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Paper Citation Record · LEDGER

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora

As of 8 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 10 inbound Pith citation observations for arXiv:2506.20963.

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

pith.paper-citation-record.v1
2506.20963 v2

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:44:04.946360Z

measured 67 of 67 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T07:06:05.559182Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T20:28:55.951900Z

Reference resolution

57 of 57 outbound references displayed

  • verified exact1
  • verified fuzzy13
  • unresolved43
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c0224478-3920-4f09-86c8-c4aaf1388ffa · outbound

This paper cites GPT-4 Technical Report.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora GPT-4 Technical Report

Reference 1

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Observation 69c73ba9-5abe-40b8-b56b-3b45a1f6b082 · outbound

This paper cites Qwen2.5 Technical Report.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Qwen2.5 Technical Report

Reference 2

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Observation 9f4a143b-b385-4478-9f9b-0906f8b179b6 · outbound

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

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora LLaMA: Open and Efficient Foundation Language Models

Reference 3

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source=pdf_text observed=2026-08-06T22:43:59.848853Z digest=sha256:ba9b1459084da80f5e1a82047aa539328208348e3ed762ef200478393b3238fc

Observation 624f3545-e491-4725-bae5-bb42b485789a · outbound

This paper cites A comprehensive survey on process-oriented automatic text summarization with exploration of llm-based methods.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora A comprehensive survey on process-oriented automatic text summarization with exploration of llm-based methods

Reference 4

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source=pdf_text observed=2026-08-06T22:43:59.913811Z digest=sha256:7141724dcdb191896c22e43b1ada9630f7118b506edad5732f00143ce39dfed4

Observation 10fd2167-574a-4693-9d25-85d3c2451f45 · outbound

This paper cites Llm-based code generation method for golang compiler testing.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Llm-based code generation method for golang compiler testing

Reference 5

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source=pdf_text observed=2026-08-06T22:43:59.956565Z digest=sha256:3e4157a44848c8a7fdc7a830fb9bc4fc3dcd67b8d64e26a7d713c2941fff5cd5

Observation 33d12c52-6780-4edc-ba04-77da5e147745 · outbound

This paper cites LLM-SR: Scientific Equation Discovery via Programming with Large Language Models.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora LLM-SR: Scientific Equation Discovery via Programming with Large Language Models

Reference 6

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Observation 52a04137-34b6-49e8-9179-0ff68e0e35ff · outbound

This paper cites A Survey of Graph Meets Large Language Model: Progress and Future Directions.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora A Survey of Graph Meets Large Language Model: Progress and Future Directions

Reference 7

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source=pdf_text observed=2026-08-06T22:44:00.189627Z digest=sha256:9a7622532a6d446bd4ce4ca8728bbb6ad9585b5328cb7faa11c1be51932d3f8a

Observation 48ab8693-af50-4e92-9c7d-3947e5ddfa38 · outbound

This paper cites Beyond one-model-fits-all: A survey of domain specialization for large language models.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Beyond one-model-fits-all: A survey of domain specialization for large language models

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 706a406d-970d-43a5-bb4c-0e02af7bab3f · outbound

This paper cites Openagi: When llm meets domain experts.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Openagi: When llm meets domain experts

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 598ae65b-1105-4b92-b7cf-676e5de2e8c0 · outbound

This paper cites A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

Reference 10

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Observation 71f0ecf2-3ae1-4e8d-b65b-27acc177a4c6 · outbound

This paper cites A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions

Reference 11

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source=pdf_text observed=2026-08-06T22:44:00.484315Z digest=sha256:e34531c78434d5c4d50878b1d758594cc9044d86451ac7389eda4b271f5939be

Observation b941c1e2-2f5d-4dd5-a024-b6b17658da2c · outbound

This paper cites LLM Lies: Hallucinations are not Bugs, but Features as Adversarial Examples.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora LLM Lies: Hallucinations are not Bugs, but Features as Adversarial Examples

Reference 12

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source=pdf_text observed=2026-08-06T22:44:00.555656Z digest=sha256:e626824efb6bef63063aff5d6fce5d48c3332fa9bda95faf487f1ee2cc51a460

Observation 29f86ffd-cb2c-43b0-badf-3f835637a52e · outbound

This paper cites When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 13

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source=pdf_text observed=2026-08-06T22:44:00.581983Z digest=sha256:4e2a8e3c533bc22a7cfc85a7f963f0da48c880b0c1d1061e744eddaa34e434c2

Observation 9856e163-d5df-4e37-93df-8cf6a885b186 · outbound

This paper cites A Closer Look at the Limitations of Instruction Tuning.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora A Closer Look at the Limitations of Instruction Tuning

Reference 14

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source=pdf_text observed=2026-08-06T22:44:00.658347Z digest=sha256:8d4b62295de1532fe8b6f883bbeebf9e2c244c14ce22704d0baa41061466b82f

Observation f3609128-1cd8-4902-85d5-d306b14313d1 · outbound

This paper cites Getting it right: the limits of fine-tuning large language models.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Getting it right: the limits of fine-tuning large language models

Reference 15

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raw_fallback, observed 2026-08-06T22:44:07.955893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:44:00.803862Z digest=sha256:7c5b25773a8b9aa48a34a2ee769763248752b2056947e262722a422e510f3fde

Observation db4b8f53-7063-4a2e-98f3-b0362549feba · outbound

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

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 16

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source=pdf_text observed=2026-08-06T22:44:00.904058Z digest=sha256:8dbd22b0e8c5411cca9d23d6fdd58ac2bdeec74ccabda0bc3b376e161624f943

Observation 07e15a44-8a4a-4258-b1b7-2aa3a3540519 · outbound

This paper cites A survey on rag meeting llms: Towards retrieval-augmented large language models.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora A survey on rag meeting llms: Towards retrieval-augmented large language models

Reference 17

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Observation 0be9a3f5-2683-4659-895e-7919c8fcf3cf · outbound

This paper cites Retrieval-Augmented Generation for Natural Language Processing: A Survey.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Retrieval-Augmented Generation for Natural Language Processing: A Survey

Reference 18

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source=pdf_text observed=2026-08-06T22:44:01.038308Z digest=sha256:3ad2540ec34667b17cd759d61d9d04c721482ba555bf7ca0cd8daca408f0a6a7

Observation ea971c73-1678-47c7-9045-11e218c9c493 · outbound

This paper cites Retrieval-Augmented Generation for AI-Generated Content: A Survey.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Retrieval-Augmented Generation for AI-Generated Content: A Survey

Reference 20

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Observation e85e3748-9045-41e6-ae16-ef0dd60ed78a · outbound

This paper cites Trustworthiness in Retrieval-Augmented Generation Systems: A Survey.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Trustworthiness in Retrieval-Augmented Generation Systems: A Survey

Reference 21

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source=pdf_text observed=2026-08-06T22:44:01.292422Z digest=sha256:6e611aa34fbd1efed339fb3a77be882e0f974a5c088a720760deb78ac47e5483

Observation 891f6ee1-e69b-45dc-8125-ca2b63f05d03 · outbound

This paper cites Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely

Reference 22

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source=pdf_text observed=2026-08-06T22:44:01.343918Z digest=sha256:02853101f8fc10e9356288ee953f207371ded97f412ce0ab9f4971cad08375f9

Observation 31d7142f-67f4-4a27-bdbb-8ce83fe7b0a6 · outbound

This paper cites Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases

Reference 23

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source=pdf_text observed=2026-08-06T22:44:01.502044Z digest=sha256:cf647d13cf14b52d99298d5cba89b5678b02ee25ebb6c30d4108a3b753d67986

Observation 02430805-5554-4437-9138-9bf59d28754e · outbound

This paper cites Understanding the Fundamental Design Decisions of Retrieval-Augmented Generation Systems.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Understanding the Fundamental Design Decisions of Retrieval-Augmented Generation Systems

Reference 24

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source=pdf_text observed=2026-08-06T22:44:01.593757Z digest=sha256:e40c8592b9a2ddf1f125e01f568bbf2edd49b51ec5e90431855c51740239d24d

Observation 2b913be1-8284-46c4-859f-e4e1a9452d8a · outbound

This paper cites How Much Can RAG Help the Reasoning of LLM?.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora How Much Can RAG Help the Reasoning of LLM?

Reference 25

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source=pdf_text observed=2026-08-06T22:44:01.630597Z digest=sha256:dd6a0879964e32ea750d9e4383ce988992e3b6282a58e815e994cc5696e6b0a3

Observation c1faa3bd-357b-46c2-a423-4f9b10db6a98 · outbound

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

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Retrieval-Augmented Generation with Graphs (GraphRAG)

Reference 26

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Observation bd9ce4be-5c2c-4f7f-9df1-4ee5ba370724 · outbound

This paper cites A survey of graph retrieval-augmented generation for customized large language models.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora A survey of graph retrieval-augmented generation for customized large language models

Reference 27

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Observation e1ed3fb7-da87-46a3-a43f-8c2eae208e9d · outbound

This paper cites an unresolved cited work.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Unresolved cited work

Reference 28

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source=pdf_text observed=2026-08-06T22:44:01.819517Z digest=sha256:83bfbb41b0f90c66d2ad9d38de5e8a9a73d4358c6bf7bb78f70519864781180d

Observation 7707218b-ee5f-4335-84a2-79c6f3aa9d49 · outbound

This paper cites GRAG: Graph Retrieval-Augmented Generation.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora GRAG: Graph Retrieval-Augmented Generation

Reference 29

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Observation 926c8d90-9707-44ca-9594-1a7e1f365bc2 · outbound

This paper cites Graph Retrieval-Augmented Generation: A Survey.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Graph Retrieval-Augmented Generation: A Survey

Reference 30

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Observation 3d695b85-fd7d-41c6-895a-09263ea62fcb · outbound

This paper cites an unresolved cited work.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Unresolved cited work

Reference 31

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation fa094e38-195e-4e5c-8621-9af6b0ebee0d · outbound

This paper cites DRAGIN: Dynamic Retrieval Augmented Generation based on the Information Needs of Large Language Models.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora DRAGIN: Dynamic Retrieval Augmented Generation based on the Information Needs of Large Language Models

Reference 32

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Observation 975c69b1-f360-42c9-9870-5459e5419e48 · outbound

This paper cites In-depth Analysis of Graph-based RAG in a Unified Framework.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora In-depth Analysis of Graph-based RAG in a Unified Framework

Reference 33

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Observation 46187748-14ca-4f79-83aa-277d167e2e84 · outbound

This paper cites From Local to Global: A Graph RAG Approach to Query-Focused Summarization.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora From Local to Global: A Graph RAG Approach to Query-Focused Summarization

Reference 34

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Observation ab8f81ea-33e5-4d85-af0c-21b811624d50 · outbound

This paper cites Approximate nearest neighbors: Towards removing the curse of dimensionality.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Approximate nearest neighbors: Towards removing the curse of dimensionality

Reference 35

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raw_fallback, observed 2026-08-06T22:44:07.567083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation c161058c-1499-4060-aeea-717c40d6da0e · outbound

This paper cites Locality-sensitive hashing scheme based on p-stable distributions.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Locality-sensitive hashing scheme based on p-stable distributions

Reference 36

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raw_fallback, observed 2026-08-06T22:44:07.372583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:44:02.595034Z digest=sha256:0fb045209171349be76c182be6ed9c1df8d6aeff2102b9fbf47b90ebf5b69710

Observation 61cb99b7-3c43-4aa2-8b00-5ddf2f6e66b2 · outbound

This paper cites Razenshteyn, and Ludwig Schmidt.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Razenshteyn, and Ludwig Schmidt

Reference 37

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:44:02.754230Z digest=sha256:ecaa680b8c9ec7cad88905937bc2598a51ef0995249d2d1110538d661a4e939e

Observation fd8b7b64-a594-44fd-9a2a-1cf07af688f0 · outbound

This paper cites Lightrag: Simple and fast retrieval-augmented generation, 2024.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Lightrag: Simple and fast retrieval-augmented generation, 2024

Reference 38

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:44:02.816428Z digest=sha256:eb5e21cca8e72737afdbcdf71c892d8a46d32947e81f37a598c4b614d67673b4

Observation 295205d4-d1ba-4c94-aa88-832a949125ff · outbound

This paper cites Dynamic Parametric Retrieval Augmented Generation for Test-time Knowledge Enhancement.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Dynamic Parametric Retrieval Augmented Generation for Test-time Knowledge Enhancement

Reference 39

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:44:02.869515Z digest=sha256:823a397ab1f058f5828b5862f8f414f9648573271b0c2427a4de70c05f544452

Observation 0606efa3-630d-4425-bb0e-4a174a42a375 · outbound

This paper cites an unresolved cited work.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Unresolved cited work

Reference 40

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raw_fallback, observed 2026-08-06T22:44:06.907571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:44:03.012102Z digest=sha256:cddd2176e13b9e7c4f222fe96d9acb89d7dced334efdcb50eea30f4977521a3a

Observation ad71dad1-0e54-4a7b-aaf9-9c65e2c0e706 · outbound

This paper cites Gslb: The graph structure learning benchmark.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Gslb: The graph structure learning benchmark

Reference 41

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raw_fallback, observed 2026-08-06T22:44:06.779774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:44:03.067732Z digest=sha256:f18694308f0ba2ec889e746c7ff0ad3980d651a87954c9a2d5fa346482e90623

Observation 80373868-90a0-4f83-b344-9131cd22bcf2 · outbound

This paper cites A Survey on Locality Sensitive Hashing Algorithms and their Applications.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora A Survey on Locality Sensitive Hashing Algorithms and their Applications

Reference 42

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:44:03.206239Z digest=sha256:7ac123ec334b8d55aeb07be220a65c225768136c871f2fc7ef3493b697845cfa

Observation 90ff8a7f-9d2f-47ff-b034-0550dad1abec · outbound

This paper cites MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries

Reference 44

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no resolver link, observed 2026-08-06T22:44:03.400107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:44:03.400107Z digest=sha256:9e18ab9cd724b3f3b558b67304e6b0fa61897f2d55ef6ccdf2025946c7219936

Observation 5a881f9f-0404-429f-b993-ab37c539720e · outbound

This paper cites HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

Reference 45

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unresolved
no resolver link, observed 2026-08-06T22:44:03.469518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:44:03.469518Z digest=sha256:d4e9691c8c3d1fa4683d5f79fa8f01b87b32988d12bc002b81cd024d11c6b747

Observation 31856ce6-6472-4705-be76-9eddccbbee0e · outbound

This paper cites QuALITY: Question Answering with Long Input Texts, Yes!.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora QuALITY: Question Answering with Long Input Texts, Yes!

Reference 46

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no resolver link, observed 2026-08-06T22:44:03.520449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:44:03.520449Z digest=sha256:b1aa263e78bf968647cebb5041415714f8aebc256f5acf1521f16b826de2bb18

Observation edc5addf-ae67-4f30-b97a-1c16109bc877 · outbound

This paper cites Musique: Multihop questions via single-hop question com- position.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Musique: Multihop questions via single-hop question com- position

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:44:06.660024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:44:03.737642Z digest=sha256:cb303622ecad62507fd04f38ccf63cc731b375d3d50614458982c115afc95819

Observation 0e53aa3e-f2f7-44ed-8a0d-7709226e13d7 · outbound

This paper cites Large language models are zero-shot reasoners.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Large language models are zero-shot reasoners

Reference 48

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no resolver link, observed 2026-08-06T22:44:03.854209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:44:03.854209Z digest=sha256:b818919e55860b04f65d92ecbe4ad07e18e3ef529443912ac7bf31989c7845fe

Observation f6b21f42-1844-43eb-abdb-002aeea84473 · outbound

This paper cites Some simple effective approximations to the 2-poisson model for probabilistic weighted retrieval.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Some simple effective approximations to the 2-poisson model for probabilistic weighted retrieval

Reference 49

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verified fuzzy
raw_fallback, observed 2026-08-06T22:44:06.529348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:44:03.960658Z digest=sha256:f740563da61cac4db32b24aed7787c06b79c45f9fd9c5619c038c77f0c4d0241

Observation b1e538f7-24a4-4303-9ceb-3c3ba2c49f47 · outbound

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

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Retrieval-augmented generation for knowledge- intensive nlp tasks

Reference 50

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:44:04.067384Z digest=sha256:c10675b684facd2e2bfecb2766c7a4ea38251bba91a4f66921987fe9b58ef4a9

Observation 9e024cf0-8c7b-457c-88b3-31d01ad12c2c · outbound

This paper cites Hipporag: Neurobiologically inspired long-term memory for large language models.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Hipporag: Neurobiologically inspired long-term memory for large language models

Reference 51

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raw_fallback, observed 2026-08-06T22:44:06.374367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:44:04.225449Z digest=sha256:a39cd7ad76fb6c26277bd1695993f23d232b469e53d154b8c4b0518d480ea961

Observation 871795a1-7e62-4397-9892-ea812655b73a · outbound

This paper cites Toolformer: Language models can teach themselves to use tools.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Toolformer: Language models can teach themselves to use tools

Reference 52

Resolution
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raw_fallback, observed 2026-08-06T22:44:06.207772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:44:04.356110Z digest=sha256:64d564e3f96b185578d76a456ef8704d56973df2975de45d6e9dcb69f16f4525

Observation c6c3bdd4-e7e6-47ec-94e0-11013dc86fc5 · outbound

This paper cites When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories

Reference 53

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:44:04.458103Z digest=sha256:b6faa6b32f640fab496937d36e8f12d8304dcc40e9e0e03a83d71c44cb17d523

Observation dc365024-fb1e-4075-af81-bffb556a7b67 · outbound

This paper cites Llama-3.1-FoundationAI-SecurityLLM-Base-8B Technical Report.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Llama-3.1-FoundationAI-SecurityLLM-Base-8B Technical Report

Reference 54

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:44:04.596340Z digest=sha256:8048e574e71201431dc86b546f93dec553f0225d2b9748ededda5714206c3c91

Observation e9b72f9b-a344-4ac7-905e-34ca5660ef2d · outbound

This paper cites A General Retrieval-Augmented Generation Framework for Multimodal Case-Based Reasoning Applications.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora A General Retrieval-Augmented Generation Framework for Multimodal Case-Based Reasoning Applications

Reference 55

Resolution
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local_arxiv, observed 2026-08-06T22:44:05.142608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:44:04.660922Z digest=sha256:6b99e09c5c8e90e1e83b0f169ecb401e6efe313e3f9aa0db28f8fddb3626f5cf

Observation 36d79908-6ee9-405c-a7eb-99d934a96936 · outbound

This paper cites M3-embedding: Multi-linguality, multi-functionality, multi-granularity text embeddings through self-knowledge distillation.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora M3-embedding: Multi-linguality, multi-functionality, multi-granularity text embeddings through self-knowledge distillation

Reference 56

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raw_fallback, observed 2026-08-06T22:44:06.059990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:44:04.735731Z digest=sha256:fd6ef13b48c70df687c34d0881d6390efb60662b00ed50491d9acb7b32aee3cb

Observation 3bbe0b2b-07f0-4181-8883-66b9e444ae18 · outbound

This paper cites MemoRAG: Boosting Long Context Processing with Global Memory-Enhanced Retrieval Augmentation.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora MemoRAG: Boosting Long Context Processing with Global Memory-Enhanced Retrieval Augmentation

Reference 57

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:44:04.826487Z digest=sha256:dfa35edbbe9984e447756f6e46ea994e29a44e15615de2fdbe27977a1c4dd4f4

Observation e42123be-4497-4b8f-9c67-76dd21d7f4c3 · outbound

This paper cites Language models are few-shot learners.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Language models are few-shot learners

Reference 58

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no resolver link, observed 2026-08-06T22:44:04.891202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:44:04.891202Z digest=sha256:598793e854c8392138f1d830b356c6c8500d629a14f8f31fa49ec3ab6bd4687e

Observation 871d0ca4-5930-4f5f-8378-7e659668fe87 · outbound

This paper cites The Chronicles of RAG: The Retriever, the Chunk and the Generator.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora The Chronicles of RAG: The Retriever, the Chunk and the Generator

Reference 59

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:44:04.946360Z digest=sha256:76a7241a5960def39ddcb5f6b272991d5fccfc83434bd527baf7e65a45f6f35b

Pith citing papers

Observation 0810a5c1-d984-4722-9e43-9d07423e0488 · inbound

EvoRAG: Making Knowledge Graph-based RAG Automatically Evolve through Feedback-driven Backpropagation cites this paper.

EvoRAG: Making Knowledge Graph-based RAG Automatically Evolve through Feedback-driven Backpropagation EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora

Reference 102

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arxiv_id, observed 2026-05-10T08:02:25.166902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T07:59:40.497067Z digest=sha256:96478af95c88db422aaef89db8856303b85dbd96acbf7849ba34efe5cc95f389

Observation 576f9127-bca3-4c6f-9e3e-fb5d04323ef3 · inbound

LLM-Oriented Information Retrieval: A Denoising-First Perspective cites this paper.

LLM-Oriented Information Retrieval: A Denoising-First Perspective EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora

Reference 220

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arxiv_id, observed 2026-05-11T16:01:19.789665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-09T18:54:06.144968Z digest=sha256:fe9754b0bab42be19da3ec80b1157f3b304728276772dc79db55bdfb20e08cce

Observation e8913526-603b-4e27-b7c6-96ec5fe04c2e · inbound

LLM-Oriented Information Retrieval: A Denoising-First Perspective cites this paper.

LLM-Oriented Information Retrieval: A Denoising-First Perspective EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora

Reference 230

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arxiv_id, observed 2026-05-21T00:19:16.438599Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-21T00:18:32.423103Z digest=sha256:3b0ece7988d6379b8e5f6678a126cc2d6b6d67d3a7a2c43689d359fc2ef4d7f8

Observation 892f4d7f-2625-48ad-829a-ced658f762a0 · inbound

Position: How can Graphs Help Large Language Models? cites this paper.

Position: How can Graphs Help Large Language Models? EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora

Reference 38

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arxiv_id, observed 2026-05-09T06:10:42.903826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-08T18:48:03.257015Z digest=sha256:453a4f5154c03409ccba597d7ccc9552c3db77f9620ad115d8f498a2e3a27b91

Observation b4c900dc-5fbf-4985-9e11-84989e080ba7 · inbound

A Comprehensive Survey on Agent Skills: Taxonomy, Techniques, and Applications cites this paper.

A Comprehensive Survey on Agent Skills: Taxonomy, Techniques, and Applications EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora

Reference 144

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arxiv_id, observed 2026-05-11T04:20:57.538087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-11T01:47:39.926540Z digest=sha256:63d7def91304bcbc6c74bb5644532d2f5347db83edf94a60d35a4d114c97dcd5

Observation 5fec0a0d-0925-42da-a551-71e7b0d3d483 · inbound

A Comprehensive Survey on Agent Skills: Taxonomy, Techniques, and Applications cites this paper.

A Comprehensive Survey on Agent Skills: Taxonomy, Techniques, and Applications EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora

Reference 146

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arxiv_id, observed 2026-05-20T23:19:14.823326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-20T23:15:44.550045Z digest=sha256:c7465301f029d751dca9fbe4498ad602bd11ba3580bee0ceb1966321319c8f6f

Observation fc88736d-4b32-4af4-92cd-937a35e6e776 · inbound

A Comprehensive Survey on Agent Skills: Taxonomy, Techniques, and Applications cites this paper.

A Comprehensive Survey on Agent Skills: Taxonomy, Techniques, and Applications EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora

Reference 138

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verified exact
arxiv_id, observed 2026-06-30T23:25:07.393247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-30T23:23:42.883286Z digest=sha256:032606b4da2daafb82976cea3d02adf68ca77d2a079091fd363c7b05147e3d78

Observation 853cb3a7-c004-4f80-914d-218a2743e6bc · inbound

MemGraphRAG: Memory-based Multi-Agent System for Graph Retrieval-Augmented Generation cites this paper.

MemGraphRAG: Memory-based Multi-Agent System for Graph Retrieval-Augmented Generation EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora

Reference 68

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arxiv_id, observed 2026-06-28T20:42:37.984526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-28T18:20:43.092561Z digest=sha256:ab3c082679d1e92cfd4c27db4a28f2a898f4b83fdb8a6de1b769c3bbb51f53d4

Observation 14aa0775-3f5b-4082-a936-3452a6ba8092 · inbound

A Unified Framework for Context-Aware and Relation-Aware Graph Retrieval-Augmented Generation cites this paper.

A Unified Framework for Context-Aware and Relation-Aware Graph Retrieval-Augmented Generation EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-07-03T20:28:55.953568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T01:17:21.685012Z digest=sha256:8101621529afedb8d38d77295f33461f8c99c6d5d188460b810591b6ade47199

Observation be408f80-03ee-4265-855e-57ff85ce9385 · inbound

Beyond Retrieval: Analytic Memory for Multimodal Agents cites this paper.

Beyond Retrieval: Analytic Memory for Multimodal Agents EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora

Reference 5

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unresolved
no resolver link, observed 2026-08-03T07:06:05.559182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T07:06:05.559182Z digest=sha256:d2d821cb8f8dd50b2d9c136741a7f7c1c61776fbe33e0e604c2d5430a37c02a8