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Paper Citation Record · LEDGER

Diversity Enhances an LLM's Performance in RAG and Long-context Task

As of 19 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 4 inbound Pith citation observations for arXiv:2502.09017.

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

pith.paper-citation-record.v1
2502.09017 v2

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T22:56:35.034208Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T17:18:31.652267Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T14:08:22.087003Z

Reference resolution

41 of 41 outbound references displayed

  • verified exact0
  • verified fuzzy17
  • unresolved24
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2ebcca3f-fe93-4cb5-85e1-eee3aa97ea99 · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:56:34.896039Z digest=sha256:b17c8a6e7a0baa1ee4622ad6fec4e1748231042371e94b23ab3eac974380a244

Observation 28f788b3-9c10-4ee2-97d9-73c3fe6fb9db · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding, 2019.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Bert: Pre-training of deep bidirectional transformers for language understanding, 2019

Reference 2

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source=pdf_text observed=2026-08-07T22:56:34.900460Z digest=sha256:3fc2bc868f95a4346c4b61dbb5b764397fe650f228d72174e4868038bd06a2d7

Observation b353f7f3-7a56-4e5a-beb6-080ce8ceab9f · outbound

This paper cites an unresolved cited work.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Unresolved cited work

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T22:56:34.904468Z digest=sha256:3af1211345f72e38e4713698b22766acce788e6533d5e78d688162a841fb2040

Observation 84ec7db6-12da-4edf-9107-8694206c6513 · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive nlp tasks, 2021.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Retrieval-augmented generation for knowledge-intensive nlp tasks, 2021

Reference 4

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source=pdf_text observed=2026-08-07T22:56:34.908887Z digest=sha256:cffc566f069d4d4923f1d5652938471ae0d2259f6e6e1049acb1cdbaef107677

Observation 41a92491-754a-443f-8e96-ac5f3fa3ce91 · outbound

This paper cites Mamba: Linear-time sequence modeling with selective state spaces, 2024.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Mamba: Linear-time sequence modeling with selective state spaces, 2024

Reference 5

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source=pdf_text observed=2026-08-07T22:56:34.913220Z digest=sha256:f02b791b97d90bad6e4869e4eff78b2d586ef6847c6c091af40ace09921a9cdb

Observation 86b4732b-f959-490f-9e7c-f8eed77012bb · outbound

This paper cites an unresolved cited work.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Unresolved cited work

Reference 6

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no resolver link, observed 2026-08-07T22:56:34.917354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:56:34.917354Z digest=sha256:4239a67c0fbcbc92092de6817fce6b4961c3fbf04bb1e730405bf94208ad6324

Observation ca082191-7f1f-45fb-ac92-accef59ba82e · outbound

This paper cites Peters, and Arman Cohan.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Peters, and Arman Cohan

Reference 7

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source=pdf_text observed=2026-08-07T22:56:34.921605Z digest=sha256:dfb0e0c6c2c7052df737f66088c386ee23e4434665e9c4e914b532988fdc519d

Observation d0b6f95b-1c89-4d0b-b5be-2ac72af703a8 · outbound

This paper cites Llm maybe longlm: Self-extend llm context window without tuning, 2024.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Llm maybe longlm: Self-extend llm context window without tuning, 2024

Reference 8

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T22:56:34.925280Z digest=sha256:5e80269006b8358375c4ba6c624544fcd58f1d3de8b9b9dd21b2ecb09e59a444

Observation 31c779e4-476c-4bae-ba5c-f3ba921dff58 · outbound

This paper cites The use of mmr, diversity-based reranking for reordering documents and producing summaries.

Diversity Enhances an LLM's Performance in RAG and Long-context Task The use of mmr, diversity-based reranking for reordering documents and producing summaries

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-07T22:56:35.356793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T22:56:34.928930Z digest=sha256:d0e8d680fb078b8294efb273d978dcdc19cd059f3607a0f1d8f1baf024ef5c5c

Observation b3143d12-6d17-4267-9123-fef1ae7cb786 · outbound

This paper cites Qi, Li Yi, Hao Su, and Leonidas J.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Qi, Li Yi, Hao Su, and Leonidas J

Reference 10

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T22:56:34.932619Z digest=sha256:284c0859415a924027be5734466be1ad4103bb08d4a22f010406ec21a0bc9a6f

Observation 8179d864-716e-469b-9083-bcdb1f60d6fc · outbound

This paper cites Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang

Reference 11

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source=pdf_text observed=2026-08-07T22:56:34.936039Z digest=sha256:27e6216c5db469843f93c1ff36fcb2acece25e1506820aeb3f22a50aa4a0c3ce

Observation cd3bd0b0-d3a7-4398-9fa3-233630d5c709 · outbound

This paper cites ROUGE: A package for automatic evaluation of summaries.

Diversity Enhances an LLM's Performance in RAG and Long-context Task ROUGE: A package for automatic evaluation of summaries

Reference 12

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T22:56:34.940344Z digest=sha256:4cf8c2afc1a649199228ea9a9d97789479e2d7327fc71f2a107991e92b338ba9

Observation a3a149f2-f13b-408c-acc6-89536b73df87 · outbound

This paper cites Hsu, James Zhu, Zhichao Wang, Bin Bi, Shubham Mehrotra, Shiva K.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Hsu, James Zhu, Zhichao Wang, Bin Bi, Shubham Mehrotra, Shiva K

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:56:35.326313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T22:56:34.944268Z digest=sha256:29196bebfcf85a499c158d54c67f02190dd1b380a6e5038293a40701130b81da

Observation 62a8d15a-1714-46f9-b442-e9138e498e7e · outbound

This paper cites Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov

Reference 14

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raw_fallback, observed 2026-08-07T22:56:35.315521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T22:56:34.947693Z digest=sha256:d7163e37be18f2cd9eaa30acaa68c92e90e41b9f9d1355323d84d0006b02110a

Observation 854237af-9d14-4250-9dbd-a42aff1eb669 · outbound

This paper cites Weld, and Luke Zettlemoyer.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Weld, and Luke Zettlemoyer

Reference 15

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source=pdf_text observed=2026-08-07T22:56:34.951256Z digest=sha256:17e893ce4e29233d7bf48511a81d086d10ff67f36afc653ef4831489ca631ddc

Observation d50e99e8-c873-4983-a2f1-57bf140f7221 · outbound

This paper cites The narrativeqa reading comprehension challenge, 2017.

Diversity Enhances an LLM's Performance in RAG and Long-context Task The narrativeqa reading comprehension challenge, 2017

Reference 16

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raw_fallback, observed 2026-08-07T22:56:35.299569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T22:56:34.954684Z digest=sha256:790a960feea0de3e189f64c214254a31a07ec85272f8d587b50b2b560de95d5e

Observation fc16b187-f4f2-427c-928e-06ac891e38e0 · outbound

This paper cites spaCy: Industrial-strength Natural Language Processing in Python.

Diversity Enhances an LLM's Performance in RAG and Long-context Task spaCy: Industrial-strength Natural Language Processing in Python

Reference 17

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T22:56:34.958056Z digest=sha256:262709af4b0b833dc52f2d3c6cd9b8a3fe84e19e695762dba714efa89f6c3106

Observation 5285ae11-74d3-419c-9602-c1ca5527842b · outbound

This paper cites Sentence-bert: Sentence embeddings using siamese bert-networks, 2019.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Sentence-bert: Sentence embeddings using siamese bert-networks, 2019

Reference 18

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source=pdf_text observed=2026-08-07T22:56:34.961561Z digest=sha256:08087559210327f796b27bfb2eb93f96fdb16d547942f294ef099bb4d0722d2d

Observation 0b8c6130-4d16-45e4-a8a8-90b298484945 · outbound

This paper cites Text embeddings by weakly-supervised contrastive pre-training, 2024.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Text embeddings by weakly-supervised contrastive pre-training, 2024

Reference 19

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source=pdf_text observed=2026-08-07T22:56:34.964925Z digest=sha256:c41fd9468fd796b42e9b5fd9b0052845140bfa39d883fe93745b4b336a9e09f2

Observation 7f23b556-1e8d-42dc-b815-ec72e5666173 · outbound

This paper cites Principal components analysis (pca).

Diversity Enhances an LLM's Performance in RAG and Long-context Task Principal components analysis (pca)

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T22:56:34.968498Z digest=sha256:01fd3b62538b84a7e091a8027380bf39ef42fda64d677e8010b2aa88d6e4ad08

Observation 40285305-512d-4ec9-a198-b29853adbba2 · outbound

This paper cites Pattern recognition and machine learning, volume 4.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Pattern recognition and machine learning, volume 4

Reference 21

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source=pdf_text observed=2026-08-07T22:56:34.971937Z digest=sha256:b707f0493ce9dc52f9ce89b35e95cc148607665711dabe0849750eef706cf284

Observation 7eba9cf7-ed10-4c9e-bfcf-e5336635d545 · outbound

This paper cites Efficient attentions for long document summarization, 2021.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Efficient attentions for long document summarization, 2021

Reference 22

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source=pdf_text observed=2026-08-07T22:56:34.975339Z digest=sha256:93c64c6db61acbdd1754541cec87927f9502b2753002411334734208ed4ace02

Observation 861ee822-c52d-43b8-8705-0a4abd758404 · outbound

This paper cites Legal case document summarization: Extractive and abstractive methods and their evaluation, 2022.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Legal case document summarization: Extractive and abstractive methods and their evaluation, 2022

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T22:56:34.978952Z digest=sha256:8095b3c018025cb4605bcf913b561955bea07c4eb35b1be7f581e294daa99964

Observation eb95feb1-e2fb-47f7-9dc4-2c724affd523 · outbound

This paper cites an unresolved cited work.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Unresolved cited work

Reference 24

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source=pdf_text observed=2026-08-07T22:56:34.982580Z digest=sha256:b28e85e6fe984dbe827d161e965f4fddebe977fd795dbb045818514b32bd84e8

Observation b1e51ccd-35c7-4bb4-9ebf-44d9fbf21682 · outbound

This paper cites Smith, and Mike Lewis.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Smith, and Mike Lewis

Reference 25

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source=pdf_text observed=2026-08-07T22:56:34.985991Z digest=sha256:100292132417c2202700b47414b8c0d52bdc32cd01a384b461bd5aae988fe896

Observation 5ca28333-025f-4c04-8602-4a2c6517a0ac · outbound

This paper cites An empirical survey on long document summarization: Datasets, models, and metrics.

Diversity Enhances an LLM's Performance in RAG and Long-context Task An empirical survey on long document summarization: Datasets, models, and metrics

Reference 26

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raw_fallback, observed 2026-08-07T22:56:35.221216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T22:56:34.989432Z digest=sha256:ebb9ab7b18573432c4efcefb77d881f0eec3c77d0f12bec0def74ba2741d2b35

Observation d77d3187-f623-4cd8-8600-b31d9615a38c · outbound

This paper cites From local to global: A graph rag approach to query-focused summarization, 2025.

Diversity Enhances an LLM's Performance in RAG and Long-context Task From local to global: A graph rag approach to query-focused summarization, 2025

Reference 27

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source=pdf_text observed=2026-08-07T22:56:34.992977Z digest=sha256:bc1a6c85c509a355b6b48e113dd12541b9d3ed7ac55c6f6de5111c2fc1ca0e23

Observation dee09e63-8855-4129-8b5f-78af27314ba9 · outbound

This paper cites Corrective retrieval augmented generation, 2024.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Corrective retrieval augmented generation, 2024

Reference 28

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source=pdf_text observed=2026-08-07T22:56:34.996206Z digest=sha256:fc77f7b5feb0a166a9f194e796330909696b49344d35c046723dd5a186db08ef

Observation 9c7740ef-7e7c-4e1f-9b0f-e1651a61aae6 · outbound

This paper cites an unresolved cited work.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Unresolved cited work

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T22:56:34.999802Z digest=sha256:ce2747cbacae97c6cb76070780fd818952fbeb4f6191102eae4282faf1174780

Observation edb62e4c-6c48-4d73-9818-c4c695883ac2 · outbound

This paper cites Modular rag: Transforming rag systems into lego-like reconfigurable frameworks, 2024.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Modular rag: Transforming rag systems into lego-like reconfigurable frameworks, 2024

Reference 30

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raw_fallback, observed 2026-08-07T22:56:35.183321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T22:56:35.003153Z digest=sha256:d081932818edb3dbed5849e9cbd06ab657947adef179ecfcd753a14b244f0d73

Observation 27506480-9723-4fc9-b08f-39f0a3b508e4 · outbound

This paper cites Vasarhelyi.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Vasarhelyi

Reference 31

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raw_fallback, observed 2026-08-07T22:56:35.172569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T22:56:35.005831Z digest=sha256:748d7e278f6d5ebf2b350daaf77cab574e91a8977d3a4be7affca058ec219a31

Observation bfb9132e-79c2-4a33-9067-623793629eb9 · outbound

This paper cites Improving unsupervised extractive summarization with facet-aware modeling.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Improving unsupervised extractive summarization with facet-aware modeling

Reference 32

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verified fuzzy
raw_fallback, observed 2026-08-07T22:56:35.161847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T22:56:35.008700Z digest=sha256:1dfd6f21cd7beccbefcb089cc4814cff4f0d0a9c1a802164cef4436c0b4d58af

Observation 8b627de9-651c-4f41-858d-d132fa29041f · outbound

This paper cites Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension, 2019.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension, 2019

Reference 33

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:56:35.011555Z digest=sha256:7c669ec3342ddc058c48210f8a65b2703ccf75c6ce43aa21f24cfa1070118418

Observation ce4d1f7a-0b1d-4209-ab28-20d9bf08d8ff · outbound

This paper cites an unresolved cited work.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Unresolved cited work

Reference 34

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source=pdf_text observed=2026-08-07T22:56:35.014478Z digest=sha256:d07b62b77c623e606298ed0403c7a2120413840575e2a58aa077f43965f13485

Observation 7d98181c-5c12-4ae6-a292-953f855c89af · outbound

This paper cites Preserve context information for extract-generate long-input summarization framework.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Preserve context information for extract-generate long-input summarization framework

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:56:35.137491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T22:56:35.017164Z digest=sha256:ba4c1c52db8dee819252d21671af76229857e849e4cbc0911c059d895717e06a

Observation 6903ef02-7cbd-493e-b8ec-fc31ff9788ae · outbound

This paper cites Gretel: Graph contrastive topic enhanced language model for long document extractive summarization, 2022.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Gretel: Graph contrastive topic enhanced language model for long document extractive summarization, 2022

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:56:35.126303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T22:56:35.019902Z digest=sha256:7c0bb8d98dd38d06a947e28ae3198edd91bf9f0a5323db92197736d7eb152e96

Observation 3dc92848-fda2-4323-9855-657ab16568c4 · outbound

This paper cites Improving multi-stage long document summarization with enhanced coarse summarizer.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Improving multi-stage long document summarization with enhanced coarse summarizer

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:56:35.114307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T22:56:35.022829Z digest=sha256:3fb61bb15940a8e5a2e0b792d5da1f115505518458273a2364ed9bb0fc9521f4

Observation 9414a4a9-2c00-4533-8035-6562200e83e3 · outbound

This paper cites Aragog: Advanced rag output grading, 2024.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Aragog: Advanced rag output grading, 2024

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:56:35.102848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T22:56:35.025525Z digest=sha256:a9f43867d9233c58aedc672452addf09b70ab2646342199fe26b198d7e7d39ca

Observation dfb5b83f-231e-4bda-aad5-89f191607413 · outbound

This paper cites Better rag using relevant information gain, 2024.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Better rag using relevant information gain, 2024

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:56:35.090723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T22:56:35.028286Z digest=sha256:f5254c9b2debf648c4d6bc98d803068948d1eaf1d791757391ec59414e59cee5

Observation 8d0ec22e-b4b7-413d-93da-338136839017 · outbound

This paper cites Deberta: Decoding-enhanced bert with disentan- gled attention, 2021.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Deberta: Decoding-enhanced bert with disentan- gled attention, 2021

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:56:35.079373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T22:56:35.031359Z digest=sha256:45f9442a3359a26e1444993fb6a54338bdb16a697c3542526568010e7abffd42

Observation 7adb7e25-dcfb-42e7-acaf-77c2c0781bce · outbound

This paper cites Dense passage retrieval for open-domain question answering, 2020.

Diversity Enhances an LLM's Performance in RAG and Long-context Task Dense passage retrieval for open-domain question answering, 2020

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T22:56:35.067387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T22:56:35.034208Z digest=sha256:efe1efb6557ee2b89ed29c8b1cb4a233001597bc0c4d88f0bb1f7ea2e9f34ed2

Pith citing papers

Observation da496169-3c93-422c-9c62-298d5d57e0a3 · inbound

Culinary Crossroads: A RAG Framework for Enhancing Diversity in Cross-Cultural Recipe Adaptation cites this paper.

Culinary Crossroads: A RAG Framework for Enhancing Diversity in Cross-Cultural Recipe Adaptation Diversity Enhances an LLM's Performance in RAG and Long-context Task

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-19T02:21:59.228993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-19T02:20:03.766702Z digest=sha256:45e0e272c722922137c50b004c19d43d97e11d22d5f4b9567c42aa7c11c12283

Observation a833dd31-c0df-451f-8a53-54e6e381f664 · inbound

GPL-SLAM: A Laser SLAM Framework with Gaussian Process Based Extended Landmarks cites this paper.

GPL-SLAM: A Laser SLAM Framework with Gaussian Process Based Extended Landmarks Diversity Enhances an LLM's Performance in RAG and Long-context Task

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-05T17:18:31.652267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:18:31.652267Z digest=sha256:de80261414bad0a29fe527a4535d06c4cfbb4f87c9a6d916c2167c76b79a0232

Observation 6ad617d8-bee4-4c37-a97e-9fdf74dd8be2 · inbound

Search for Coverage: Learning Coverage-Aware Retrieval with Augmented Sub-Question Answerability cites this paper.

Search for Coverage: Learning Coverage-Aware Retrieval with Augmented Sub-Question Answerability Diversity Enhances an LLM's Performance in RAG and Long-context Task

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-06-29T09:53:17.505959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T09:47:15.978952Z digest=sha256:f63435367d67cf3cbd0f77a4f969b5d8879fb753b7acc74c0f06fd291d69d8ec

Observation ffa35b8d-278f-4392-8bc1-f65e02e21b9f · inbound

How Fine-Grained Should a RAG Benchmark Be? A Hierarchical Framework for Synthetic Question Generation cites this paper.

How Fine-Grained Should a RAG Benchmark Be? A Hierarchical Framework for Synthetic Question Generation Diversity Enhances an LLM's Performance in RAG and Long-context Task

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-07-03T14:08:22.092022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-27T07:12:41.103643Z digest=sha256:dd8b095ade7542567ded5fb11cbd280afc93a4dddb9a8c7d3c051c70d945f85c