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Paper Citation Record · LEDGER

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions

As of 22 August 2026, this Paper Citation Record lists 100 of 107 outbound references and 8 inbound Pith citation observations for arXiv:2507.18910.

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

pith.paper-citation-record.v1
2507.18910 v1

Coverage vector

measured 100 of 107 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:08:11.910058Z

measured 108 of 108 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T08:13:27.519293Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

100 of 107 outbound references displayed

  • verified exact2
  • verified fuzzy33
  • unresolved65
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

5
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation d5e68c2b-abd4-4f8d-a1c9-cfae25e05d5c · outbound

This paper cites RAGAR, Your Falsehood Radar: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions RAGAR, Your Falsehood Radar: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models

Reference 1

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source=pdf_text observed=2026-08-15T18:08:11.524035Z digest=sha256:8e9c317cab45248b16a7dcd3cde6345254229568207f56c29f506e709600f120

Observation 760d0dcf-e035-46b0-b692-ff3491a0474a · outbound

This paper cites Cbr-rag: Case-based reasoning for retrieval augmented generation in llms for legal question answering.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Cbr-rag: Case-based reasoning for retrieval augmented generation in llms for legal question answering

Reference 2

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source=pdf_text observed=2026-08-15T18:08:11.529070Z digest=sha256:88e1af3e931462be519e3cc7b52d726079a5ccf612dc16e9bd75b70b83b0fb1b

Observation a87ce445-62f7-4bf1-9f9a-78ccd0bce215 · outbound

This paper cites FACTS About Building Retrieval Augmented Generation-based Chatbots.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions FACTS About Building Retrieval Augmented Generation-based Chatbots

Reference 3

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source=pdf_text observed=2026-08-15T18:08:11.533271Z digest=sha256:5ea203d4be36d98a4fd31c66b90507e54f677118a13fb099f2e38eb2600f028b

Observation 1f25f95a-e51f-43de-af07-5e9c18504f7e · outbound

This paper cites HyperRAG: Enhancing Quality-Efficiency Tradeoffs in Retrieval-Augmented Generation with Reranker KV-Cache Reuse.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions HyperRAG: Enhancing Quality-Efficiency Tradeoffs in Retrieval-Augmented Generation with Reranker KV-Cache Reuse

Reference 4

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local_arxiv, observed 2026-08-15T18:08:12.619966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.537767Z digest=sha256:0f63bef3db91e3a3588c2da76ccf253ffff10a2d2906c4d9c9db3a302f9438f3

Observation 8d3b5034-34da-4f7f-b9fa-19be62bcfa71 · outbound

This paper cites Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection

Reference 5

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source=pdf_text observed=2026-08-15T18:08:11.542222Z digest=sha256:1b38fdf89c0777e363e46369708bfb6133705e85a179c790244aa3c8ee6e8a02

Observation 881b0696-0271-4f3b-89a6-6a05c67918d2 · outbound

This paper cites Self-rag: Learning to retrieve, generate, and critique through self-reflection.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Self-rag: Learning to retrieve, generate, and critique through self-reflection

Reference 6

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source=pdf_text observed=2026-08-15T18:08:11.546651Z digest=sha256:3e303874426fbbdae543945ba3a3df8d532872765c0b922830c1679d23b54bdb

Observation 738e776d-3d03-47e2-a5f2-94abbf9cdd5a · outbound

This paper cites Bias on the web.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Bias on the web

Reference 7

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source=pdf_text observed=2026-08-15T18:08:11.552139Z digest=sha256:cf2f26a147e3b2b89a2ee42e569655a2580e315359989f44ca4a29618a959825

Observation 47d9c750-c592-44f1-b771-5baa6692c517 · outbound

This paper cites Leveraging approximate caching for faster retrieval-augmented generation.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Leveraging approximate caching for faster retrieval-augmented generation

Reference 8

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source=pdf_text observed=2026-08-15T18:08:11.556033Z digest=sha256:d515a858d50529ca7ae2862d87c1735a58dd8368b24198dedde97b0371cc92bf

Observation b29999d3-f89f-4f7a-a508-8debce5ff7f7 · outbound

This paper cites Improving language models by retrieving from trillions of tokens.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Improving language models by retrieving from trillions of tokens

Reference 9

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source=pdf_text observed=2026-08-15T18:08:11.559742Z digest=sha256:5211b069b2d46c2c95d6d0c76e1e7bf698aeebbd06da53e2c1531be9a6bd7b4f

Observation db3f5723-facc-4478-aa87-deef898578b2 · outbound

This paper cites Rae, Erich Elsen, and Laurent Sifre.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Rae, Erich Elsen, and Laurent Sifre

Reference 10

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source=pdf_text observed=2026-08-15T18:08:11.564813Z digest=sha256:5bdbac2e00bacc9efbac3a4b813dbefb75f2039b598dff05926d3166937c6981

Observation 3033c66c-e2f2-4df3-8526-6767ea83e6b3 · outbound

This paper cites Ai doesn’t know much about golf.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Ai doesn’t know much about golf

Reference 11

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source=pdf_text observed=2026-08-15T18:08:11.568848Z digest=sha256:1aebaa79a3a7c3b8df2f61f3465b99c8876ec86d5478a948917b49f7912a0872

Observation c1049a54-4ed6-4c07-8b90-fe0665934d9b · outbound

This paper cites Reading wikipedia to answer open-domain questions.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Reading wikipedia to answer open-domain questions

Reference 12

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source=pdf_text observed=2026-08-15T18:08:11.572638Z digest=sha256:407d9dcc1aa08267589df474337ff13cdf432e95f719c8f43efc838f02988b01

Observation 2d4a9887-0078-4468-83f9-642931977d40 · outbound

This paper cites Benchmarking large language models in retrieval-augmented generation.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Benchmarking large language models in retrieval-augmented generation

Reference 13

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source=pdf_text observed=2026-08-15T18:08:11.576459Z digest=sha256:128e52d5953c3815d1fde2039f73fdfec2c2a90e37c688fc6016d6f6818188c2

Observation 9c10ee76-3186-4438-adb7-29636abe5397 · outbound

This paper cites Retrieval-augmented generation with knowledge graphs: A survey.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Retrieval-augmented generation with knowledge graphs: A survey

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.580377Z digest=sha256:c327e9df7af7bf6a715b03e2880987cfa7386e0e401d80bb3bd2b9aac470aa4f

Observation 59922472-716b-48c4-a3dc-f6f8a29467b9 · outbound

This paper cites Bridging the gap between prior and posterior knowledge selection for knowledge-grounded dialogue generation.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Bridging the gap between prior and posterior knowledge selection for knowledge-grounded dialogue generation

Reference 15

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source=pdf_text observed=2026-08-15T18:08:11.584290Z digest=sha256:e5670fb21c4842912e3b25ee3cb163540dfda7db485b7f0dcaa961e33cf9d56e

Observation 98e3ebdc-b702-4cab-824f-eadea3631007 · outbound

This paper cites Lift yourself up: Retrieval-augmented text generation with self-memory.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Lift yourself up: Retrieval-augmented text generation with self-memory

Reference 16

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source=pdf_text observed=2026-08-15T18:08:11.588134Z digest=sha256:1d5aeb2f2c7f023581e9ad7a23a31f030c7f6d01a0e94c7949e5e1a6060c0b80

Observation 299f4431-f24d-479c-ba4a-d91bd4930e68 · outbound

This paper cites Two-layer retrieval-augmented generation framework for low-resource medical question answering using reddit data: Proof-of-concept study.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Two-layer retrieval-augmented generation framework for low-resource medical question answering using reddit data: Proof-of-concept study

Reference 17

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source=pdf_text observed=2026-08-15T18:08:11.592456Z digest=sha256:ba1f37df3f17a2c6297cd17962952672c63d2069d2e947d72315793b79b87b3f

Observation b3d84009-e711-4eab-b84e-26784c5a7a78 · outbound

This paper cites Wizard of wikipedia: Knowledge-powered conversational agents.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Wizard of wikipedia: Knowledge-powered conversational agents

Reference 18

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source=pdf_text observed=2026-08-15T18:08:11.596743Z digest=sha256:0ca08ccdae579c96b739b6fa70d969fce88186fb1a42488311c32faccfc7e910

Observation 61e8f900-cd69-416a-be3b-842eff11e975 · outbound

This paper cites A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models

Reference 19

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source=pdf_text observed=2026-08-15T18:08:11.600915Z digest=sha256:e3028cca639765c7f0ffa92f9380b50386a7689ea4760c3ea1d8f6492b649c0d

Observation 207c8af1-d628-42b5-8e41-d69519a77ad5 · outbound

This paper cites ARAGOG: Advanced RAG Output Grading.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions ARAGOG: Advanced RAG Output Grading

Reference 20

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source=pdf_text observed=2026-08-15T18:08:11.605442Z digest=sha256:e39a264143ed7a6a0983edf45097c25633c9f1c373466c74a71a813b10a03573

Observation e354ca23-a244-43d4-9094-6feb6b7e8087 · outbound

This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 21

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source=pdf_text observed=2026-08-15T18:08:11.609402Z digest=sha256:40d5d35f79df3de4a140547947eb788c0e3a790ba6eed3ee6fcb495fdfc0dd89

Observation 0730a9c9-985e-445f-9ace-8688785e7c67 · outbound

This paper cites Kather, and Aidan Hogan.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Kather, and Aidan Hogan

Reference 22

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source=pdf_text observed=2026-08-15T18:08:11.613588Z digest=sha256:b06d20339edf5d2ffcecaef269a3ed76960644ec6c247793ccdefb48835fac71

Observation 795becc4-00ff-4151-8b70-8838c7894aec · outbound

This paper cites Cpr: Retrieval augmented generation for copyright protection.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Cpr: Retrieval augmented generation for copyright protection

Reference 23

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source=pdf_text observed=2026-08-15T18:08:11.617249Z digest=sha256:adbec298462aff859b129e72ae703141ecb088f05cb04301a5244401a3075d4c

Observation 98113bea-f8f0-478d-a5e4-2ad40684b221 · outbound

This paper cites Structugraphrag: Structured document-informed knowledge graphs for retrieval-augmented generation.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Structugraphrag: Structured document-informed knowledge graphs for retrieval-augmented generation

Reference 24

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source=pdf_text observed=2026-08-15T18:08:11.621077Z digest=sha256:80439b879f7ca489ab81089cff08b7641a725e9bc167e72cfb833b68f989e337

Observation 170a8f5e-81c1-46d0-839a-e8e34b05dd45 · outbound

This paper cites REALM: Retrieval-augmented language model pre-training.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions REALM: Retrieval-augmented language model pre-training

Reference 25

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source=pdf_text observed=2026-08-15T18:08:11.625212Z digest=sha256:47b6fcc65614f39e4b92a25421692e02eae8f3125765420a0af5156c0086cd34

Observation cf659129-7e27-497f-8ea1-b2197b4e8228 · outbound

This paper cites Retrieval-augmented language model pre-training.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Retrieval-augmented language model pre-training

Reference 26

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source=pdf_text observed=2026-08-15T18:08:11.629340Z digest=sha256:406396334315c257b76d519f2dbce906c5afb729a494d360429120673583b5d2

Observation e7781396-bfec-4ffd-81cb-741feda1b153 · outbound

This paper cites A survey on largelanguagemodels: Applications, challenges, limitations, and practical usage.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions A survey on largelanguagemodels: Applications, challenges, limitations, and practical usage

Reference 27

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source=pdf_text observed=2026-08-15T18:08:11.633345Z digest=sha256:064407b88f912491a92108add43b4e74ab8f18428adabd74febfefb7ac6ce27f

Observation a3b9e255-d40b-4a4f-bc1b-4d16cb478e0c · outbound

This paper cites an unresolved cited work.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Unresolved cited work

Reference 28

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source=pdf_text observed=2026-08-15T18:08:11.637504Z digest=sha256:332cca99657fa4825f59f2c52845b849dfea20566d2f199a547b5ca121a5a614

Observation 50ca63d5-b7f1-4c4f-8021-8be31cf67d43 · outbound

This paper cites Retrieval-Augmented Generation with Graphs (GraphRAG).

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Retrieval-Augmented Generation with Graphs (GraphRAG)

Reference 29

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source=pdf_text observed=2026-08-15T18:08:11.641262Z digest=sha256:5080a472479b515dfac5a73c59f0f19ec686762ad788f4066fb61d860742690c

Observation cdac5560-674f-42ac-b222-3e612e04fdf6 · outbound

This paper cites Knowledge updating? no more model editing! just selective contextual reasoning.Journal of the ACM, 2025.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Knowledge updating? no more model editing! just selective contextual reasoning.Journal of the ACM, 2025

Reference 30

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source=pdf_text observed=2026-08-15T18:08:11.645453Z digest=sha256:74a502bc58c8e217872f80fa081740f477486a1cd6a2d359254b7057fd731e8f

Observation f98d436d-4fa4-438e-b311-b858c0961d4b · outbound

This paper cites G-retriever: Retrieval-augmented generation for textual graph understanding and question answering.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions G-retriever: Retrieval-augmented generation for textual graph understanding and question answering

Reference 31

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source=pdf_text observed=2026-08-15T18:08:11.649726Z digest=sha256:9d097424945466afb66022a2c599fb8df9e1c91513f1f28ef323b66d3a1fb24f

Observation b6e55252-0016-43f0-826c-278a07501f57 · outbound

This paper cites What is rag (retrieval augmented generation)? IBM, 2023.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions What is rag (retrieval augmented generation)? IBM, 2023

Reference 32

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source=pdf_text observed=2026-08-15T18:08:11.653543Z digest=sha256:7ab3b296fb5ee6c1734c52e5610a0170243e1070b0af25179242ca18660b2e93

Observation 65a3e398-5236-4a50-9173-4ee777525953 · outbound

This paper cites What is retrieval-augmented generation? IBM Research Blog, 22 August 2023, 2023.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions What is retrieval-augmented generation? IBM Research Blog, 22 August 2023, 2023

Reference 33

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source=pdf_text observed=2026-08-15T18:08:11.657348Z digest=sha256:934acba463043f793d1f56eed1597ff0e4a443c58092b5d8e49799bbe2ea8f76

Observation c9a4de7f-ba62-40c3-bc30-bbba5f310a8e · outbound

This paper cites Leveraging passage retrieval with generative models for open domain question answering.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Leveraging passage retrieval with generative models for open domain question answering

Reference 34

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source=pdf_text observed=2026-08-15T18:08:11.662293Z digest=sha256:889af9cc4e04bbf682e03287cf1ad78c4034ebf8089b5df109caef7416e4b9a6

Observation 59678f3e-43ad-4db5-ba5c-3630507f3481 · outbound

This paper cites Atlas: Few-shot Learning with Retrieval Augmented Language Models.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Atlas: Few-shot Learning with Retrieval Augmented Language Models

Reference 35

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source=pdf_text observed=2026-08-15T18:08:11.665930Z digest=sha256:1e2b75db41f786cf969fbe6cc166bfe905e73107f50aaf4ec3baec895970a42b

Observation b7fe6452-1f73-4e2a-a139-d05b6b3c4a95 · outbound

This paper cites Atlas: Few-shot learning with retrieval augmented language models.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Atlas: Few-shot learning with retrieval augmented language models

Reference 36

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source=pdf_text observed=2026-08-15T18:08:11.669813Z digest=sha256:2b24e38917d8a40d33c31a0a40626229403c6bc68c08130c2e3b04bf0c187416

Observation 3e931fb4-2bf1-4d39-b8d4-10366cb82bbb · outbound

This paper cites Efficiently improving the performance of noisy quantum computers.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Efficiently improving the performance of noisy quantum computers

Reference 37

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source=pdf_text observed=2026-08-15T18:08:11.673786Z digest=sha256:673c9564b8e186972e536dd02f8e3ce11de72618f4e7fb4a1b5d85c6651a69d6

Observation 8ba83ade-929b-4de7-b602-18fcaa9689f5 · outbound

This paper cites Active retrieval augmented generation.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Active retrieval augmented generation

Reference 38

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source=pdf_text observed=2026-08-15T18:08:11.677574Z digest=sha256:c7a367889eeb7237a37eed2fc121ccc5d16bf9047045a7522deecdeab2cef943

Observation 9f326792-8ca7-4117-b08c-66265b0bcb60 · outbound

This paper cites Long-context llms meet rag: Overcoming challenges for long inputs in rag.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Long-context llms meet rag: Overcoming challenges for long inputs in rag

Reference 39

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source=pdf_text observed=2026-08-15T18:08:11.681644Z digest=sha256:8470d9d3e2e8f6b8052f949ee334719b17385d65616bc05eeeb5b07dce9b834f

Observation b267dbcf-0aa3-4e3d-b8b7-ebd512abfbd7 · outbound

This paper cites RAGCache: Efficient Knowledge Caching for Retrieval-Augmented Generation.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions RAGCache: Efficient Knowledge Caching for Retrieval-Augmented Generation

Reference 40

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source=pdf_text observed=2026-08-15T18:08:11.685607Z digest=sha256:686e9aa62589951e4a16c9101a7aaba9027a68b8516a667cf50894d1c2905b27

Observation af812147-0c42-4bd3-abe1-e9dc32a6ec26 · outbound

This paper cites Tug-of-war between knowledge: Exploring and resolving knowledge conflicts in retrieval-augmented language models.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Tug-of-war between knowledge: Exploring and resolving knowledge conflicts in retrieval-augmented language models

Reference 41

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source=pdf_text observed=2026-08-15T18:08:11.689576Z digest=sha256:ccbbf8956bc66d55c7c7596c55358926f25b88585cb199ca69dfdf31d39ea64c

Observation ac05539f-4d32-4c3f-859d-d1d5a3f2d495 · outbound

This paper cites Securing retrieval-augmented generation: Privacy risks and mitigation strategies.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Securing retrieval-augmented generation: Privacy risks and mitigation strategies

Reference 42

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source=pdf_text observed=2026-08-15T18:08:11.694030Z digest=sha256:d4229c297b42b2ec3134b9f2c214c6ba39fff8043f0354fd183f765032909683

Observation b4f1a8ea-eac1-4f45-ae51-c5ae1cfeca4b · outbound

This paper cites Knowledge Graph-Augmented Language Models for Knowledge-Grounded Dialogue Generation.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Knowledge Graph-Augmented Language Models for Knowledge-Grounded Dialogue Generation

Reference 43

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source=pdf_text observed=2026-08-15T18:08:11.697679Z digest=sha256:9f35170f116b891a4b19de564b1a0a080a3150f0a5239a6467f38f0044696b9c

Observation 90567d32-1347-412f-b01d-e83a4a0267fc · outbound

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

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Dense passage retrieval for open-domain question answering

Reference 44

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source=pdf_text observed=2026-08-15T18:08:11.701352Z digest=sha256:65f4cc78ce6fac9480da6f79861e16d29a2c9e95a56ccc3b93b5876dbce5960f

Observation c596ad56-643f-4de8-ac57-fcf1099e1e6c · outbound

This paper cites an unresolved cited work.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Unresolved cited work

Reference 45

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source=pdf_text observed=2026-08-15T18:08:11.704787Z digest=sha256:4cfb5bce73e357c97876b689876139203fc7902ad38af05da7b867e883a739d5

Observation c1c247a8-5637-4eb1-9673-ce55cd5f4678 · outbound

This paper cites Mitigating Bias in RAG: Controlling the Embedder.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Mitigating Bias in RAG: Controlling the Embedder

Reference 46

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source=pdf_text observed=2026-08-15T18:08:11.708799Z digest=sha256:d08e474f061ad4639171d711121056f6a0c2586d1da18c909ec7aa5ec9c8afba

Observation bf1be1f4-0ffa-4537-95cc-db5a8a0f7507 · outbound

This paper cites Retrieval-augmented generation for dialog modeling.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Retrieval-augmented generation for dialog modeling

Reference 47

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.712271Z digest=sha256:99fc98423e4645565fdb5964bfea5fc08ad5fb8f4a9acd5e69ca0d9a2dfd9490

Observation 63022432-0111-4a09-91a2-a702b78ae173 · outbound

This paper cites Latent retrieval for weakly supervised open domain question answering.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Latent retrieval for weakly supervised open domain question answering

Reference 48

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source=pdf_text observed=2026-08-15T18:08:11.715701Z digest=sha256:9b25007ddd06e7591c9cad23ddc95559803e9eaa47a23022f6543b2231c941a5

Observation 17b276d3-c985-450a-b483-db3cb07acebb · outbound

This paper cites Pre-training via Paraphrasing.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Pre-training via Paraphrasing

Reference 49

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source=pdf_text observed=2026-08-15T18:08:11.719254Z digest=sha256:ce31b5bd7a6ea7c5e4e3793ffdcd0e1109362ecfe0ed1a3edf673048a01fee7c

Observation 07c04570-31ae-43ac-b318-a76395792542 · outbound

This paper cites Time100 ai 2024.Time, 2024.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Time100 ai 2024.Time, 2024

Reference 50

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.723264Z digest=sha256:132d2cf21a2c4a7a53865ad324f52195f2695b7a21005ccdcbb7e0a0f5aed38b

Observation 124d0d1d-b200-4136-8d1b-34d07c9887e8 · outbound

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

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Retrieval-augmented generation for knowledge-intensive nlp tasks

Reference 51

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.726869Z digest=sha256:c99f3331475dea3401be204d7e7ecf2a785d0784609d96975ee6aee0b32ea0cd

Observation 60f7f6b1-07dd-45f0-95f5-5fd5b372bc58 · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive NLP tasks.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Retrieval-augmented generation for knowledge-intensive NLP tasks

Reference 52

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.730293Z digest=sha256:6d47b56a1f6def0a0b0ff5d91305fcd8ed9029c2bfb9ebd642f392b467193272

Observation 03f6357a-5ad3-49f8-b731-be28712f54a9 · outbound

This paper cites Benchmarking Multimodal Retrieval Augmented Generation with Dynamic VQA Dataset and Self-adaptive Planning Agent.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Benchmarking Multimodal Retrieval Augmented Generation with Dynamic VQA Dataset and Self-adaptive Planning Agent

Reference 53

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source=pdf_text observed=2026-08-15T18:08:11.733682Z digest=sha256:3064ab03e31308b1c46e7c1a9a624248fd4e981e6eabc601a5df344a0927d65f

Observation 0ab0ab1d-2559-4f49-87e4-49eb689dc9d3 · outbound

This paper cites Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach

Reference 54

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source=pdf_text observed=2026-08-15T18:08:11.737000Z digest=sha256:06c8bf5f7ebd2bab91c3af2e517d86fec79b3a842fbe96ac7f8a25d394f8c041

Observation 88cab0ab-3e9d-46b8-9942-7615c5692e40 · outbound

This paper cites SafeRAG: Benchmarking Security in Retrieval-Augmented Generation of Large Language Model.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions SafeRAG: Benchmarking Security in Retrieval-Augmented Generation of Large Language Model

Reference 55

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source=pdf_text observed=2026-08-15T18:08:11.740656Z digest=sha256:9028ca276f63e332c0356f16ce6cbf0bd96c6c8a26d4840fefed462a414c9197

Observation d583181b-319f-44fa-bfa7-6b6405bbae99 · outbound

This paper cites Manning, and Daniel E.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Manning, and Daniel E

Reference 56

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source=pdf_text observed=2026-08-15T18:08:11.744166Z digest=sha256:76ae449f90ec3c6328efe758b1ce9069026958b75e584bc040fb691fc63fe661

Observation e69e1d31-2fd0-44da-a5cb-1b3e12ce2c42 · outbound

This paper cites an unresolved cited work.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Unresolved cited work

Reference 57

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source=pdf_text observed=2026-08-15T18:08:11.747439Z digest=sha256:a458b8a277b326966329732a51be63d3edc53819b8f669aa3bac9b1193a0089d

Observation 08556571-3fc0-423a-93ed-7ed57b97dc08 · outbound

This paper cites Federated Learning: Opportunities and Challenges.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Federated Learning: Opportunities and Challenges

Reference 58

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source=pdf_text observed=2026-08-15T18:08:11.750920Z digest=sha256:61be432546fbaac379db0dfb837bf4b96fce6fa187256448c2650ab0b378dd9b

Observation 8bfb1085-ea17-433e-9ecd-e6e9d901e0ed · outbound

This paper cites A Survey of Multimodal Retrieval-Augmented Generation.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions A Survey of Multimodal Retrieval-Augmented Generation

Reference 59

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source=pdf_text observed=2026-08-15T18:08:11.754274Z digest=sha256:fc1bfafe696d8148924fc2729e9abe56c97d453a6c3dd951882401cfe800f6b6

Observation 6ed0109a-82fe-46fe-8dec-7021894aad5d · outbound

This paper cites What is retrieval-augmented generation aka RAG? NVIDIA Blog, 15 November 2023, 2023.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions What is retrieval-augmented generation aka RAG? NVIDIA Blog, 15 November 2023, 2023

Reference 60

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source=pdf_text observed=2026-08-15T18:08:11.757737Z digest=sha256:668317560b0f763f1308a7e6b50016019e616be553cff5c64c7f7bc01e7b93a4

Observation 9bea9a9d-0e9c-4baf-8ef6-0a6c86573065 · outbound

This paper cites Garcia Valencia, and Wisit Cheungpasitporn.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Garcia Valencia, and Wisit Cheungpasitporn

Reference 61

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.760925Z digest=sha256:3d42c2994250d6138ae9d16fca4c53336526085d3f59a097801b21e6c51cd8dc

Observation 9d33534c-8eef-494e-8689-44806ab5ac90 · outbound

This paper cites WebGPT: Browser-assisted question-answering with human feedback.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions WebGPT: Browser-assisted question-answering with human feedback

Reference 62

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source=pdf_text observed=2026-08-15T18:08:11.764299Z digest=sha256:0baedd9a8b93bbd35b3bc4d27d60239f23320b15302a2dec81a77d12f67731c5

Observation 275cb859-7410-407c-92ce-1390fd7394b1 · outbound

This paper cites Passage re-ranking with bert.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Passage re-ranking with bert

Reference 63

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raw_fallback, observed 2026-08-15T18:08:12.971383Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.768395Z digest=sha256:6583ceb8d4ed38608d957fdcad96abeef49bd4edc389e90270580a45f6fa5500

Observation 8bce948d-4877-4d17-96a9-4c3a39dd776c · outbound

This paper cites Capabilities of GPT-4 on Medical Challenge Problems.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Capabilities of GPT-4 on Medical Challenge Problems

Reference 64

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source=pdf_text observed=2026-08-15T18:08:11.772361Z digest=sha256:f8d35d6d151479e6b1ef50d2907ed85a4ac3dee816a1458c4318a0e6619cf1b6

Observation cb8e9586-edcd-4d7c-aa30-b5063786efbf · outbound

This paper cites Activate your data with custom generative ai.NVIDIA, 2023.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Activate your data with custom generative ai.NVIDIA, 2023

Reference 65

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.775754Z digest=sha256:ced92b4a338180de1f549b3016e1ac9e9b22b99277520755d3d96bbf1aa7dcb9

Observation 99ffc450-b846-46a2-9104-7764839d4525 · outbound

This paper cites On the risk of misinformation pollution with large language models.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions On the risk of misinformation pollution with large language models

Reference 66

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raw_fallback, observed 2026-08-15T18:08:12.950120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.779349Z digest=sha256:06e0f470831099add84d62a4b741e6744e89dd5d104fed1d402331faf81a76e3

Observation fef12e61-f5a6-4bf1-b1bb-2a1536c175c4 · outbound

This paper cites Retrieval augmented code generation and summarization.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Retrieval augmented code generation and summarization

Reference 67

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raw_fallback, observed 2026-08-15T18:08:12.939658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.782751Z digest=sha256:d8bb1c2af9e5a52e2d8defa3ff758967d2d6e9bab9fea39ecfae8879197aa397

Observation b0c7a78e-07cf-4dac-9c2b-93e409f467cb · outbound

This paper cites KILT: a benchmark for knowledge intensive language tasks.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions KILT: a benchmark for knowledge intensive language tasks

Reference 68

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raw_fallback, observed 2026-08-15T18:08:12.928716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.785936Z digest=sha256:af5fedfc5367a7519623bcf8046fcc565f2d8c66263c6c4a18db468daf68d1ea

Observation 96e5e6d1-cffa-483f-ac3c-cd2f31db39e6 · outbound

This paper cites Kilt: a benchmark for knowledge intensive language tasks.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Kilt: a benchmark for knowledge intensive language tasks

Reference 69

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raw_fallback, observed 2026-08-15T18:08:12.918187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.789108Z digest=sha256:d35df8f1cad01276518d51608dbcda366ba661f7bde17986cf0aa0df4a97898c

Observation 9763e096-7386-43c7-9fa8-a8224a301de5 · outbound

This paper cites Ragnar\"ok: A Reusable RAG Framework and Baselines for TREC 2024 Retrieval-Augmented Generation Track.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Ragnar\"ok: A Reusable RAG Framework and Baselines for TREC 2024 Retrieval-Augmented Generation Track

Reference 71

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:08:11.796345Z digest=sha256:60ef0c765a08823bdc29b03b553b4dffc243c608d0d8270d81a22db5c040564f

Observation ef3d57aa-c65f-4a9c-81aa-40d95a22b673 · outbound

This paper cites Web application for retrieval-augmented generation: Implementation and testing.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Web application for retrieval-augmented generation: Implementation and testing

Reference 72

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.799985Z digest=sha256:85359e1052a08cf933185c973aeade148c85ec5504c40e44b9ebcba0b5c8e4d5

Observation 5894b6f4-1cf1-4317-aced-14aa2615171f · outbound

This paper cites an unresolved cited work.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Unresolved cited work

Reference 73

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.803641Z digest=sha256:6f283da76a34dbab4e03e9e71feb1394cb3e38d321227b531de5615175f08939

Observation 399f09e2-9efd-4836-9fb6-9af17b8bcdc2 · outbound

This paper cites Enterprise ai with retrieval-augmented generation.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Enterprise ai with retrieval-augmented generation

Reference 74

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raw_fallback, observed 2026-08-15T18:08:12.874673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.811379Z digest=sha256:49684e0b6fd9c2e45c568e6acf768c0fec181ea09ce6d87a9f3d2e2e502110a2

Observation d2e68308-7a41-4a83-be9e-4b07eca80250 · outbound

This paper cites How much knowledge can you pack into the parameters of a language model? InEMNLP, 2020.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions How much knowledge can you pack into the parameters of a language model? InEMNLP, 2020

Reference 75

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raw_fallback, observed 2026-08-15T18:08:12.864274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.815242Z digest=sha256:7c029d6786bd490a8ae4aadc3dba3ae87ede53b999ea94339bf74475e93f0ef7

Observation e149823a-f62d-4094-b560-baea7c623070 · outbound

This paper cites End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering

Reference 76

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no resolver link, observed 2026-08-15T18:08:11.818789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:08:11.818789Z digest=sha256:ad74d4af0c28da41019f7b9ded421ef1f9b4797e77a1394c742de58bd6c590b1

Observation b28f24fb-6f03-482f-8f60-00fb19e36082 · outbound

This paper cites Hamilton, Chris Dyer, and Dani Yogatama.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Hamilton, Chris Dyer, and Dani Yogatama

Reference 77

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raw_fallback, observed 2026-08-15T18:08:12.853656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.822597Z digest=sha256:fa79881bea147b27320cab5595df567d5114fd0e9b1bd547c3542affe6a2cc1c

Observation a4d964b6-a572-4ed7-a13a-03598acc4530 · outbound

This paper cites Evaluating retrieval quality in retrieval-augmented generation.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Evaluating retrieval quality in retrieval-augmented generation

Reference 78

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raw_fallback, observed 2026-08-15T18:08:12.843256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.825967Z digest=sha256:49f406d704d639244a454fc1b2ce8977b2a79c65d77f20c0e7480078d3911ca9

Observation 32459107-eb07-44c4-9ed6-d2e49410755f · outbound

This paper cites StreamingRAG: Real-time Contextual Retrieval and Generation Framework.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions StreamingRAG: Real-time Contextual Retrieval and Generation Framework

Reference 79

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no resolver link, observed 2026-08-15T18:08:11.830067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:08:11.830067Z digest=sha256:23d34f46fcb562974f9219f3afc1997988096604d71d7b89291bedc1e43c13b5

Observation 6d2baa0c-e384-428a-8e6c-36433811d94f · outbound

This paper cites BlenderBot 3: a deployed conversational agent that continually learns to responsibly engage.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions BlenderBot 3: a deployed conversational agent that continually learns to responsibly engage

Reference 80

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no resolver link, observed 2026-08-15T18:08:11.833502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:08:11.833502Z digest=sha256:367fef6efb3602e6833dd6464dd0a0f8f2ab38e52f3c5739ef10612568c2a745

Observation fad6b574-40d3-4444-b945-f7cdbc4a5c30 · outbound

This paper cites Language models that seek for knowledge: Modular search & generation for dialogue and prompt completion.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Language models that seek for knowledge: Modular search & generation for dialogue and prompt completion

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:08:12.832192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.837252Z digest=sha256:bd11cd4b928856da6a549c950302b9f873beb0f74b7be46d39757a7f0f74f447

Observation 65639980-9383-4056-980c-ae7b2465816f · outbound

This paper cites Retrieval augmentation reduces hallucination in conversation.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Retrieval augmentation reduces hallucination in conversation

Reference 82

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raw_fallback, observed 2026-08-15T18:08:12.821048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.840453Z digest=sha256:81b372ac8ea71fb0bdb030c5db9175d5c818695a793574c8b1fbb32feee16ebd

Observation 2c303275-7a3a-472f-bd8f-ffb73794fb1e · outbound

This paper cites Agentic Retrieval-Augmented Generation: A Survey on Agentic RAG.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Agentic Retrieval-Augmented Generation: A Survey on Agentic RAG

Reference 83

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no resolver link, observed 2026-08-15T18:08:11.843881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:08:11.843881Z digest=sha256:71bb83b823a0ee9dcb4c6d490166c160be69e40339189c29f855812d8eeebf65

Observation ad87c92d-1a62-45b0-8399-c906d1cdd341 · outbound

This paper cites ChunkRAG: Novel LLM-Chunk Filtering Method for RAG Systems.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions ChunkRAG: Novel LLM-Chunk Filtering Method for RAG Systems

Reference 84

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no resolver link, observed 2026-08-15T18:08:11.847401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:08:11.847401Z digest=sha256:597c3dc56269c1d25e3c38e76b6e1552e3c6c60c2dea1db0399795b6ab439c00

Observation 3b15d551-d5dd-4de5-a0db-5149c786cafb · outbound

This paper cites Improving the domain adaptation of retrieval augmented generation (rag) models for open domain question answering.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Improving the domain adaptation of retrieval augmented generation (rag) models for open domain question answering

Reference 85

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raw_fallback, observed 2026-08-15T18:08:12.809888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.851667Z digest=sha256:01fc83e6112a0ee05fa038f14fb0c452d6dea681672524d08c736afe74b42d0b

Observation 77fc85d3-0120-4d95-8b05-c6325529d4a3 · outbound

This paper cites Fine tuning vs.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Fine tuning vs

Reference 86

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verified fuzzy
raw_fallback, observed 2026-08-15T18:08:12.798502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.854941Z digest=sha256:e6402f45831a51fcbc25d8dd1f27a42f0cccb3e6561f2d1dabb45aeeaee9abea

Observation 22dd586c-638f-452d-8fab-a7e0d95f96f5 · outbound

This paper cites End-to-end memory networks.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions End-to-end memory networks

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:08:12.787250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.858329Z digest=sha256:2bd5fc0ad94f1e7033e4bf5986f5cad2c7f74a995d468ac64f886d0fea4668e5

Observation 39c15e4a-3129-4459-bfac-179aae3d8e1e · outbound

This paper cites Multihop-rag: Benchmarking retrieval-augmented generation for multi-hop queries.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Multihop-rag: Benchmarking retrieval-augmented generation for multi-hop queries

Reference 88

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raw_fallback, observed 2026-08-15T18:08:12.776259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.861793Z digest=sha256:0c9c642783f7146a1d9950f0b2e0fd76fa66ebcae523edad2346f038f8a19425

Observation 713b699b-9326-48f7-9b12-dfa5b876fb82 · outbound

This paper cites Enterprise-grade rag systems: High-performance rag with vector databases,.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Enterprise-grade rag systems: High-performance rag with vector databases,

Reference 89

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raw_fallback, observed 2026-08-15T18:08:12.763580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.865410Z digest=sha256:fcfb462feea2f67b2f9561ee4626a915dd381962d03813f57690b7e608650fa9

Observation fa93b102-5077-4a82-9061-78c5e83c354d · outbound

This paper cites Interleaving retrieval with chain-of-thought reasoning for knowledge-intensive multi-step questions.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Interleaving retrieval with chain-of-thought reasoning for knowledge-intensive multi-step questions

Reference 90

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raw_fallback, observed 2026-08-15T18:08:12.751744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.869410Z digest=sha256:0bf13c23122075b0f035d40b06116459fe6c2cecd009c04a34351e0f45583041

Observation 5f787b61-6d74-4750-9fed-a77573451f1e · outbound

This paper cites Rag based question-answering for contextual response prediction system.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Rag based question-answering for contextual response prediction system

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:08:12.739509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.872823Z digest=sha256:8c75cf2810df66a0a35f4806ad54f1e0fd3b0c93664b07db44f40a978e8d66bf

Observation be7b0141-8948-484a-8dfe-b001bd1deba0 · outbound

This paper cites Rˆ3: Reinforced reader-ranker for open-domain question answering.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Rˆ3: Reinforced reader-ranker for open-domain question answering

Reference 92

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raw_fallback, observed 2026-08-15T18:08:12.728344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.876623Z digest=sha256:b68c664d8c8071e3831857c7b4c312d0945f032d189e904f851542d8917fe6a6

Observation 78a83394-7f77-4295-a924-8314b2663ed0 · outbound

This paper cites Searching for best practices in retrieval-augmented generation.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Searching for best practices in retrieval-augmented generation

Reference 93

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raw_fallback, observed 2026-08-15T18:08:12.717693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.880110Z digest=sha256:e40eb39e5f2fed141e0e94fccaed013811a49b4d98cf4e84e4a6c1bdeee774b8

Observation 50e54ecf-17a3-46f2-a843-1afef42dc718 · outbound

This paper cites Learning to Filter Context for Retrieval-Augmented Generation.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Learning to Filter Context for Retrieval-Augmented Generation

Reference 94

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no resolver link, observed 2026-08-15T18:08:11.884206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:08:11.884206Z digest=sha256:9314c3390944616132041cd85c9b506a3e3f21103943fbb1f6c31941d52cc963

Observation 1d50dd86-526b-4453-b15d-49b26e41060a · outbound

This paper cites Memory networks.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Memory networks

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:08:12.706599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.887898Z digest=sha256:7a74245d23ab1aeb4f6824f1b8ff4b7f2ace37f56b196c5286b0a0cbf7aebc3e

Observation ff643fa3-e3bc-4bd0-9ba3-c846094a4eac · outbound

This paper cites Self-routing rag: Binding selective retrieval with knowledge verbalization.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Self-routing rag: Binding selective retrieval with knowledge verbalization

Reference 96

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no resolver link, observed 2026-08-15T18:08:11.891955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:08:11.891955Z digest=sha256:b018fbd444f834934ab8cfdc3a2d7f53c5944efbb3ebad8780cf04c7a85f57bb

Observation e416d642-faa2-4d5e-8cfc-69cd436e3aed · outbound

This paper cites Benchmarking retrieval-augmented generation for medicine.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Benchmarking retrieval-augmented generation for medicine

Reference 97

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no resolver link, observed 2026-08-15T18:08:11.896008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:08:11.896008Z digest=sha256:78a512f7bba170f88494bf488d7106285919d968bee2a51e4287d89598379f51

Observation 6bff7ab9-32e5-409d-a6b9-e6006c9449b0 · outbound

This paper cites Knowing you don’t know: Learning when to continue search in multi-round rag through self-practicing.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Knowing you don’t know: Learning when to continue search in multi-round rag through self-practicing

Reference 98

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no resolver link, observed 2026-08-15T18:08:11.899298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:08:11.899298Z digest=sha256:554a881ab784c144adee9a5caa13b6a85cb16fde538f7d8284475a4bf90942ca

Observation 1bf5a39a-27be-494f-8126-c38a29397fdb · outbound

This paper cites Retrieval-augmented generation for generative artificial intelligence in health care.npj Health Systems, 2(2):1–8, 2025.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Retrieval-augmented generation for generative artificial intelligence in health care.npj Health Systems, 2(2):1–8, 2025

Reference 99

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verified fuzzy
raw_fallback, observed 2026-08-15T18:08:12.688709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.902903Z digest=sha256:5d4bd7904f5564eb0841efc275491b0dee9455916d3e534e02720541f25434bc

Observation 94040239-5876-466f-ac2a-60e5901e705f · outbound

This paper cites Rankrag: Unifying context ranking with retrieval-augmented generation in llms.

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions Rankrag: Unifying context ranking with retrieval-augmented generation in llms

Reference 100

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unresolved
no resolver link, observed 2026-08-15T18:08:11.906687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:08:11.906687Z digest=sha256:e1520461712fd895e2210a625974a87d0c0c742ff76f4142bf7eb926b3bafe02

Observation 04148607-43c0-4a8f-9c6e-864b07bb3143 · outbound

This paper cites The good and the bad: Exploring privacyissuesinretrieval-augmentedgeneration (RAG).

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions The good and the bad: Exploring privacyissuesinretrieval-augmentedgeneration (RAG)

Reference 101

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raw_fallback, observed 2026-08-15T18:08:12.670749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:08:11.910058Z digest=sha256:9da3de273efca1309a0d24e4c6a0a7fc1f9c615e0f331f0b3946b95cc1e7c0c9

Pith citing papers

Observation 0d890f15-69cf-4e3b-b57b-1f2108519c8d · inbound

Benchmarking and Learning Real-World Customer Service Dialogue cites this paper.

Benchmarking and Learning Real-World Customer Service Dialogue A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions

Reference 16

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unresolved
no resolver link, observed 2026-08-04T08:13:27.519293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T08:13:27.519293Z digest=sha256:d642ccebdf6da7619c1c361f97b2370adc8542c378b36989467243e078fc8f94

Observation a3b48c1f-6002-4e07-91ce-2f3a5e0c0a69 · inbound

Adaptive Query Routing: A Tier-Based Framework for Hybrid Retrieval Across Financial, Legal, and Medical Documents cites this paper.

Adaptive Query Routing: A Tier-Based Framework for Hybrid Retrieval Across Financial, Legal, and Medical Documents A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions

Reference 50

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metadata mismatch
arxiv_id, observed 2026-05-10T14:45:41.154710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-10T14:42:00.856705Z digest=sha256:8691b8c67379d14bc84ec3c7d7b5eb3c17413c261ba4c503187bfe4f4502ba3f

Observation 27cee526-c0f3-46cf-85c0-547dd53f9208 · inbound

Learning from AVA: Early Lessons from a Curated and Trustworthy Generative AI for Policy and Development Research cites this paper.

Learning from AVA: Early Lessons from a Curated and Trustworthy Generative AI for Policy and Development Research A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions

Reference 77

Resolution
verified exact
arxiv_id, observed 2026-05-10T12:10:22.954392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-10T04:38:00.482850Z digest=sha256:dcae8399c738ba65b17e1b07ef7ee6ea10828a2c636a4d621a46eed6d26a89e4

Observation aad19c00-6e94-4bb7-be33-647046c56b17 · inbound

From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning cites this paper.

From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-11T13:16:05.638106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-05-10T02:06:32.021051Z digest=sha256:81908db580e88fdb1f38c7429e082d6d68e7686da56101c7dc57112a600e26bd

Observation d72e7a60-e96d-4a0b-a8b1-9e9e1500b9ac · inbound

Development and Preliminary Evaluation of a Domain-Specific Large Language Model for Tuberculosis Care in South Africa cites this paper.

Development and Preliminary Evaluation of a Domain-Specific Large Language Model for Tuberculosis Care in South Africa A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions

Reference 36

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T22:49:33.509955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-14T22:48:41.826046Z digest=sha256:db7c14cb661dcf7cffaf403412e2a557bef17a3afc94d86af134d1e74eb39390

Observation 98cfe52f-a4c6-42ee-8e5c-a8cecd9d85e2 · inbound

Beyond Semantic Relevance: Counterfactual Risk Minimization for Robust Retrieval-Augmented Generation cites this paper.

Beyond Semantic Relevance: Counterfactual Risk Minimization for Robust Retrieval-Augmented Generation A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions

Reference 60

Resolution
verified exact
arxiv_id, observed 2026-05-11T16:46:10.899349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-09T15:04:40.429929Z digest=sha256:6db39a7e5301f7d4f7231e844f939caf8b589b4cbca9b4f79a14006224f932c9

Observation 13bc7141-565e-4721-a426-f693866350d4 · inbound

AgenticRAG: Agentic Retrieval for Enterprise Knowledge Bases cites this paper.

AgenticRAG: Agentic Retrieval for Enterprise Knowledge Bases A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-11T19:21:08.658291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-05-08T12:10:01.748436Z digest=sha256:ee2f62ccaef2c9d0a798c5a09bfc30dfa8a2c71fbea41f2ef6e3bab520d5e3ad

Observation 31ea90e2-40c9-48c6-b6e5-bc9ea68c928d · inbound

SentAttack: A Sentence-Level Black-Box Adversarial Attack Method for Dense Retrieval Models cites this paper.

SentAttack: A Sentence-Level Black-Box Adversarial Attack Method for Dense Retrieval Models A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions

Reference 31

Resolution
unresolved
no resolver link, observed 2026-07-12T02:21:35.800392Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T02:21:35.800392Z digest=sha256:ac8e6ba181e3936d673f0f47226260007d4127d8d19f4d9a088e5f26633a3494