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Paper Citation Record · LEDGER

DocRefine: An Intelligent Framework for Scientific Document Understanding and Content Optimization based on Multimodal Large Model Agents

As of 8 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2508.07021.

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

pith.paper-citation-record.v1
2508.07021 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:28:38.338356Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

18 of 18 outbound references displayed

  • verified exact0
  • verified fuzzy14
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3f496f99-d99f-4d33-bbd2-9bf8471aabfe · outbound

This paper cites A semantic model of integrity constraints on a relational data base,.

DocRefine: An Intelligent Framework for Scientific Document Understanding and Content Optimization based on Multimodal Large Model Agents A semantic model of integrity constraints on a relational data base,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:28:40.615861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T22:28:37.138600Z digest=sha256:bdb1ae412d57ddf923eebe813e6e2030c6ee058354669969d6f1a109c6335eb9

Observation 7e6ac4a7-1da5-4e4d-830e-48c6c60f7f09 · outbound

This paper cites Chatgpt for good? on opportunities and challenges of large language models for education,.

DocRefine: An Intelligent Framework for Scientific Document Understanding and Content Optimization based on Multimodal Large Model Agents Chatgpt for good? on opportunities and challenges of large language models for education,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:28:40.501158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T22:28:37.215155Z digest=sha256:f9ef347af6c6841d0c825f9f0d21cbdd24095ef885cb417b01332e170b2f102c

Observation b55d9604-c458-4fce-ac95-17c836c283e8 · outbound

This paper cites Lvlm-ehub: A comprehensive evaluation bench- mark for large vision-language models,.

DocRefine: An Intelligent Framework for Scientific Document Understanding and Content Optimization based on Multimodal Large Model Agents Lvlm-ehub: A comprehensive evaluation bench- mark for large vision-language models,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:28:40.379482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T22:28:37.253990Z digest=sha256:17a07f720d32e8257b1c26fe518935444958a397c24dbcc8f2225bcfe0337d78

Observation 9067c10e-7c86-4215-a87c-e4541db06fd3 · outbound

This paper cites Weak to strong generalization for large language models with multi-capabilities,.

DocRefine: An Intelligent Framework for Scientific Document Understanding and Content Optimization based on Multimodal Large Model Agents Weak to strong generalization for large language models with multi-capabilities,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:28:40.268520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T22:28:37.302645Z digest=sha256:3f4ce19d3ff0173411b31e95b79776696937641a032bd2064061240c8ce0ade6

Observation 13c19543-af14-4bc3-b3f7-9c6546518aa4 · outbound

This paper cites Thread of Thought Unraveling Chaotic Contexts.

DocRefine: An Intelligent Framework for Scientific Document Understanding and Content Optimization based on Multimodal Large Model Agents Thread of Thought Unraveling Chaotic Contexts

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-05T22:28:37.355969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:28:37.355969Z digest=sha256:55648c8d22afcb84213df4ec9828b38f2fd97667e8e0b392c4202a8c4c58e57f

Observation 2a8a1c4f-c3f9-491e-8345-5bdb1b345e0b · outbound

This paper cites Visual in-context learning for large vision-language models,.

DocRefine: An Intelligent Framework for Scientific Document Understanding and Content Optimization based on Multimodal Large Model Agents Visual in-context learning for large vision-language models,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:28:40.114701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T22:28:37.453164Z digest=sha256:5b700aa5874a5908991bd6b598614263c08c5be26977ad0a0963583d7bfda412

Observation 4950c14e-ae3a-4857-a27d-880c3d4b6f9a · outbound

This paper cites Improving Medical Large Vision-Language Models with Abnormal-Aware Feedback.

DocRefine: An Intelligent Framework for Scientific Document Understanding and Content Optimization based on Multimodal Large Model Agents Improving Medical Large Vision-Language Models with Abnormal-Aware Feedback

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-05T22:28:37.518286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:28:37.518286Z digest=sha256:2f1ffd36638bf7d9d62d6d7516ff49b4da132c3672ea5da5c2b4ed038ef7f7e9

Observation fc97759a-79a5-473e-a028-2395a32a1ddf · outbound

This paper cites Exploring ai-driven approaches for unstructured document analysis and future horizons,.

DocRefine: An Intelligent Framework for Scientific Document Understanding and Content Optimization based on Multimodal Large Model Agents Exploring ai-driven approaches for unstructured document analysis and future horizons,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:28:39.930269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T22:28:37.605320Z digest=sha256:e41a8d75c6ec3a1ccbbe5bfb85c80f81c857919d138395ad819e467d8315207a

Observation ecce5bc0-4f36-4207-a8aa-9bb57edc425c · outbound

This paper cites Large language model enhanced multi-agent systems for 6g communications,.

DocRefine: An Intelligent Framework for Scientific Document Understanding and Content Optimization based on Multimodal Large Model Agents Large language model enhanced multi-agent systems for 6g communications,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:28:39.761906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T22:28:37.686420Z digest=sha256:9d6e78455e83d30136546280010a1b2518f3ecdaaa54903027870f9d38494528

Observation daebe4f3-c61d-450d-9920-fbd3c9c72962 · outbound

This paper cites Multi-agent collaboration mechanisms: A survey of llms,.

DocRefine: An Intelligent Framework for Scientific Document Understanding and Content Optimization based on Multimodal Large Model Agents Multi-agent collaboration mechanisms: A survey of llms,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:28:39.625884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T22:28:37.787045Z digest=sha256:aab40049dabbf409cb01e4ef3b454c236f30308faf2b68f912de9cddc7454603

Observation a51226ee-9c5e-44d4-bcd9-8a4efdecdded · outbound

This paper cites Transforming competition into collaboration: The rev- olutionary role of multi-agent systems and language models in modern organizations,.

DocRefine: An Intelligent Framework for Scientific Document Understanding and Content Optimization based on Multimodal Large Model Agents Transforming competition into collaboration: The rev- olutionary role of multi-agent systems and language models in modern organizations,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:28:39.492023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T22:28:37.856412Z digest=sha256:cf51e18bc2adee94fe78823cc12c036e67b35c3b3c3e5e22096f6fb4b0c7be99

Observation c5bbb376-d18f-42b6-9b30-875985e83313 · outbound

This paper cites Draw ALL Your Imagine: A Holistic Benchmark and Agent Framework for Complex Instruction-based Image Generation.

DocRefine: An Intelligent Framework for Scientific Document Understanding and Content Optimization based on Multimodal Large Model Agents Draw ALL Your Imagine: A Holistic Benchmark and Agent Framework for Complex Instruction-based Image Generation

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-05T22:28:37.911045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:28:37.911045Z digest=sha256:d04afd47afcdc5b6cdd0aa258a4cbb1446208e58c7351203c0f55dee82e8218f

Observation 8468154f-ead5-4b69-adc4-65101a167fd3 · outbound

This paper cites Layered chain-of-thought prompting for multi-agent LLM systems: A comprehensive approach to explainable large language models,.

DocRefine: An Intelligent Framework for Scientific Document Understanding and Content Optimization based on Multimodal Large Model Agents Layered chain-of-thought prompting for multi-agent LLM systems: A comprehensive approach to explainable large language models,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:28:39.352855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T22:28:37.988418Z digest=sha256:bf102f2f99e3781c35724ccad2e3dafdbee049f0e08339849dab54b34b8fc352

Observation 14fa7b76-6329-49f7-afe8-12713045ee80 · outbound

This paper cites Au- tomatically correcting large language models: Surveying the landscape of diverse self-correction strategies,.

DocRefine: An Intelligent Framework for Scientific Document Understanding and Content Optimization based on Multimodal Large Model Agents Au- tomatically correcting large language models: Surveying the landscape of diverse self-correction strategies,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:28:39.153520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T22:28:38.060752Z digest=sha256:5ccb67f6b5c97b762f37bc514ae6cc20fb1d9d72a56b022fc564357385e81fb8

Observation ce8aa9f9-114b-4e77-82f1-c7365b6bcd75 · outbound

This paper cites Benchmark evaluations, applications, and challenges of large vision language models: A survey,.

DocRefine: An Intelligent Framework for Scientific Document Understanding and Content Optimization based on Multimodal Large Model Agents Benchmark evaluations, applications, and challenges of large vision language models: A survey,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:28:38.980675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T22:28:38.148819Z digest=sha256:c7faee3c88f7757928c7aeb237526ea8848b88e12ee25ef367a0b68f63f8eaba

Observation 4fa7a151-17f7-490b-830e-5088e4c8e51b · outbound

This paper cites Large language model based multi-agents: A survey of progress and challenges,.

DocRefine: An Intelligent Framework for Scientific Document Understanding and Content Optimization based on Multimodal Large Model Agents Large language model based multi-agents: A survey of progress and challenges,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:28:38.811613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T22:28:38.226583Z digest=sha256:a9fe8e3c5980a2100805d0197fc6c75b6476cdda47f52a2713e713b535277db1

Observation 69f1e351-670a-4c2f-a8fd-de0d9d3fd292 · outbound

This paper cites Less is more: Vision representation compression for efficient video generation with large language models,.

DocRefine: An Intelligent Framework for Scientific Document Understanding and Content Optimization based on Multimodal Large Model Agents Less is more: Vision representation compression for efficient video generation with large language models,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:28:38.566217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T22:28:38.303246Z digest=sha256:5d5aa10be6c8b43b90112b0b56e3ae8de138412ac58bcb13b3da6d5159da393f

Observation 0d823e82-a3bf-456b-80df-1434b7022e4d · outbound

This paper cites MemoryMamba: Memory-Augmented State Space Model for Defect Recognition.

DocRefine: An Intelligent Framework for Scientific Document Understanding and Content Optimization based on Multimodal Large Model Agents MemoryMamba: Memory-Augmented State Space Model for Defect Recognition

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-05T22:28:38.338356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:28:38.338356Z digest=sha256:ec220fa572107d653baa2609ffda7ea0170a5fa7ff570b8866917611cc191dfc

Pith citing papers

No inbound Pith citation observations are available.