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Paper Citation Record · LEDGER

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

As of 23 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 2026-08-22T06:32:14.747728+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
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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 2026-08-22T06:32:14.747728+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=sha256:816ab5bf6ead0700b23b6b30f9aef08e06523abffb0e58e4d31d8e9ce1aa9540

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:d66e3d6673d685b654dda83b63eeefa9a2bc113d94bbf92e09448dba5bffb688

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:fc4b9e7448fffdf3a7e9303dd0738bb38e4dda3fc427cc128942fa66e1a4913b

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=sha256:6d38f547b62c429bcd525ff80c2bf3792a9214e6da2ca892bdf07999d54c3b48

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=sha256:67d36d798c8aad03824ad07fbb5fb9e778ef5e232932b430a87ecfa492fce746

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:11:59.812322Z digest=sha256:58adf594f5f2fa82ba4b632d2d277e4e297aba692ec99bd83965c27097915762

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:11:59.945149Z digest=sha256:87fa79fca6c1f175b5a78787fc45b321da4fbe35bb22d96ce9802daea29587c2

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:12:00.043620Z digest=sha256:96b128488f30de01c4c2afefdc2bd59513ccf8fc9a9a9539b756c70ce139534e

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=sha256:1f3c3e6e6dd740a1a23fca0147ed9c7b565c0c0fa5e0345ba3b2eefae5e70d46

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:12:00.359797Z digest=sha256:94c33805af0c920d87f6dbb86b8f2e57a05d6548e27c957612891ddcdfb5ae3c

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:12:00.538822Z digest=sha256:6cb7c295ab5f312ef2fcb1702cefec620453063203b16748f7996ca6b506e059

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:12:00.658961Z digest=sha256:af9a142329bf867070a332947fceb38c8606013d5adea9cd8d7de7b2065152df

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:12:00.724539Z digest=sha256:17f3c2f329c9ff1a1fc2c984dfa80c1e9903f3b4654a31a77adc2862b744a8d6

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:12:00.817655Z digest=sha256:03253c7de5deeafd77ff366020fa72ba017fbd1db8e8c0157c68c871f5c1bb79

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:12:00.931170Z digest=sha256:bd06e8e846965e101d9738e5561a7e0fa4a2aaed8b1eca5ae824e3f927cab2b4

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:e3498c8b8627e25e82ceccd67974d3114a4652ccead1370fbb904be70e55e03b

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=sha256:33e5ae8c7b1d36e8b6d917bd163eab8457e819df8c7e68649f904c22b4b8c4f7

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 2026-08-22T06:32:14.747728+00:00.

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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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raw_fallback, observed 2026-08-06T16:12:06.668443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:12:01.566528Z digest=sha256:b603717de17d74a54991f9fd36a63407d47bb208e65bf01d9274e179a9d2be39

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:e8e019ea40c06670b0f90d59321b5e14853798fa3af1290f7068ad57ee2f06b3

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:12:01.876492Z digest=sha256:ec655ee3a57561fd6341fbb4936a5f12f6f0fe7db670474545877fb3bff99ff3

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=sha256:54caad964a598c464ef8d8864d61a7cdc535e223c4dad946c38a83e2d064127c

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=sha256:60f47aca5f2cff5a9ddbb5ff27663e5a1208fd76f42bdd38c688dfc7711cce81

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=sha256:8165181cbff8ff457ac1f8fbf06a6c45ed8ff5a6f39e4f4f3ce92498343a04f2

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

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:12:02.479204Z digest=sha256:60e40d17371d7da20b141434ba26f86ecd0eb4cacd0251f9903d279e58a3b6aa

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:12:02.641880Z digest=sha256:a8fbd1430aa7c495a58525d470a04bacd9445e78d13685e9516d093e1bc71edf

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:12:02.766229Z digest=sha256:bace8a773ba88e23f38c8c8ff4c7391e7647c732338922f9fd2dc129e6627be2

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:12:02.916848Z digest=sha256:b39cbc3df867fe9550536fcb52bebb68062082f83f3c55721266dc12530a35f3

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:feba62d21e9cb141f601dde0681fcdeaf61c668218b796329daabb1ba792d395

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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source=pdf_text observed=2026-08-06T16:12:03.116125Z digest=sha256:86ab44f469039aea7bbb1b1312f78dc16e9e91019f76ee6a319bcf2fce90a105

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:12:03.272897Z digest=sha256:e5e189db44cf2f225fa764f0ddf339837ea801715e8f35c38a5093944b01bd63

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:ce7f3d67cde8db2462c946eb7035d76632de7863389202710adfe8973fedd53a

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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verified exact
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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:12:03.638856Z digest=sha256:6c7862e2646b1db636381eb7830612e8e188b3fc8bbe1bda26cfd58e1500883b

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:12:03.811310Z digest=sha256:15efa626505af55abff865dee4d468784a1a97ee61be8107de92f98279c777a3

Pith citing papers

No inbound Pith citation observations are available.