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Paper Citation Record · LEDGER

Schema-Guided Scene-Graph Reasoning based on Multi-Agent Large Language Model System

As of 9 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 1 inbound Pith citation observation for arXiv:2502.03450.

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

pith.paper-citation-record.v1
2502.03450 v2

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T04:45:34.727306Z

measured 15 of 15 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:26:47.846440Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T23:26:56.530363Z

Reference resolution

14 of 14 outbound references displayed

  • verified exact0
  • verified fuzzy6
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3fad57fb-410c-44ce-9f4a-2820cfad4e1b · outbound

This paper cites Reason on what information do you need to solve the task, and query for the information from the retriever.

Schema-Guided Scene-Graph Reasoning based on Multi-Agent Large Language Model System Reason on what information do you need to solve the task, and query for the information from the retriever

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T04:45:34.938594Z

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=2026-08-09T04:45:34.717216Z digest=sha256:e187c36ce2767e78ee673e0cb61ee60d9dc681e98804f5d6128c736ec8c4b059

Observation 2511c089-f5f0-49ae-9f38-d700babe18f8 · outbound

This paper cites Call a function from the given function set to address a substep.

Schema-Guided Scene-Graph Reasoning based on Multi-Agent Large Language Model System Call a function from the given function set to address a substep

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T04:45:34.923088Z

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=2026-08-09T04:45:34.722331Z digest=sha256:3c51cc79e4f896c995f41abdc7e3a033c2cce3a873a881c10e0c8f06b6aef3e3

Observation ff797bc8-5ade-40b7-a8a9-0df1f864339c · outbound

This paper cites type": String. The type of the element type. Choices: root, room, agent, key, door, box, ball •.

Schema-Guided Scene-Graph Reasoning based on Multi-Agent Large Language Model System type": String. The type of the element type. Choices: root, room, agent, key, door, box, ball •

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T04:45:34.908623Z

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=2026-08-09T04:45:34.727306Z digest=sha256:69b539229ceaeb3d91776da6464365dd1dc4b5ad52572fbb20f6681893ebf7d5

Observation 5a037ed8-6b65-4b3d-abe7-143e729a4183 · outbound

This paper cites LLM+P: Empowering Large Language Models with Optimal Planning Proficiency.

Schema-Guided Scene-Graph Reasoning based on Multi-Agent Large Language Model System LLM+P: Empowering Large Language Models with Optimal Planning Proficiency

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-09T04:45:34.674610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T04:45:34.674610Z digest=sha256:9b5397174abe3c8ce09abcccd60e979b30a815066c7a2e6a5be3e56907f764f8

Observation 4fe79c77-f6f1-4003-b054-3eb003ffa7a9 · outbound

This paper cites Open X-Embodiment: Robotic Learning Datasets and RT-X Models.

Schema-Guided Scene-Graph Reasoning based on Multi-Agent Large Language Model System Open X-Embodiment: Robotic Learning Datasets and RT-X Models

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-09T04:45:34.680641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T04:45:34.680641Z digest=sha256:6157244ab7301e1bc5032d4910989e215da241325689f253804476e858ced2ae

Observation 2eada0aa-e67c-4ff1-a633-e2b402234738 · outbound

This paper cites In The Twelfth International Conference on Learning Representations.

Schema-Guided Scene-Graph Reasoning based on Multi-Agent Large Language Model System In The Twelfth International Conference on Learning Representations

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T04:45:34.970727Z

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=2026-08-09T04:45:34.685695Z digest=sha256:6649a048dd594ec0bbd2eb71870c6ad5b6e7d4275009895826190e9cc5abebe7

Observation a4dc5099-c145-4331-8ff1-13dc9ee2f633 · outbound

This paper cites Octo: An Open-Source Generalist Robot Policy.

Schema-Guided Scene-Graph Reasoning based on Multi-Agent Large Language Model System Octo: An Open-Source Generalist Robot Policy

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-09T04:45:34.690726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T04:45:34.690726Z digest=sha256:4fe324934816f9873447f167d22ca3cf2c780e14a290f7ac3feacba7fc5ff6cd

Observation a58dff10-ea09-4676-b44e-53e9b3880605 · outbound

This paper cites Wu, S.-C.; Wald, J.; Tateno, K.; Navab, N.; and Tombari, F.

Schema-Guided Scene-Graph Reasoning based on Multi-Agent Large Language Model System Wu, S.-C.; Wald, J.; Tateno, K.; Navab, N.; and Tombari, F

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T04:45:34.954675Z

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=2026-08-09T04:45:34.696829Z digest=sha256:45ae0d099ccf36832d850315e3589725d8cbe4c9310deaac788504e36ee99ac6

Observation 1de4f2bd-bed4-482f-973a-cb5ef19e64ed · outbound

This paper cites Language is All a Graph Needs.

Schema-Guided Scene-Graph Reasoning based on Multi-Agent Large Language Model System Language is All a Graph Needs

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-09T04:45:34.711750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T04:45:34.711750Z digest=sha256:9aaa4858046bfd6b76d2d12c4c5bd8b103044600c09d440d5dce779dde4732b3

Observation e3f827e7-2b8c-4330-8d51-22f2ea6a50e2 · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

Schema-Guided Scene-Graph Reasoning based on Multi-Agent Large Language Model System ReAct: Synergizing Reasoning and Acting in Language Models

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-09T04:45:34.706449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T04:45:34.706449Z digest=sha256:49123afc2448742de97ed7286e554c1ca87bece946a9b380f27c4fb129856127

Observation 015aca78-3aa5-49b6-9de9-7b0aa72b747f · outbound

This paper cites The Rise and Potential of Large Language Model Based Agents: A Survey.

Schema-Guided Scene-Graph Reasoning based on Multi-Agent Large Language Model System The Rise and Potential of Large Language Model Based Agents: A Survey

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-09T04:45:34.701538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T04:45:34.701538Z digest=sha256:279579aef05f5d73d4089d9fa0d23cbd26e92d8ad30770f16e86e04c83ae1d3f

Observation 04bca54b-7c65-4ac0-bc82-1f74e3ae750c · outbound

This paper cites Ad- vances in neural information processing systems , 35: 22199– 22213.

Schema-Guided Scene-Graph Reasoning based on Multi-Agent Large Language Model System Ad- vances in neural information processing systems , 35: 22199– 22213

Reference 2022

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T04:45:34.987570Z

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=2026-08-09T04:45:34.669585Z digest=sha256:69f8257541d1cd615012a25453dfff33c4ec2072c9b772a5edcfb316670c3cdf

Observation 565c2c17-34c4-437c-82ec-4ba233b86433 · outbound

This paper cites Planning with Sequence Models through Iterative Energy Minimization.

Schema-Guided Scene-Graph Reasoning based on Multi-Agent Large Language Model System Planning with Sequence Models through Iterative Energy Minimization

Reference 2023

Resolution
metadata mismatch
local_arxiv, observed 2026-08-09T04:45:34.873006Z

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=2026-08-09T04:45:34.664536Z digest=sha256:488f98654502d2a4c7a91803bf3c82b42edb272d275bf2e33d68a8491fe39a0e

Observation dbe155a3-5eab-4969-8018-e5bfe5a2dc82 · outbound

This paper cites Large Language Models for Mathematical Reasoning: Progresses and Challenges.

Schema-Guided Scene-Graph Reasoning based on Multi-Agent Large Language Model System Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-09T04:45:34.659093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T04:45:34.659093Z digest=sha256:5ad42ba1c97e8a355dff42fbe8545498bec3bed890d80e9343ec0e966f1c4890

Pith citing papers

Observation e8db85f9-a25d-48b9-bdce-f65d3d7d2874 · inbound

Graphs Meet AI Agents: Taxonomy, Progress, and Future Opportunities cites this paper.

Graphs Meet AI Agents: Taxonomy, Progress, and Future Opportunities Schema-Guided Scene-Graph Reasoning based on Multi-Agent Large Language Model System

Reference 68

Resolution
verified exact
local_arxiv, observed 2026-08-06T23:26:56.536028Z

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=2026-08-06T23:26:47.846440Z digest=sha256:57df9cb3ef5a9b1138a9c583cb6e0d9b942796abd41dc940f33cb2f6c807bcc6