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Paper Citation Record · LEDGER

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

As of 10 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=sha256:41489358b8c080f4326b4887d3365b1210635fa420400daba87f7acfc903de5b

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=sha256:1baf6ac637fea3ea853cf6b44d5861c29ca0c383065416e8d8d96641b333a853

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:f7ac1e2de37dc071b84a032afe8836b75d75581bce146d821eb15b415afb93b0

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=sha256:00f0766864245c3591704b6dccbe79fffce3031da2692ebffb81d7f022cf2bbc

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=sha256:661ca8b0190915042aaef0081e24bf81dd60a9adaf5ad564b3373bd319ce8cda

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=sha256:371d67fc2969052d8f460d379dafa4a30314ff9283b48a8992e5bdc984c25381

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:e959443a703526ebf0095033a9904a8a1d6d20fe64c4a022e604a28665a466d7

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=sha256:71f1d106c73537cddcccb5fc7fab38677f9913aa8baac8981e64425cec8a5e73

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=sha256:3268d6358a802d81dcf49ed8c2fe337fd23c508f7ba6ce15e9e934ef071c64ef

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=sha256:79c5e7ac4b01c5c75480603aca5f5311d2ceef4e004e979a3bab35aff75a848e

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:eb4a9d4539bd95ea43cae76ae2aa0611fc8dafb756b8b91329bc33720745769d

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=sha256:6f594b2ba790e8ca314c887c75193295abe53e03b2d28cce631ea2a235c32e1c

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=sha256:1087b9344f50ac691710147ebb130e37c412a4f374a85094bab4971ef88f7428

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:dabd9941e5360df05d19464f75d8d2c12d77245796eb212bfff658abed9c1bdb

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:e5c9d039278aa42ff52689ab8e118964ead8f56a0b250da3cf6b996b0d90a101