Paper Citation Record · LEDGER

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents

As of 19 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2607.09195.

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

pith.paper-citation-record.v1
2607.09195 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-13T04:47:57.575546Z

measured 46 of 46 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.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

46 of 46 outbound references displayed

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Outbound references

Observation 8772dd0d-7198-44a0-b982-f4b30fdddb21 · outbound

This paper cites Towardsend-to-endautomationofairesearch.Nature,651(8107):914–919, 2026.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Towardsend-to-endautomationofairesearch.Nature,651(8107):914–919, 2026

Reference 1

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Observation e6ba0094-0a0b-48e4-baad-122ccff560a1 · outbound

This paper cites Towards an AI co-scientist.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Towards an AI co-scientist

Reference 2

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Observation 842b9155-f8c5-47a4-b344-8defde571cd4 · outbound

This paper cites Kosmos: An AI Scientist for Autonomous Discovery.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Kosmos: An AI Scientist for Autonomous Discovery

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-13T04:47:57.575546Z

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Observation c134605c-790f-48d4-be79-ed3272859286 · outbound

This paper cites Towards agentic intelligence for materials science.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Towards agentic intelligence for materials science

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-13T04:47:57.575546Z

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Observation a805fa02-f56a-43bc-9164-b37e10def821 · outbound

This paper cites React: Synergizing reasoning and acting in language models.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents React: Synergizing reasoning and acting in language models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-13T04:47:57.575546Z

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Observation fb6575c0-3934-42b0-9ede-6567a6120ee8 · outbound

This paper cites Introducing the Model Context Protocol.https://www.anthropic.com/news/ model-context-protocol, 2024.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Introducing the Model Context Protocol.https://www.anthropic.com/news/ model-context-protocol, 2024

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-13T04:47:57.575546Z

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Observation 6014a6be-dfcb-4f38-ab99-cd0f15cbae09 · outbound

This paper cites Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directions.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directions

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-13T04:47:57.575546Z

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Observation e496fbd0-9a36-4525-893d-ce76fb98b87f · outbound

This paper cites Voyager: An open-ended embodied agent with large language models.Transactions on Machine Learning Research (TMLR), 2024.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Voyager: An open-ended embodied agent with large language models.Transactions on Machine Learning Research (TMLR), 2024

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-13T04:47:57.575546Z

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Observation cabedfdf-e8a0-445e-9c88-fe7dc9901547 · outbound

This paper cites SoK: Agentic Skills -- Beyond Tool Use in LLM Agents.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents SoK: Agentic Skills -- Beyond Tool Use in LLM Agents

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-13T04:47:57.575546Z

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Observation 54619231-e67c-45cb-8e6a-203671e19b42 · outbound

This paper cites Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-13T04:47:57.575546Z

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Observation b9c4bce8-d54c-4a21-82d3-f743d50eac78 · outbound

This paper cites A survey of self-evolving agents: What, when, how, and where to evolve on the path to artificial super intelligence.Transactions on Machine Learning Research, 2026.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents A survey of self-evolving agents: What, when, how, and where to evolve on the path to artificial super intelligence.Transactions on Machine Learning Research, 2026

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-13T04:47:57.575546Z

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Observation 07274e73-a45c-45d7-a600-4ba299346a16 · outbound

This paper cites Adaplanner: Adaptive planning from feedback with language models.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Adaplanner: Adaptive planning from feedback with language models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-13T04:47:57.575546Z

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Observation 10331ea4-3f85-4847-90ea-e4ac02ec54b2 · outbound

This paper cites Reflexion: Language agents with verbal reinforcement learning.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Reflexion: Language agents with verbal reinforcement learning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-13T04:47:57.575546Z

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Observation c0ad3597-e855-4609-af88-347b4f1cc2c6 · outbound

This paper cites Toward Generalist Autonomous Research via Hypothesis-Tree Refinement.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Toward Generalist Autonomous Research via Hypothesis-Tree Refinement

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-13T04:47:57.575546Z

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Observation 3bc1a851-6094-41da-8b3c-cd6c98b0b501 · outbound

This paper cites Robin: A multi-agent system for automating scientific discovery.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Robin: A multi-agent system for automating scientific discovery

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-13T04:47:57.575546Z

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Observation 2fefe5d3-3687-472c-a51f-02a0007d43f9 · outbound

This paper cites Biodisco: Multi-agent hypothesis generation with dual-mode evidence, iterative feedback and temporal evaluation.arXiv preprint arXiv:2508.01285, 2025.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Biodisco: Multi-agent hypothesis generation with dual-mode evidence, iterative feedback and temporal evaluation.arXiv preprint arXiv:2508.01285, 2025

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-13T04:47:57.575546Z

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Observation 6f0dc820-4a54-4423-aae0-6606587ce839 · outbound

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

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Bran, Sam Cox, Oliver Schilter, Carlo Baldassari, Andrew D

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-13T04:47:57.575546Z

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Observation f8d6231a-d8c8-4f83-b242-a7dd2f3861a9 · outbound

This paper cites Boiko, Robert MacKnight, Ben Kline, and Gabe Gomes.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Boiko, Robert MacKnight, Ben Kline, and Gabe Gomes

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-13T04:47:57.575546Z

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Observation ba40fb13-7b44-4872-802c-1997097fefa6 · outbound

This paper cites Organa: A robotic assistant for automated chemistry experimentation and characterization.Matter, 8(2):101897, 2025.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Organa: A robotic assistant for automated chemistry experimentation and characterization.Matter, 8(2):101897, 2025

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-13T04:47:57.575546Z

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Observation 71d21728-3b95-4897-b7d5-dcd250cd5fa0 · outbound

This paper cites LLMatDesign: Autonomous Materials Discovery with Large Language Models.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents LLMatDesign: Autonomous Materials Discovery with Large Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-13T04:47:57.575546Z

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Observation 9d393947-e4dd-44ce-8ffa-50d310fa2b24 · outbound

This paper cites Accelerated inorganic materials design with generative ai agents.Cell Reports Physical Science, 6(12), 2025.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Accelerated inorganic materials design with generative ai agents.Cell Reports Physical Science, 6(12), 2025

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-13T04:47:57.575546Z

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Observation fdb1e145-9fb2-45f2-a898-d8f3ed047fba · outbound

This paper cites Crystalyse: a multi-tool agent for materials design.arXiv preprint arXiv:2512.00977, 2025.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Crystalyse: a multi-tool agent for materials design.arXiv preprint arXiv:2512.00977, 2025

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-13T04:47:57.575546Z

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Observation 7238e51a-a3cc-4906-bd0b-387310955982 · outbound

This paper cites Materealize: a multi-agent deliberation system for end-to-end material design and synthesis.arXiv preprint arXiv:2601.15743, 2026.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Materealize: a multi-agent deliberation system for end-to-end material design and synthesis.arXiv preprint arXiv:2601.15743, 2026

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-13T04:47:57.575546Z

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Observation a2e4ba77-5cff-433a-a82d-b3e608eb19a2 · outbound

This paper cites El agente: An autonomous agent for quantum chemistry.Matter, 8(7):102263, 2025.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents El agente: An autonomous agent for quantum chemistry.Matter, 8(7):102263, 2025

Reference 24

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Observation 98c407c6-35e3-4daf-b0a7-2f0c187b9f46 · outbound

This paper cites Pham, Aditya Tanikanti, and Murat Keçeli.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Pham, Aditya Tanikanti, and Murat Keçeli

Reference 25

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Observation ca4a3b73-69d0-43b2-8a61-50a25e71be3d · outbound

This paper cites Harnessing AtomisticSkills for Agentic Atomistic Research.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Harnessing AtomisticSkills for Agentic Atomistic Research

Reference 26

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Observation fe25d623-5e79-4fcf-9a02-2e2a822b1265 · outbound

This paper cites Agentic LLM Reasoning in a Self-Driving Laboratory for Air-Sensitive Lithium Halide Spinel Conductors.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Agentic LLM Reasoning in a Self-Driving Laboratory for Air-Sensitive Lithium Halide Spinel Conductors

Reference 27

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Observation 619d3e21-319f-49fc-a350-955d30f5d928 · outbound

This paper cites Performance of ai agents based on reasoning language models on ald process optimization tasks.arXiv preprint arXiv:2601.09980, 2026.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Performance of ai agents based on reasoning language models on ald process optimization tasks.arXiv preprint arXiv:2601.09980, 2026

Reference 28

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Observation 962a7ab6-3b09-434b-a58e-db99bf0a27da · outbound

This paper cites Knowledge-driven autonomous materials research via collaborative multi-agent and robotic system.Matter, 9(2):102577, 2026.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Knowledge-driven autonomous materials research via collaborative multi-agent and robotic system.Matter, 9(2):102577, 2026

Reference 29

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Observation 810f0008-9654-44ed-9d91-e4f279a9c84c · outbound

This paper cites Smedskjaer, Katrin Wondraczek, Lothar Wondraczek, Nitya Nand Gosvami, and N.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Smedskjaer, Katrin Wondraczek, Lothar Wondraczek, Nitya Nand Gosvami, and N

Reference 30

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Observation 9b9a5c5c-1f53-488d-b691-7d4b8a8fd285 · outbound

This paper cites Prince, Tao Zhou, Henry Chan, and Mathew J.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Prince, Tao Zhou, Henry Chan, and Mathew J

Reference 31

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Observation 46b01d9a-63ca-4606-9809-8b74927654c0 · outbound

This paper cites AI scientists produce results without reasoning scientifically.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents AI scientists produce results without reasoning scientifically

Reference 32

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Observation efb784d4-d6d1-4535-b4b1-80de0c01386e · outbound

This paper cites an unresolved cited work.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Unresolved cited work

Reference 33

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Observation 795fd306-c083-42b3-b0e2-0cd13d381e1b · outbound

This paper cites Large language models for automated open-domain scientific hypotheses discovery.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Large language models for automated open-domain scientific hypotheses discovery

Reference 34

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Observation ec334b22-e6d8-4dfc-8531-5cf8b3333cb0 · outbound

This paper cites Moose-chem: Large language models for rediscovering unseen chemistry scientific hypotheses.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Moose-chem: Large language models for rediscovering unseen chemistry scientific hypotheses

Reference 35

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Observation 194876a0-22cb-4e38-895c-4dfb4a107f74 · outbound

This paper cites Moose-chem2: Exploringllmlimitsinfine-grainedscien- tific hypothesis discovery via hierarchical search.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Moose-chem2: Exploringllmlimitsinfine-grainedscien- tific hypothesis discovery via hierarchical search

Reference 36

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Observation ab0ad8b7-e9a9-4707-a120-85d61c7eff45 · outbound

This paper cites AIGS: Generating Science from AI-Powered Automated Falsification.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents AIGS: Generating Science from AI-Powered Automated Falsification

Reference 37

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Observation 35a79b55-609b-4891-8428-857e73433551 · outbound

This paper cites Li, Emmanuel Candès, and Jure Leskovec.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Li, Emmanuel Candès, and Jure Leskovec

Reference 38

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Observation fedc48a9-4baa-4fe5-9a1c-613fb490efee · outbound

This paper cites Autodiscovery: Open-ended scientific discovery via bayesian surprise.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Autodiscovery: Open-ended scientific discovery via bayesian surprise

Reference 39

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Observation d006a7ba-2e4e-4e45-bae5-b724590774e0 · outbound

This paper cites Wang, Lee Marom, Subhadeep Pal, Rachel K.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Wang, Lee Marom, Subhadeep Pal, Rachel K

Reference 40

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Observation fb882f91-c4da-4fd1-8c92-563b07b1fa1d · outbound

This paper cites DiscoverPhysics: Benchmarking LLMs for Out-of-the-Box Scientific Thinking.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents DiscoverPhysics: Benchmarking LLMs for Out-of-the-Box Scientific Thinking

Reference 41

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Observation 37b94a76-29f1-46f1-bb77-bd6bbb7888b1 · outbound

This paper cites Workflow Closure Is Not Scientific Closure in Auto-Research Systems.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Workflow Closure Is Not Scientific Closure in Auto-Research Systems

Reference 42

Resolution: unresolved; no resolver link, observed 2026-07-13T04:47:57.575546Z

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Observation e4b59e4f-20ff-44a2-be69-9d881e0e72b5 · outbound

This paper cites Agentic AI Scientists Are Not Built For Autonomous Scientific Discovery.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Agentic AI Scientists Are Not Built For Autonomous Scientific Discovery

Reference 43

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Observation dfc32ef9-3976-47ef-a3b6-b04a1d0c290b · outbound

This paper cites GPT-5.5 System Card.https://openai.com/index/gpt-5-5-system-card/, 2026.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents GPT-5.5 System Card.https://openai.com/index/gpt-5-5-system-card/, 2026

Reference 44

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Observation 62aa19a0-1faa-435a-a5c3-76444095b30f · outbound

This paper cites Introducing GPT-5.4 mini and nano.https://openai.com/index/ introducing-gpt-5-4-mini-and-nano/, 2026.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Introducing GPT-5.4 mini and nano.https://openai.com/index/ introducing-gpt-5-4-mini-and-nano/, 2026

Reference 45

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Observation 64bf5b7b-5990-4a82-890c-9a2284481275 · outbound

This paper cites Introducing GPT-4.1 in the API.https://openai.com/index/gpt-4-1/, 2025.

Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents Introducing GPT-4.1 in the API.https://openai.com/index/gpt-4-1/, 2025

Reference 46

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Pith citing papers

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