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Paper Citation Record · LEDGER

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark

As of 9 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2507.15882.

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

pith.paper-citation-record.v1
2507.15882 v2

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:12:03.811310Z

measured 36 of 36 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 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

36 of 36 outbound references displayed

  • verified exact1
  • verified fuzzy18
  • unresolved17
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bdec5a75-e740-4419-9381-c9d9a27ecc92 · outbound

This paper cites Improving language understanding by generative pre-training.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark Improving language understanding by generative pre-training

Reference 1

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

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Observation 15ff5d91-7beb-4982-a532-37f0e1536a26 · outbound

This paper cites Palm: Scaling language modeling with pathways.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark Palm: Scaling language modeling with pathways

Reference 2

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source=pdf_text observed=2026-08-06T16:11:59.401910Z digest=sha256:4f61740dc286449abdd5835b1f3bdd1cc883737c0ac2efb9cbc979bf1e4bbb53

Observation d7bf8b15-b176-45bb-9de9-0b3e549a0122 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark LLaMA: Open and Efficient Foundation Language Models

Reference 3

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Observation 5ffc3dc8-c6b8-4fe4-822d-8208fa21d627 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 4

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source=pdf_text observed=2026-08-06T16:11:59.455039Z digest=sha256:3b2248b731f5d2032a29023b20f6389f01cf4484a06e3a3c0141ffadbf673ed8

Observation 055f1b8a-079e-4295-a6e0-373421acef82 · outbound

This paper cites GPT-4 Technical Report.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark GPT-4 Technical Report

Reference 5

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source=pdf_text observed=2026-08-06T16:11:59.493405Z digest=sha256:37f3299d3823baecc5f08f592c98cfc0577864b145a6e7db5252534474e663d1

Observation afb4f16d-a539-4702-bdc4-b88b33ff2f43 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark Gemini: A Family of Highly Capable Multimodal Models

Reference 6

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source=pdf_text observed=2026-08-06T16:11:59.549630Z digest=sha256:7c7c0dcd60ed90f4e4796655eed7cd5568dd9061bb7d5e4331b9f6ff4e41c95a

Observation 746a3555-eb67-43d1-bb57-19cc4bcab9f6 · outbound

This paper cites The Llama 3 Herd of Models.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark The Llama 3 Herd of Models

Reference 7

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source=pdf_text observed=2026-08-06T16:11:59.677645Z digest=sha256:917a90af3e48489538ff99da0ce6f2671ae0d34ba89bd141a00066abe7d232ab

Observation dd1fa778-bdde-4df4-b501-cc0a34073135 · outbound

This paper cites Introducing the next generation of claude: Claude 3 model family.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark Introducing the next generation of claude: Claude 3 model family

Reference 8

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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=2026-08-06T16:11:59.812322Z digest=sha256:fba9aa704d99e3cc17ec58e5522783b022503d631a45f3850040977946795549

Observation 6029eb52-ba7e-4834-b8a9-72a7cc99e65f · outbound

This paper cites The amazon nova family of models: Technical report and model card.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark The amazon nova family of models: Technical report and model card

Reference 9

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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=2026-08-06T16:11:59.945149Z digest=sha256:ad7cf1b4aab633bd63fc0ec6ba64c0401f69ea915967878e21378d892af93f36

Observation f74e43bc-4295-4db0-a940-1a8ed08f3396 · outbound

This paper cites Visionllm: Large language model is also an open-ended decoder for vision-centric tasks.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark Visionllm: Large language model is also an open-ended decoder for vision-centric tasks

Reference 10

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

source=pdf_text observed=2026-08-06T16:12:00.043620Z digest=sha256:cf4d3e8e1040d8a04b338de803c4468b57957effcec9a1f0150018cf5b51c8df

Observation 48e270f1-ef79-48ee-9c86-fb54bdc34c40 · outbound

This paper cites Adaptive Video Understanding Agent: Enhancing efficiency with dynamic frame sampling and feedback-driven reasoning.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark Adaptive Video Understanding Agent: Enhancing efficiency with dynamic frame sampling and feedback-driven reasoning

Reference 11

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source=pdf_text observed=2026-08-06T16:12:00.161768Z digest=sha256:ed93c81b6bc2b9bd5ae7fc2337cf2afdcaa4258bb1573867695f7e2e03d4a2d6

Observation f70a710e-72fa-49f5-9473-03ad86e397d1 · outbound

This paper cites Zero-resource speech translation and recognition with llms.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark Zero-resource speech translation and recognition with llms

Reference 12

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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=2026-08-06T16:12:00.359797Z digest=sha256:8cf6303a25adeb2898f48213de596ff525f88b0c39fc9dbb03dc4d19c05cbb04

Observation 53e7e97b-432f-487e-9f15-55cc23f44d33 · outbound

This paper cites Legal- bench: A collaboratively built benchmark for measuring legal reasoning in large language models.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark Legal- bench: A collaboratively built benchmark for measuring legal reasoning in large language models

Reference 13

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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=2026-08-06T16:12:00.538822Z digest=sha256:7370746c5db06e9e190316332b48feba15d7b80e9429920f852b93bce59766c4

Observation 691f8977-ccee-4b33-91cf-ed45f729094a · outbound

This paper cites Chatlaw: Open-source legal large language model with integrated external knowledge bases.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark Chatlaw: Open-source legal large language model with integrated external knowledge bases

Reference 14

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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=2026-08-06T16:12:00.658961Z digest=sha256:9ea0eba7583c0a684285a98c01e8486a3fd7e7079e73c0e125ecdffe5bf4b305

Observation cfd8f6f6-3ff4-4515-a935-f83a85ea8b94 · outbound

This paper cites A study of generative large language model for medical research and healthcare.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark A study of generative large language model for medical research and healthcare

Reference 15

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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=2026-08-06T16:12:00.724539Z digest=sha256:ccc972b652890d683884291daa4581f1c6e0ae5b1ec2a2d9f84ae45dfa1baaaf

Observation 5709f843-c7c6-4453-b980-c1b77cd516df · outbound

This paper cites Large language models in medicine.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark Large language models in medicine

Reference 16

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

source=pdf_text observed=2026-08-06T16:12:00.817655Z digest=sha256:29ed03a055e0f394a1f43198b55ff5f14646ca4b1e5b159e9916de45b84ebe7d

Observation 2d67e545-e78e-4c93-93af-b62101901c99 · outbound

This paper cites Large language models in finance: A survey.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark Large language models in finance: A survey

Reference 17

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

source=pdf_text observed=2026-08-06T16:12:00.931170Z digest=sha256:506c5c9ecae07516535d4fae48a037d5906c0c4d5f2d35a8c53a86d08a2e5254

Observation 01eccb1b-fd52-43fb-a708-227884a5c295 · outbound

This paper cites A Survey on Large Language Models for Critical Societal Domains: Finance, Healthcare, and Law.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark A Survey on Large Language Models for Critical Societal Domains: Finance, Healthcare, and Law

Reference 18

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source=pdf_text observed=2026-08-06T16:12:01.088100Z digest=sha256:4e99713b6a8008f0fed8cb6188baf8ec673045d71b5705db4bc9c7e56cf0a848

Observation be36be46-14c7-442b-9148-bdf8a426487c · outbound

This paper cites GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

Reference 19

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source=pdf_text observed=2026-08-06T16:12:01.261807Z digest=sha256:1331f4faa6b961bc45df673fe872469a1e4369d29a83a4f2d47011e64bbcc30c

Observation dadc202f-5e84-45c4-a3ff-3e8eceeda7ff · outbound

This paper cites Superglue: A stickier benchmark for general- purpose language understanding systems.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark Superglue: A stickier benchmark for general- purpose language understanding systems

Reference 20

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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=2026-08-06T16:12:01.394095Z digest=sha256:bade2c331de1c1b77e55517080a8fd543cbae0075c6ea1ba41f630c3554c24ea

Observation 05a1a7e5-78ad-45cf-b5b1-2b7ce80cbff0 · outbound

This paper cites Needle in a haystack-pressure testing llms.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark Needle in a haystack-pressure testing llms

Reference 21

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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=2026-08-06T16:12:01.566528Z digest=sha256:b307f9f8e45f43990e92281f2a7148b7b29b2a4661f71bd13b223995a44451ba

Observation b703fee8-e780-40c9-a86a-53f5c6c9b6a9 · outbound

This paper cites LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding

Reference 22

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source=pdf_text observed=2026-08-06T16:12:01.712774Z digest=sha256:a10bf72dd5a9595985fbee15b0c9ba5fd7968fb78c64fcd97089420b7e172298

Observation e8e3a648-420a-4b26-b5f5-3e32071c7ed3 · outbound

This paper cites Vqa: Visual question answering.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark Vqa: Visual question answering

Reference 23

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

source=pdf_text observed=2026-08-06T16:12:01.876492Z digest=sha256:c4b482c2d2a743950d9135b753ce62b3dc13483d758f690005595ecf05587512

Observation f4e19d24-0934-444b-8fab-2888b4389a5b · outbound

This paper cites A Corpus for Reasoning About Natural Language Grounded in Photographs.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark A Corpus for Reasoning About Natural Language Grounded in Photographs

Reference 24

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source=pdf_text observed=2026-08-06T16:12:02.036747Z digest=sha256:666f4f36c898e818d19a4a6d0b14ac38cffc14dfa39b41e7cc212b527158ef2e

Observation 2c6eae63-2f9c-449f-b856-6080ae010be5 · outbound

This paper cites MileBench: Benchmarking MLLMs in Long Context.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark MileBench: Benchmarking MLLMs in Long Context

Reference 25

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source=pdf_text observed=2026-08-06T16:12:02.171862Z digest=sha256:3ea1a47f1f080ce0acf3fdbe13eec48be0a19312cf2879bd44676a3a25f32a03

Observation 1e246951-2bed-4f69-9193-0ad1ef4dd56f · outbound

This paper cites ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning

Reference 26

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source=pdf_text observed=2026-08-06T16:12:02.326329Z digest=sha256:b4e606b38e5f261e51abc12358fee7af32d13682856fa40d0b93c57c540eb6d0

Observation 76c5ce3d-5e6d-464e-a5d8-2572687aa250 · outbound

This paper cites Docvqa: A dataset for vqa on document images.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark Docvqa: A dataset for vqa on document images

Reference 27

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raw_fallback, observed 2026-08-06T16:12:06.071480Z

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=2026-08-06T16:12:02.479204Z digest=sha256:17b8be3983402a0f22d55db99ef6975e04dbf938a1667cdce0a2d0e474c3d0da

Observation 91332362-0274-45a4-a58f-852ee01988dd · outbound

This paper cites Document understanding dataset and evalua- tion (dude).

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark Document understanding dataset and evalua- tion (dude)

Reference 28

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raw_fallback, observed 2026-08-06T16:12:05.884146Z

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

source=pdf_text observed=2026-08-06T16:12:02.641880Z digest=sha256:d82c1155479999390e2dd2a95abc7cbf7eb96460c192e24245e04d1fd6103e0d

Observation eaa94a9d-bd12-43eb-bc08-6fa51c8b11c3 · outbound

This paper cites Leave no document behind: Benchmarking long-context llms with extended multi-doc qa.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark Leave no document behind: Benchmarking long-context llms with extended multi-doc qa

Reference 29

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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=2026-08-06T16:12:02.766229Z digest=sha256:369d9c7d9844fdc21fb23f605b566b75c7d2f37c65cd3336337176f86a7cc299

Observation e8b89465-2f2f-4727-9996-0e454d557092 · outbound

This paper cites Slidevqa: A dataset for document visual question answering on multiple images.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark Slidevqa: A dataset for document visual question answering on multiple images

Reference 30

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raw_fallback, observed 2026-08-06T16:12:05.270470Z

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=2026-08-06T16:12:02.916848Z digest=sha256:98f493752ce157f1559e990bd575b8284d28432d37dd59bfaebe328fc6589610

Observation d4acb8a5-5d1b-43b1-94a9-f204c153c49a · outbound

This paper cites MMLongBench-Doc: Benchmarking Long-context Document Understanding with Visualizations.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark MMLongBench-Doc: Benchmarking Long-context Document Understanding with Visualizations

Reference 31

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:12:02.996244Z digest=sha256:cf58b145c4425a856eab6b4e74ee7cd17287d99db21eb5fbef4f24e9cb119841

Observation 527e72e5-0a7d-4e03-9788-624ac5fab665 · outbound

This paper cites Needle In A Multimodal Haystack.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark Needle In A Multimodal Haystack

Reference 32

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:12:03.116125Z digest=sha256:b506ddfd0f2f699bce1f7c0249e1fa21cf0cae2bff7d30e7c53e3ad90227a4e4

Observation 40d0d1e0-ba4b-4b0a-abe3-874870c8707a · outbound

This paper cites M-Longdoc: A Benchmark For Multimodal Super-Long Document Understanding And A Retrieval-Aware Tuning Framework.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark M-Longdoc: A Benchmark For Multimodal Super-Long Document Understanding And A Retrieval-Aware Tuning Framework

Reference 33

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source=pdf_text observed=2026-08-06T16:12:03.272897Z digest=sha256:37a9c582ae225a44f8463ea0941ac39cf6f45b8b7df7254a184d023afbf8b468

Observation c64c4e5b-afd7-4f9b-a92e-1e04eed10b3e · outbound

This paper cites Pixtral 12B.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark Pixtral 12B

Reference 34

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:12:03.418422Z digest=sha256:ecbef270f6413950a050cca8560cea603df0de2c93045bc73452f8522b59ae82

Observation 07604ab5-94a6-416c-8a5b-08e471b4db48 · outbound

This paper cites Cross-Modal Retrieval: A Systematic Review of Methods and Future Directions.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark Cross-Modal Retrieval: A Systematic Review of Methods and Future Directions

Reference 35

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local_arxiv, observed 2026-08-06T16:12:04.176645Z

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=2026-08-06T16:12:03.638856Z digest=sha256:17ff35fd58354d5558f4736dfdfb4c511ce477a483419610564583c36131d157

Observation 8d68d363-5b69-4a39-86db-2c1b14cf346d · outbound

This paper cites Lost in the middle: How language models use long contexts.

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark Lost in the middle: How language models use long contexts

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:12:04.935596Z

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=2026-08-06T16:12:03.811310Z digest=sha256:ff828005da7912c1df95fc713084917dc189620092def6200d32b255dd828fc9

Pith citing papers

No inbound Pith citation observations are available.