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Paper Citation Record · LEDGER

HoneyComb: A Flexible LLM-Based Agent System for Materials Science

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:2409.00135.

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

pith.paper-citation-record.v1
2409.00135 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T14:48:36.391313Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
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  • malformed identifier0
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External citation measurements

5
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 2b790e1f-a0a3-4ceb-800b-7d14aee5451b · inbound

TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis cites this paper.

TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis HoneyComb: A Flexible LLM-Based Agent System for Materials Science

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-05-23T19:45:47.144574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-23T19:45:39.130509Z digest=sha256:466573ce686ba7a5394721b393688b61c2454ea4fa3d32b4f9fc32dcf8941a69

Observation cd632fee-de16-4a74-a15f-f809a1c2bb38 · inbound

The AI Agent Index cites this paper.

The AI Agent Index HoneyComb: A Flexible LLM-Based Agent System for Materials Science

Reference 101

Resolution
unresolved
no resolver link, observed 2026-08-09T14:48:36.391313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:48:36.391313Z digest=sha256:c8c6597e6c73730cc084b606b2c81a86bbd39261ee3f72ae99f6900b6ee6a6cb

Observation 920559ef-6977-458b-aaaf-1ca8223bba36 · inbound

From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review cites this paper.

From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review HoneyComb: A Flexible LLM-Based Agent System for Materials Science

Reference 141

Resolution
verified exact
arxiv_id, observed 2026-05-15T02:57:38.517412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T02:57:37.873567Z digest=sha256:6365a460ecfefb5b2599b240f929bc422a01fff8168e65d477c5361e2e5f4fe6

Observation de8ae1e0-fa17-410f-817a-0c2cfeff945a · inbound

Seeing Beyond Words: MatVQA for Challenging Visual-Scientific Reasoning in Materials Science cites this paper.

Seeing Beyond Words: MatVQA for Challenging Visual-Scientific Reasoning in Materials Science HoneyComb: A Flexible LLM-Based Agent System for Materials Science

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-07T14:37:31.390393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:37:31.390393Z digest=sha256:da623ea0cb6cb40e29070423dffd5b2cd507792b5ac45229f3dbf98d0c4aa357

Observation 8dabfc3b-d9c4-4088-bae8-fe8dc73d11ce · inbound

Beyond Atomic Geometry Representations in Materials Science: A Human-in-the-Loop Multimodal Framework cites this paper.

Beyond Atomic Geometry Representations in Materials Science: A Human-in-the-Loop Multimodal Framework HoneyComb: A Flexible LLM-Based Agent System for Materials Science

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T12:12:02.875750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:02.875750Z digest=sha256:12156f17d81ec005be214482cf554fc85c998591e1477c5ead491d2b645761a0

Observation 325b94a7-ba57-4f10-b351-431228a97d3f · inbound

Stress-Testing Multimodal Foundation Models for Crystallographic Reasoning cites this paper.

Stress-Testing Multimodal Foundation Models for Crystallographic Reasoning HoneyComb: A Flexible LLM-Based Agent System for Materials Science

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T00:43:54.731892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:43:54.731892Z digest=sha256:3cee9ad9f27b34421777824cf6dc53cb7e83b84a967d6dc7dd34fe6e21856175

Observation 3955247d-bc47-40b9-9549-d521278cb1f0 · inbound

A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools cites this paper.

A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools HoneyComb: A Flexible LLM-Based Agent System for Materials Science

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-06T22:45:51.422557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:45:51.422557Z digest=sha256:ac208b8f2fcc248f90b13d0add86f7ff43b94d619c3630333a4c76d27d843158

Observation 558d0611-f1d5-4c80-9341-83f7fd54042a · inbound

HedraRAG: Coordinating LLM Generation and Database Retrieval in Heterogeneous RAG Serving cites this paper.

HedraRAG: Coordinating LLM Generation and Database Retrieval in Heterogeneous RAG Serving HoneyComb: A Flexible LLM-Based Agent System for Materials Science

Reference 79

Resolution
unresolved
no resolver link, observed 2026-08-06T18:08:47.203410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:08:47.203410Z digest=sha256:c7ab89ec39fc43eedac64973830cb77435db4c94cb4e59aa1a5ca191225ca9a4

Observation 8f542d3c-5cfb-4f1f-8570-c60b2f443db8 · inbound

Perovskite-R1: a domain-specialized large language model for intelligent discovery of precursor additives and experimental design cites this paper.

Perovskite-R1: a domain-specialized large language model for intelligent discovery of precursor additives and experimental design HoneyComb: A Flexible LLM-Based Agent System for Materials Science

Reference 50

Resolution
verified exact
arxiv_id, observed 2026-05-22T00:30:49.212157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-22T00:26:35.977160Z digest=sha256:5aac5541be6589378ccf91653f532f291d9f5f1161a33d0018dac43cb124d4bc

Observation 506ffbb7-b9b1-403a-abb8-7f71ca70b124 · inbound

IR-Agent: Expert-Inspired LLM Agents for Structure Elucidation from Infrared Spectra cites this paper.

IR-Agent: Expert-Inspired LLM Agents for Structure Elucidation from Infrared Spectra HoneyComb: A Flexible LLM-Based Agent System for Materials Science

Reference 39

Resolution
malformed identifier
arxiv_id, observed 2026-05-21T23:20:45.257137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-21T23:16:08.658251Z digest=sha256:572798a8980998abe9433dfeeb9035f2032f9a2b9fbadc7c256a879b21c58d6d

Observation 076adc81-e2fb-4956-b1ad-b351ef410002 · inbound

Can Multimodal LLMs See Materials Clearly? A Multimodal Benchmark on Materials Characterization cites this paper.

Can Multimodal LLMs See Materials Clearly? A Multimodal Benchmark on Materials Characterization HoneyComb: A Flexible LLM-Based Agent System for Materials Science

Reference 2020

Resolution
malformed identifier
no resolver link, observed 2026-08-04T19:25:50.080180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:25:50.080180Z digest=sha256:a4a1e1802d79dd2cc9558545d3a4d910fe27a4bbe951c81f6f66cc64060d21a3

Observation 00114ee4-27a5-49e3-a9f6-f97890bfaab6 · inbound

Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory cites this paper.

Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory HoneyComb: A Flexible LLM-Based Agent System for Materials Science

Reference 297

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T23:13:16.068209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-14T23:13:15.016486Z digest=sha256:a9e27df11df8d65652d654789a9085274425dff9f8a6a49f98777454d083c28e

Observation f196e015-daa5-4566-9ce6-30ed547dd89f · inbound

VASP Agent: An Agentic Framework for Autonomous First-principles Calculations cites this paper.

VASP Agent: An Agentic Framework for Autonomous First-principles Calculations HoneyComb: A Flexible LLM-Based Agent System for Materials Science

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-03T14:45:41.515515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T14:45:41.515515Z digest=sha256:7bf83364e34db82e98e187a228dd6c014d733423aa07e6c2d782d587b73dc0bf

Observation 7506b1fd-1c02-4611-9409-9f424f40f6a8 · inbound

ALL-FEM: Agentic Large Language models Fine-tuned for Finite Element Methods cites this paper.

ALL-FEM: Agentic Large Language models Fine-tuned for Finite Element Methods HoneyComb: A Flexible LLM-Based Agent System for Materials Science

Reference 15

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T15:51:05.266070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-16T15:49:36.623425Z digest=sha256:545e75c1990e15b7fe7072eefa8531d886346fede4c6a53dfa905a7d987387c8

Observation ec13e380-9ce2-4cd7-b502-025a70abeaaa · inbound

SciHorizon-DataEVA: An Agentic System for AI-Readiness Evaluation of Heterogeneous Scientific Data cites this paper.

SciHorizon-DataEVA: An Agentic System for AI-Readiness Evaluation of Heterogeneous Scientific Data HoneyComb: A Flexible LLM-Based Agent System for Materials Science

Reference 28

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T09:26:26.158979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-07T10:54:22.054202Z digest=sha256:a151523893aed2390ecc83c0adf949f1b1d5e8182cfddef1c7fbb824f4e5a858

Observation bfc627ef-f456-47cd-a77f-2f69cf2fed4c · inbound

SCICONVBENCH: Benchmarking LLMs on Multi-Turn Clarification for Task Formulation in Computational Science cites this paper.

SCICONVBENCH: Benchmarking LLMs on Multi-Turn Clarification for Task Formulation in Computational Science HoneyComb: A Flexible LLM-Based Agent System for Materials Science

Reference 78

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T10:38:12.051234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-20T10:36:09.724234Z digest=sha256:069a964aaac506134cdabeefe8dd09e87d9187fd9fa6ce55a05efc3319e41688

Observation cdc1b42e-8db6-43d4-b039-d1456142bc79 · inbound

From Text to Discovery: How Large Language Models Are Reshaping Research Across Scientific and Humanistic Disciplines cites this paper.

From Text to Discovery: How Large Language Models Are Reshaping Research Across Scientific and Humanistic Disciplines HoneyComb: A Flexible LLM-Based Agent System for Materials Science

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-06-27T17:31:07.405701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T17:22:30.784806Z digest=sha256:037c08e0b1a8a4568ef533e3301677d4386b83d2ceda29505d9bff56dbcf18a2

Observation 3756b274-62da-4b45-a288-253903f62964 · inbound

From Text to Discovery: How Large Language Models Are Reshaping Research Across Scientific and Humanistic Disciplines cites this paper.

From Text to Discovery: How Large Language Models Are Reshaping Research Across Scientific and Humanistic Disciplines HoneyComb: A Flexible LLM-Based Agent System for Materials Science

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-02T12:03:26.563246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T12:03:26.563246Z digest=sha256:04eeadde2de5caf8103c136533d592c02646d3661bd922fbf3314d192332c0ef