Paper Citation Record · LEDGER

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design

As of 18 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2510.23379.

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

pith.paper-citation-record.v1
2510.23379 v2

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T07:59:26.303247Z

measured 53 of 53 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

53 of 53 outbound references displayed

verified exact1
verified fuzzy0
unresolved51
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1707395b-905f-40d4-a66a-39cbc6f03086 · outbound

This paper cites Collins, Elizabeth Bourne, Gareth W.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Collins, Elizabeth Bourne, Gareth W

Reference 1

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Observation e329bcd9-aa54-4919-b5b3-34ba2253984e · outbound

This paper cites GPT-4 Technical Report.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design GPT-4 Technical Report

Reference 2

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Observation b644f466-2cef-4cfa-9bf6-ae031612463e · outbound

This paper cites Claude 3.5 sonnet: Frontier intelligence at 2× the speed.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Claude 3.5 sonnet: Frontier intelligence at 2× the speed

Reference 3

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Observation d0a7102b-203a-4544-ab83-cccc78d9efc6 · outbound

This paper cites Generalising Closed World Specialisation: A Chess End Game Application.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Generalising Closed World Specialisation: A Chess End Game Application

Reference 4

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Observation 77e660da-b271-43bc-a6e0-dc97487780c6 · outbound

This paper cites An open source chemical structure curation pipeline using rdkit.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design An open source chemical structure curation pipeline using rdkit

Reference 5

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Observation c767ef6c-c462-4c84-89bf-277c4e61b81d · outbound

This paper cites Neural-Symbolic Learning and Reasoning: A Survey and Interpretation.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Neural-Symbolic Learning and Reasoning: A Survey and Interpretation

Reference 6

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Observation 03c19d87-4b3d-4383-ba1e-c79e3006afee · outbound

This paper cites Generating novel leads for drug discovery using llms with logical feedback.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Generating novel leads for drug discovery using llms with logical feedback

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T07:59:20.639160Z

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Observation 193d9fe4-1def-4ea0-b4e8-e36befe757a2 · outbound

This paper cites Language Models are Few-Shot Learners.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Language Models are Few-Shot Learners

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T07:59:20.755323Z

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Observation c220ff61-085c-4567-8280-c9ec625ec359 · outbound

This paper cites Language models are few-shot learners.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Language models are few-shot learners

Reference 9

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Observation a16c3c05-c979-4c63-9528-e88ef03ab6b0 · outbound

This paper cites Empowering LLMs with Logical Reasoning: A Comprehensive Survey.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Empowering LLMs with Logical Reasoning: A Comprehensive Survey

Reference 10

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Observation 4b607aa7-3024-4121-a7e6-ac90cad9fabf · outbound

This paper cites Chervonyi, T.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Chervonyi, T

Reference 11

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Observation f8a03f4c-b4dd-4269-b2d4-6528f116c6d3 · outbound

This paper cites Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T07:59:21.322189Z

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Observation e0447da0-5c55-4cf7-a5eb-f4126cfb9c46 · outbound

This paper cites Muggleton.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Muggleton

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T07:59:21.465361Z

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Observation 33ad92ea-185f-40b7-8d53-136b94573be4 · outbound

This paper cites Using domain-knowledge to assist lead discovery in early-stage drug design.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Using domain-knowledge to assist lead discovery in early-stage drug design

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T07:59:21.620253Z

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Observation 3848de23-d5c7-4158-82e9-dd64174d34f0 · outbound

This paper cites d'Avila Garcez , L.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design d'Avila Garcez , L

Reference 15

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Observation 4c7fd6fa-a6ef-4a6c-bbc8-a84406cde4c5 · outbound

This paper cites ProbLog: A probabilistic Prolog and its application in link discovery.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design ProbLog: A probabilistic Prolog and its application in link discovery

Reference 16

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Observation 7e4006f2-a097-4dc8-9d75-baffc844369b · outbound

This paper cites Defining neurosymbolic AI.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Defining neurosymbolic AI

Reference 17

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Observation e3af5b5d-1610-4017-8ad6-147ddd23b032 · outbound

This paper cites The deeplog neurosymbolic machine, 2025.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design The deeplog neurosymbolic machine, 2025

Reference 18

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Observation dd773343-6277-4a61-bc79-b9a8eded9160 · outbound

This paper cites Doytchinova.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Doytchinova

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-04T07:59:22.163295Z

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Observation ceaa2bba-e7ba-42ce-a28c-ebc3dc561490 · outbound

This paper cites d’Avila Garcez and L.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design d’Avila Garcez and L

Reference 20

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Observation 5f392fd2-5cea-4580-99a8-6814ab766dc7 · outbound

This paper cites GPT2 Zinc 87M.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design GPT2 Zinc 87M

Reference 21

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Observation 0cb441f2-caf9-4f7c-ae9a-5d556609351a · outbound

This paper cites ChEMBL : a large-scale bioactivity database for drug discovery.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design ChEMBL : a large-scale bioactivity database for drug discovery

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-04T07:59:22.582648Z

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Observation 3e08ca13-86cd-47cb-b6e6-7b141de31b54 · outbound

This paper cites Data-Efficient Graph Grammar Learning for Molecular Generation.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Data-Efficient Graph Grammar Learning for Molecular Generation

Reference 23

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Observation bb73d6e4-9ca2-48ba-9116-0d74505bb319 · outbound

This paper cites Hilario, C.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Hilario, C

Reference 24

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Observation 7683ee69-0a62-4f9c-8aea-3aab85fd5377 · outbound

This paper cites An overview of strategies for neurosymbolic integration.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design An overview of strategies for neurosymbolic integration

Reference 25

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Observation 8473d7ca-4074-4c6f-a1c3-771ad91859cd · outbound

This paper cites Zinc20—a free ultralarge-scale chemical database for ligand discovery.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Zinc20—a free ultralarge-scale chemical database for ligand discovery

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-04T07:59:23.243722Z

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Observation bf7c15d5-bd5d-426a-8040-6c5353289373 · outbound

This paper cites Jacobson and Y.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Jacobson and Y

Reference 27

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Observation a62e8a65-2355-4e07-b340-37f8148c41bf · outbound

This paper cites Direct global optimization algorithm.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Direct global optimization algorithm

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-04T07:59:23.491721Z

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Observation 2eea7aaa-7b07-439f-90f2-cf22cdc7b0d7 · outbound

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Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Unresolved cited work

Reference 29

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Observation fa593a48-1c61-4808-b74f-5cfeddcb047f · outbound

This paper cites Kusner, B.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Kusner, B

Reference 30

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Observation e20800f9-331a-4c72-ad5b-67d1e9fb4e44 · outbound

This paper cites Basic Category Theory, volume 143 of Cambridge Studies in Advanced Mathematics.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Basic Category Theory, volume 143 of Cambridge Studies in Advanced Mathematics

Reference 31

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Observation 5f7f7f6b-0f4f-4f6d-a35e-e504cb807837 · outbound

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Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Unresolved cited work

Reference 32

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Observation 33485790-a4b1-4ab7-9b6f-315ad35cc7d9 · outbound

This paper cites Liang, D.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Liang, D

Reference 33

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Observation daf60a76-8a15-42b6-a487-af3369df5aae · outbound

This paper cites Molecular generative model based on conditional variational autoencoder for de novo molecular design.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Molecular generative model based on conditional variational autoencoder for de novo molecular design

Reference 34

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Observation c7d61166-235f-48be-b8d3-ce4c23d9b2ec · outbound

This paper cites Constrained graph variational autoencoders for molecule design.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Constrained graph variational autoencoders for molecule design

Reference 35

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Observation 2a357243-624d-4dc9-b273-bc7b2688bd04 · outbound

This paper cites Marra, S.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Marra, S

Reference 36

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Observation f034bf9a-8965-4b92-8e0d-e2df6df1577f · outbound

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Symbolic Neural Generation with Applications to Lead Discovery in Drug Design LIME : A system for learning relations

Reference 37

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Observation 24c76265-c63f-4604-b2d3-a639ecb3d3b5 · outbound

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Symbolic Neural Generation with Applications to Lead Discovery in Drug Design McCulloch and W

Reference 38

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Observation c7a9441c-9a18-48e7-9ff4-9042d7af61c7 · outbound

This paper cites A comparison of three methods for selecting values of input variables in the analysis of output from a computer code.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design A comparison of three methods for selecting values of input variables in the analysis of output from a computer code

Reference 39

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Observation b89d183f-62ba-480a-b0ed-4d3aa03f1667 · outbound

This paper cites Gnina 1.0: molecular docking with deep learning.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Gnina 1.0: molecular docking with deep learning

Reference 40

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Observation 4ab1e5ef-4dfe-46a4-af34-c43bf6a5b357 · outbound

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Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Learning from positive data

Reference 41

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Observation 3e35ce94-c648-4bc4-aacd-5b2d6696fbf9 · outbound

This paper cites Hypothesizing an algorithm from one example: the role of specificity.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Hypothesizing an algorithm from one example: the role of specificity

Reference 42

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Observation 44344d8b-29fc-429c-89cb-dbb7d247292c · outbound

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Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Unresolved cited work

Reference 43

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Observation 26e27020-b3f0-415b-b549-ca9071e1fcc6 · outbound

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Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Odense and A

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-04T07:59:25.295107Z

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Observation 6826c4f7-42d5-4893-b6ad-9b1fbd24b7d2 · outbound

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Symbolic Neural Generation with Applications to Lead Discovery in Drug Design LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers

Reference 45

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Observation 6146b01b-d163-4128-bff6-f98a96f67ad1 · outbound

This paper cites Large Language Models Meet Symbolic Provers for Logical Reasoning Evaluation.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Large Language Models Meet Symbolic Provers for Logical Reasoning Evaluation

Reference 46

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Observation 65871865-22b0-4902-9bba-d9a8128c60e2 · outbound

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Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Prism: a language for symbolic-statistical modeling

Reference 47

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Observation c6d31aef-7012-4361-90d2-c6b530c01350 · outbound

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Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Nested sampling

Reference 48

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Observation 7e1cfd7a-3ab9-4f71-b763-3ed0ff8f9ea8 · outbound

This paper cites Foundation Molecular Grammar: Multi-Modal Foundation Models Induce Interpretable Molecular Graph Languages.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Foundation Molecular Grammar: Multi-Modal Foundation Models Induce Interpretable Molecular Graph Languages

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-04T07:59:25.839028Z

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Observation 89bda269-7ecb-4190-9a4f-5550da515b60 · outbound

This paper cites The crystal structure of human dopamine -hydroxylase at 2.9 resolution.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design The crystal structure of human dopamine -hydroxylase at 2.9 resolution

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-04T07:59:25.957166Z

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Observation b40e0c14-d30e-4c90-b550-2e9aa50add32 · outbound

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Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Probabilistic embedding of knowledge graphs with box lattice measures

Reference 51

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Observation f2b7b8b6-dcc4-455b-9cc7-2d30a062e1fe · outbound

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Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Scientific Large Language Models: A Survey on Biological & Chemical Domains

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-04T07:59:26.182291Z

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Observation 81a6eed8-0425-4a7d-a3b3-736562e42b87 · outbound

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Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Unresolved cited work

Reference 53

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Pith citing papers

No inbound Pith citation observations are available.