound
Conditional Chemical Language Models are Versatile Tools in Drug Discovery C., and Murray, C
Reference 3
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.
Observation b6a65663-03ea-4a1e-82d1-32cb79bb723c · outbound
Conditional Chemical Language Models are Versatile Tools in Drug Discovery A Unified Approach to Interpreting Model Predictions
Reference 8
Source-reported events for the cited work
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Observation aeed70d8-3bb5-4625-9428-6bccc0447fd5 · outbound
Conditional Chemical Language Models are Versatile Tools in Drug Discovery SAFE setup for generative molecular design
Reference 9
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.
Observation aca15bda-4963-4ab0-ad09-b16c7837a6bd · outbound
Conditional Chemical Language Models are Versatile Tools in Drug Discovery Fame: fragment-based conditional molecular generation for phenotypic drug discovery
Reference 10
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.
Observation fe3f3eaa-eba3-491c-b56e-904309ea1c94 · outbound
Conditional Chemical Language Models are Versatile Tools in Drug Discovery Analyzing the Structure of Attention in a Transformer Language Model
Reference 12
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 32c58f06-a298-429c-9dfd-335069d842ef · outbound
Conditional Chemical Language Models are Versatile Tools in Drug Discovery doi: 10.1021/ACS.JMEDCHEM.3C02070/SUPPL FILE/JM3C02070 SI 001.PDF
Reference 15
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.
Observation f556e30a-b6ac-4b69-832d-c3137a13b597 · outbound
Conditional Chemical Language Models are Versatile Tools in Drug Discovery J., Blackshaw, J., Corbett, S., Veij, M
Reference 16
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.
Observation e3bc09dd-708f-4563-9190-00e4531f1202 · outbound
Conditional Chemical Language Models are Versatile Tools in Drug Discovery Activity Cliff Prediction: Dataset and Benchmark
Reference 17
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a5267fe6-d972-4679-a265-784f6cb60c47 · outbound
Conditional Chemical Language Models are Versatile Tools in Drug Discovery doi: 10.1093/NAR/GKAD751
Reference 18
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2aab153c-133a-46d8-8d16-704a8d10d1a5 · outbound
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
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.
Observation 19c7c58c-a842-43a5-8444-c011d74c114b · outbound
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
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.
Observation ceab660a-6f2d-488b-8880-efd67cfaaf57 · outbound
Conditional Chemical Language Models are Versatile Tools in Drug Discovery Unresolved cited work
Reference 21
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.
Observation 15760986-07a5-439d-bdbd-baa2a287e76a · outbound
Conditional Chemical Language Models are Versatile Tools in Drug Discovery With MoA
Reference 23
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.
Observation 3d4e3be8-8c55-4c0f-a2d0-74e4ed87d6d6 · outbound
Conditional Chemical Language Models are Versatile Tools in Drug Discovery Explainability Techniques for Chemical Language Models
Reference 2004
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.
Observation 38f7b059-dff9-47e6-9350-9285868cefd4 · outbound
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
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.
Observation d3f33f26-db30-4072-9e7c-ecabaf2cebab · outbound
Conditional Chemical Language Models are Versatile Tools in Drug Discovery doi: 10.1038/nrd3926-c1
Reference 2013
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.
Observation cd9d904c-fc1f-4a90-bb3e-3dae4b6621c6 · outbound
Conditional Chemical Language Models are Versatile Tools in Drug Discovery TxGemma: Efficient and Agentic LLMs for Therapeutics
Reference 2017
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dff5f3fe-aa98-4cab-abeb-96e19b935019 · outbound
Conditional Chemical Language Models are Versatile Tools in Drug Discovery doi: 10.1093/NAR/GKX1037
Reference 2018
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e4adacd9-ec18-47d1-9fc1-17e7fe2cb955 · outbound
Conditional Chemical Language Models are Versatile Tools in Drug Discovery Drug Discovery with Dynamic Goal-aware Fragments
Reference 2020
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ddf61d56-7407-46e3-97ef-f720ad9cd4d2 · outbound
Conditional Chemical Language Models are Versatile Tools in Drug Discovery Inseq: An Interpretability Toolkit for Sequence Generation Models
Reference 2021
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 204c7421-e694-4510-a516-3660e74c3ddf · outbound
Conditional Chemical Language Models are Versatile Tools in Drug Discovery Sample Efficiency Matters: A Benchmark for Practical Molecular Optimization
Reference 2022
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c08b441d-59b3-4f82-a237-aed652dd3000 · outbound
Conditional Chemical Language Models are Versatile Tools in Drug Discovery GenMol: A Drug Discovery Generalist with Discrete Diffusion
Reference 2023
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation adb95d9c-b9c3-4c84-abfb-8f6a76aa1ee6 · outbound
Conditional Chemical Language Models are Versatile Tools in Drug Discovery Generating 3D Molecules for Target Protein Binding
Reference 2024
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
No inbound Pith citation observations are available.