Paper Citation Record · LEDGER

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search

As of 21 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 1 inbound Pith citation observation for arXiv:2507.07426.

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

pith.paper-citation-record.v1
2507.07426 v3

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:47:24.102376Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-22T11:47:11.730921Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T11:51:30.108826Z

Reference resolution

39 of 39 outbound references displayed

verified exact1
verified fuzzy24
unresolved14
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f0962929-6b1b-4b15-bf67-f93fbff6f378 · outbound

This paper cites Why is tanimoto index an appropriate choice for fingerprint-based similarity calculations? Journal of cheminformatics, 7:1–13, 2015.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Why is tanimoto index an appropriate choice for fingerprint-based similarity calculations? Journal of cheminformatics, 7:1–13, 2015

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:47:24.827113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3908b79e-e531-418b-8e22-68936d7c527d · outbound

This paper cites Monte-carlo tree search.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Monte-carlo tree search

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:47:24.813135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c8b78ffb-cb31-4a3f-bdd2-512c5f34b484 · outbound

This paper cites Csstep: Step-by-step exploration of the chemical space of drug molecules via multi- agent and multi-stage reinforcement learning.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Csstep: Step-by-step exploration of the chemical space of drug molecules via multi- agent and multi-stage reinforcement learning

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:47:24.797307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f9bf2a51-e8bd-4c9b-a7ef-3c4471b66f0e · outbound

This paper cites Improving retrieval- augmented generation through multi-agent reinforce- ment learning.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Improving retrieval- augmented generation through multi-agent reinforce- ment learning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T18:47:22.521481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d092c96-c0d3-4a09-9d73-f828b0993a63 · outbound

This paper cites Continuous upper confidence trees.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Continuous upper confidence trees

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:47:24.783231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 19f18fa9-7a6b-480d-a9a6-e59301ea19d4 · outbound

This paper cites MolCap-Arena: A Comprehensive Captioning Benchmark on Language-Enhanced Molecular Property Prediction.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search MolCap-Arena: A Comprehensive Captioning Benchmark on Language-Enhanced Molecular Property Prediction

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-06T18:47:24.400677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0c176391-1cbb-45de-a9cd-c0d300642805 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T18:47:23.022154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69fb506d-0b2d-44d6-8027-3bb1acb60981 · outbound

This paper cites Using autodock 4 and autodock vina with autodock- tools: a tutorial.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Using autodock 4 and autodock vina with autodock- tools: a tutorial

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:47:24.768125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ad20653e-fd09-4d2a-bd41-ab68276fd0f9 · outbound

This paper cites GPT-4o System Card.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search GPT-4o System Card

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T18:47:23.192621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3706d051-3292-4351-959a-a61533d1aaf1 · outbound

This paper cites Lost but not only in the middle: Positional bias in retrieval augmented generation.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Lost but not only in the middle: Positional bias in retrieval augmented generation

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:47:24.754586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d3146415-116e-4c17-92d5-78329ec49c39 · outbound

This paper cites Drugagent: Multi-agent large language model-based reasoning for drug-target interaction prediction.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Drugagent: Multi-agent large language model-based reasoning for drug-target interaction prediction

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:47:24.739894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 01200a28-ed1d-4bc9-8889-4e097fdcd3fd · outbound

This paper cites Drugbank 6.0: the drugbank knowledgebase for 2024.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Drugbank 6.0: the drugbank knowledgebase for 2024

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:47:24.726170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 33a4642e-62d8-4c83-a3cc-130215adfe14 · outbound

This paper cites Deepconv-dti: Prediction of drug-target interac- tions via deep learning with convolution on pro- tein sequences.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Deepconv-dti: Prediction of drug-target interac- tions via deep learning with convolution on pro- tein sequences

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:47:24.712095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7136ec56-0956-46fd-aa2f-6df165521848 · outbound

This paper cites Rag-enhanced collaborative llm agents for drug discovery.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Rag-enhanced collaborative llm agents for drug discovery

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T18:47:23.454837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd9de133-3dc5-4ad9-a24f-6f852fdc5521 · outbound

This paper cites Alpha-SQL: Zero-Shot Text-to-SQL using Monte Carlo Tree Search.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Alpha-SQL: Zero-Shot Text-to-SQL using Monte Carlo Tree Search

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T18:47:23.531898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c72e3b1-0291-447f-acbe-a1956d103839 · outbound

This paper cites Lost in the Middle: How Language Models Use Long Contexts.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Lost in the Middle: How Language Models Use Long Contexts

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T18:47:23.592502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3e42c21-afe9-4f86-a3ce-17fa814d2a59 · outbound

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

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search DrugAgent: Automating AI-aided Drug Discovery Programming through LLM Multi-Agent Collaboration

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T18:47:23.652762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00cd5b10-f30c-4791-bbbd-9f668479a221 · outbound

This paper cites Does RAG Really Perform Bad For Long-Context Processing?.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Does RAG Really Perform Bad For Long-Context Processing?

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T18:47:23.726816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7ecdba6-1b58-4987-a282-375c55ccb80d · outbound

This paper cites Toward Understanding Catastrophic Forgetting in Continual Learning.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Toward Understanding Catastrophic Forgetting in Continual Learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T18:47:23.796279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0bf8d226-0a86-4792-a1a6-aed99fa59411 · outbound

This paper cites Perceiver cpi: a nested cross- attention network for compound–protein interaction prediction.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Perceiver cpi: a nested cross- attention network for compound–protein interaction prediction

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T18:47:23.826994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ea0eb9e-3106-4a36-9db8-77d657bc7f9a · outbound

This paper cites Graphdta: predicting drug–target binding affin- ity with graph neural networks.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Graphdta: predicting drug–target binding affin- ity with graph neural networks

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:47:24.688197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cb62bb68-fe93-4c8c-8a82-b8d1e51b1ef6 · outbound

This paper cites Maximizing rag effi- ciency: A comparative analysis of rag methods.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Maximizing rag effi- ciency: A comparative analysis of rag methods

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:47:24.675051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 94599eb4-df69-4728-a07b-88ecfd5f3805 · outbound

This paper cites LLM Agent Swarm for Hypothesis-Driven Drug Discovery.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search LLM Agent Swarm for Hypothesis-Driven Drug Discovery

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T18:47:24.009118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b312ae56-f8a0-431b-b880-05f6dd968426 · outbound

This paper cites Pubchempy documentation.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Pubchempy documentation

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:47:24.661552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f33fc848-f564-4da6-8ae5-16a8fdc91c7a · outbound

This paper cites Making sense of large-scale kinase inhibitor bioactivity data sets: a comparative and in- tegrative analysis.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Making sense of large-scale kinase inhibitor bioactivity data sets: a comparative and in- tegrative analysis

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:47:24.648553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation abf819b5-2ae8-4014-aa3f-3015828cc610 · outbound

This paper cites Qwen2.5 Technical Report.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Qwen2.5 Technical Report

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T18:47:24.051170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3253868b-5971-4ff7-8e5e-5a04249353e3 · outbound

This paper cites Assessment of fine-tuned large language models for real-world chem- istry and material science applications.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Assessment of fine-tuned large language models for real-world chem- istry and material science applications

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:47:24.634897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d41e12a6-1ec4-4a3f-a8e2-993639b5ba60 · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T18:47:24.059340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45eceb13-076e-442a-91ec-d8161d705505 · outbound

This paper cites Drugrealign: a multisource prompt framework for drug repurposing based on large language models.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Drugrealign: a multisource prompt framework for drug repurposing based on large language models

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:47:24.621425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 728288c7-930a-4e09-b630-7513319900ba · outbound

This paper cites Pubmed 2.0.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Pubmed 2.0

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:47:24.608037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7c1946b3-50cf-431f-a99b-3c88f9a7333c · outbound

This paper cites mhmg-dti: A drug-target interaction prediction framework combining modified hierarchical molecular graphs and improved convolutional block attention module.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search mhmg-dti: A drug-target interaction prediction framework combining modified hierarchical molecular graphs and improved convolutional block attention module

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:47:24.594328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 23b0e57a-8137-494a-bfde-4f7e1c85a770 · outbound

This paper cites iresnetdm: An interpretable deep learning ap- proach for four types of dna methylation modification prediction.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search iresnetdm: An interpretable deep learning ap- proach for four types of dna methylation modification prediction

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:47:24.581128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 26f7ee45-f367-4c6a-8bd7-6f203040ee23 · outbound

This paper cites Drugassist: A large language model for molecule optimization.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Drugassist: A large language model for molecule optimization

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:47:24.566973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a2ddb3d7-3a4c-4c56-ab9b-7b9b9c1fc09f · outbound

This paper cites Using pymol as a platform for computational drug design.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Using pymol as a platform for computational drug design

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:47:24.551766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8d3f0ae5-c667-4259-bb11-2273a2add1b1 · outbound

This paper cites Rag2mol: Structure-based drug design based on retrieval augmented generation.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Rag2mol: Structure-based drug design based on retrieval augmented generation

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:47:24.538314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3801486a-b061-43f3-a779-1a68b1a93509 · outbound

This paper cites Fine-tuning large language models for chemical text mining.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Fine-tuning large language models for chemical text mining

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:47:24.524303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation acbbb012-1788-4fc0-b8db-cabab7fecedb · outbound

This paper cites Attentiondta: prediction of drug– target binding affinity using attention model.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Attentiondta: prediction of drug– target binding affinity using attention model

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:47:24.510130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ecba2531-29e4-4adb-8e82-72607bd2e715 · outbound

This paper cites Large language models for scientific discovery in molecular property prediction.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Large language models for scientific discovery in molecular property prediction

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:47:24.495833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2821061f-8bbb-4581-a6a9-dfda70e7a51e · outbound

This paper cites Large Language Models in Drug Discovery and Development: From Disease Mechanisms to Clinical Trials.

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search Large Language Models in Drug Discovery and Development: From Disease Mechanisms to Clinical Trials

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-06T18:47:24.102376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 5476ead0-db3f-4f5d-927e-777c8d4694f5 · inbound

Large Language Model Agent for User-friendly Chemical Process Simulations cites this paper.

Large Language Model Agent for User-friendly Chemical Process Simulations DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-22T11:51:30.111776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.