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Paper Citation Record · LEDGER

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

As of 22 August 2026, this Paper Citation Record lists 100 of 105 outbound references and 28 inbound Pith citation observations for arXiv:2411.14110.

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

pith.paper-citation-record.v1
2411.14110 v2

Coverage vector

measured 100 of 105 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:34:26.274730Z

measured 128 of 128 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 28 of 28 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T06:05:57.556607Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T14:09:53.298273Z

Reference resolution

100 of 105 outbound references displayed

  • verified exact1
  • verified fuzzy32
  • unresolved67
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e0a778be-2e1e-43c9-9d95-142df1551b86 · outbound

This paper cites Survey of hallucination in natural language generation.ACM Computing Surveys, 55(12):1–38, 2023.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Survey of hallucination in natural language generation.ACM Computing Surveys, 55(12):1–38, 2023

Reference 1

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source=pdf_text observed=2026-08-12T15:34:25.367102Z digest=sha256:f389838d61e71524b23c03ca4f1732afe8c9391ec5d0007758d6aadc5015723b

Observation 6165c84a-f777-44b0-99a0-ae217afde1d7 · outbound

This paper cites Retrieval augmentation reduces hallucination in conversation.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Retrieval augmentation reduces hallucination in conversation

Reference 2

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source=pdf_text observed=2026-08-12T15:34:25.374074Z digest=sha256:62b5543304561520e2a84a05427cb7b7828c4be7c6af3d6b495c2cd576ac0bdd

Observation 00ef36a9-092e-4fa4-a572-88a651b2aef9 · outbound

This paper cites Retrieval-augmented generation for knowledge- intensive nlp tasks.Advances in Neural Information Processing Systems, 33:9459–9474, 2020.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Retrieval-augmented generation for knowledge- intensive nlp tasks.Advances in Neural Information Processing Systems, 33:9459–9474, 2020

Reference 3

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source=pdf_text observed=2026-08-12T15:34:25.381796Z digest=sha256:64ae00f58afba7b6a0fcdfa2f56fd5134a00af9be034b6432263561c6371f1f2

Observation 39c91828-d50a-4843-9ed7-49989c1e3a20 · outbound

This paper cites Replug: Retrieval-augmented black-box language models.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Replug: Retrieval-augmented black-box language models

Reference 4

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source=pdf_text observed=2026-08-12T15:34:25.387851Z digest=sha256:8e539bbd8b41edddd901377967b16f453d38b6d63f5ec533d3abbd41a1faee82

Observation 8a3456f8-5f2c-44a6-8bd9-bcd62ff2313a · outbound

This paper cites In-context retrieval-augmented language models.Transactions of the Association for Computational Linguistics, 11:1316–1331, 2023.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications In-context retrieval-augmented language models.Transactions of the Association for Computational Linguistics, 11:1316–1331, 2023

Reference 5

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source=pdf_text observed=2026-08-12T15:34:25.396027Z digest=sha256:57cb3fe9da0f32298055de619ee84e35ac6d33e853b2f7f037e647fad1688fdb

Observation fa4f1390-bea1-4cea-8d02-0e8c5a5fc82e · outbound

This paper cites Adapted large language models can outperform medical experts in clinical text summarization.Nature medicine, 30(4):1134–1142, 2024.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Adapted large language models can outperform medical experts in clinical text summarization.Nature medicine, 30(4):1134–1142, 2024

Reference 6

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source=pdf_text observed=2026-08-12T15:34:25.402939Z digest=sha256:9b3a867b1346af1182b3498ff48c4ff346305ecb361a91d54f0beea7dc3f32df

Observation cc602784-030f-405a-b27f-12d330c0971d · outbound

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

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Dense passage retrieval for open-domain question answering

Reference 7

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source=pdf_text observed=2026-08-12T15:34:25.409637Z digest=sha256:9d2842c3211898cb612f108eaf83e94eeb1f46705548f569ff195dc1cbba4335

Observation 06f0c26e-0691-4142-820c-fbe42610a7f0 · outbound

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

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Improving language models by retrieving from trillions of tokens

Reference 8

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source=pdf_text observed=2026-08-12T15:34:25.419688Z digest=sha256:278bb7c8c7825fa8661b637e3de2a0e607676e48e7a5c39adac013bffc7fa76a

Observation 4d817bd7-9b45-4087-b2e0-02f445a22b31 · outbound

This paper cites LaMDA: Language Models for Dialog Applications.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications LaMDA: Language Models for Dialog Applications

Reference 9

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source=pdf_text observed=2026-08-12T15:34:25.425300Z digest=sha256:386d4b42c700b92bc99364d9139210cfb8b3d6f2569e823e7671f304b5ae76cd

Observation 77242461-5e07-430b-a1ce-29eb06822058 · outbound

This paper cites Transforming healthcare education: Harnessing large language models for frontline health worker capacity building using retrieval-augmented generation.medRxiv, pages 2023–12, 2023.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Transforming healthcare education: Harnessing large language models for frontline health worker capacity building using retrieval-augmented generation.medRxiv, pages 2023–12, 2023

Reference 10

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source=pdf_text observed=2026-08-12T15:34:25.431985Z digest=sha256:0bfcc84f16cf6d542f2ac02682485e84b89b6917c24531cb0728672e0ded232c

Observation d291cb63-f8a9-4057-8831-558fc10b2832 · outbound

This paper cites Potential for gpt technology to optimize future clinical decision-making using retrieval-augmented generation.Annals of Biomedical Engineering, 52(5):1115–1118, 2024.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Potential for gpt technology to optimize future clinical decision-making using retrieval-augmented generation.Annals of Biomedical Engineering, 52(5):1115–1118, 2024

Reference 11

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source=pdf_text observed=2026-08-12T15:34:25.440193Z digest=sha256:8afe84b79cfb7d3c61689bc8e9dcd7c28f94324ff091823c9e2e2eb9bd00663c

Observation bebaf762-446f-424e-9665-0d99a06b1472 · outbound

This paper cites Making llms worth every penny: Resource-limited text classification in banking.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Making llms worth every penny: Resource-limited text classification in banking

Reference 12

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source=pdf_text observed=2026-08-12T15:34:25.459253Z digest=sha256:65ffd76d0eb968cce779446b9a75866ff66c364d072b714e6c6f7af52c1a5a89

Observation 34aa249b-4463-4fc0-9e1f-e56e65a49ef0 · outbound

This paper cites AutoLAW: Augmented Legal Reasoning through Legal Precedent Prediction.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications AutoLAW: Augmented Legal Reasoning through Legal Precedent Prediction

Reference 13

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source=pdf_text observed=2026-08-12T15:34:25.468610Z digest=sha256:a9963757d37f3c912941ed1afc9b0f3c53671e78eccb6df5ccc0df76080164e6

Observation 86a9151c-0cf7-4d4d-afad-6e192a78b172 · outbound

This paper cites Chain of reference prompting helps llm to think like a lawyer.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Chain of reference prompting helps llm to think like a lawyer

Reference 14

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source=pdf_text observed=2026-08-12T15:34:25.478108Z digest=sha256:53bf07228ffcb6513c4ae6ee042e5d3098fcbc58bea46227e3da48fbce980ab1

Observation 2f895b7f-60cf-4355-8c67-e45090a0e1f0 · outbound

This paper cites Mycrunchgpt: A llm assisted framework for scientific machine learning.Journal of Machine Learning for Modeling and Computing, 4(4), 2023.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Mycrunchgpt: A llm assisted framework for scientific machine learning.Journal of Machine Learning for Modeling and Computing, 4(4), 2023

Reference 15

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source=pdf_text observed=2026-08-12T15:34:25.485440Z digest=sha256:d606ece20eb38ac088273dfd174e6a6bfbf4a9f8da673b8f17e5192cfdf918cc

Observation ef3fbb0a-08fe-40b4-83cc-e2372c19ebdd · outbound

This paper cites An Interdisciplinary Outlook on Large Language Models for Scientific Research.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications An Interdisciplinary Outlook on Large Language Models for Scientific Research

Reference 16

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source=pdf_text observed=2026-08-12T15:34:25.496731Z digest=sha256:e29939c20fc2fd1eedb66d032bcb3eab7c9fd9794883d525d3f4664149e1e720

Observation 036606d4-521c-4fce-90f6-10ba5c0efd89 · outbound

This paper cites Opportunities for retrieval and tool augmented large language models in scientific facilities.npj Computational Materials, 10(1):251, 2024.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Opportunities for retrieval and tool augmented large language models in scientific facilities.npj Computational Materials, 10(1):251, 2024

Reference 17

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source=pdf_text observed=2026-08-12T15:34:25.506465Z digest=sha256:8fe6f247684ecfead83c2135757ccdb5d56b04356323fa3fc0bc07470811edf3

Observation 35d60478-dfee-44fc-aaf5-ba18c98bff5c · outbound

This paper cites Openai gpts, access in 2024.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Openai gpts, access in 2024

Reference 18

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source=pdf_text observed=2026-08-12T15:34:25.512539Z digest=sha256:6d78f57a57188db600ffa0241b9401bf5e73faccaf760c061888652b130014f1

Observation 297a2f20-388d-4868-bd52-df7331023308 · outbound

This paper cites Exploring AI Text Generation, Retrieval-Augmented Generation, and Detection Technologies: a Comprehensive Overview.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Exploring AI Text Generation, Retrieval-Augmented Generation, and Detection Technologies: a Comprehensive Overview

Reference 19

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source=pdf_text observed=2026-08-12T15:34:25.518349Z digest=sha256:eadbba6a98ed546a47dc19990aeac5eeb8d53dceed0811103a99c13d57aefa2b

Observation 1c14d5b1-32a2-4d6c-b292-3f96bfd1ea47 · outbound

This paper cites RAG-WM: An Efficient Black-Box Watermarking Approach for Retrieval-Augmented Generation of Large Language Models.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications RAG-WM: An Efficient Black-Box Watermarking Approach for Retrieval-Augmented Generation of Large Language Models

Reference 20

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T15:34:25.528216Z digest=sha256:cfd0e36a731f2bcee958f9a3a22f61de6f9d8ed6986e361ae224793ac72132bc

Observation 418864b0-a63f-4ce9-9a40-811ed9d6326e · outbound

This paper cites Development of dental consultation chatbot using retrieval augmented llm.The Journal of the Institute of Internet, Broadcasting and Communication, 24(2):87–92, 2024.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Development of dental consultation chatbot using retrieval augmented llm.The Journal of the Institute of Internet, Broadcasting and Communication, 24(2):87–92, 2024

Reference 21

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source=pdf_text observed=2026-08-12T15:34:25.534683Z digest=sha256:0945bb6752e840c77b7c2d0cea83833899ce80a11407c435c05cac7b6f5eccc2

Observation d7a843d7-a1e9-4af1-aa4a-3fefb55c5d77 · outbound

This paper cites HealthQ: Unveiling Questioning Capabilities of LLM Chains in Healthcare Conversations.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications HealthQ: Unveiling Questioning Capabilities of LLM Chains in Healthcare Conversations

Reference 22

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source=pdf_text observed=2026-08-12T15:34:25.539726Z digest=sha256:c5c69b10dc01d315c747e125aebb3f5ea97bb9f9a0b4e1363cd7e5d7ab8b5473

Observation b03d77f6-e6e4-42d3-a977-bda84fb4cd67 · outbound

This paper cites A rag-based medical assistant especially for infectious diseases.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications A rag-based medical assistant especially for infectious diseases

Reference 23

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source=pdf_text observed=2026-08-12T15:34:25.549537Z digest=sha256:8a525ea69be2462b9d3222cb495f5d3627428c2e8940dd06844eb80bf2b5474f

Observation ec89538c-59dc-401c-a8ce-8f75015a9c6f · outbound

This paper cites Medical Graph RAG: Towards Safe Medical Large Language Model via Graph Retrieval-Augmented Generation.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Medical Graph RAG: Towards Safe Medical Large Language Model via Graph Retrieval-Augmented Generation

Reference 24

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source=pdf_text observed=2026-08-12T15:34:25.566758Z digest=sha256:cad89eb20484ba09ce2282f0963af4ea661cbaf9190c63f0010b2269799b6cc6

Observation fad76100-6f4f-4a43-9c2a-d1c0cee16704 · outbound

This paper cites Follow my instruction and spill the beans: Scalable data extraction from retrieval-augmented generation systems.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Follow my instruction and spill the beans: Scalable data extraction from retrieval-augmented generation systems

Reference 25

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source=pdf_text observed=2026-08-12T15:34:25.577258Z digest=sha256:f0a6f743c0fad57c1fe58d66dd8e750a7d85308cc11e8e7aece64b5852744387

Observation 2816eb98-da99-41ef-ba5e-eb30557fab70 · outbound

This paper cites The good and the bad: Exploring privacy issues in retrieval-augmented generation (RAG).

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications The good and the bad: Exploring privacy issues in retrieval-augmented generation (RAG)

Reference 26

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source=pdf_text observed=2026-08-12T15:34:25.587260Z digest=sha256:8fd96bb725128ba1a479a9dac9585940181c44d302e474c3bd4b5f029932f998

Observation 4971352d-a5c7-4b97-9a62-49cc096ecc36 · outbound

This paper cites Unleashing Worms and Extracting Data: Escalating the Outcome of Attacks against RAG-based Inference in Scale and Severity Using Jailbreaking.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Unleashing Worms and Extracting Data: Escalating the Outcome of Attacks against RAG-based Inference in Scale and Severity Using Jailbreaking

Reference 27

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source=pdf_text observed=2026-08-12T15:34:25.602580Z digest=sha256:8ca10281a30ffc7bf5fa3ebc22609ef74b2da76cca0d21a7519190de4b2d7add

Observation 9d1df88c-bb0e-4c09-ac4e-6dd00c2256b5 · outbound

This paper cites Bytedance coze, access in 2024.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Bytedance coze, access in 2024

Reference 28

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source=pdf_text observed=2026-08-12T15:34:25.608196Z digest=sha256:c9a3cba6b2daf6164c4e906da54588151dfd5f2326c220aba5cb148aca90380c

Observation 643eb61c-ed1b-4e23-8552-76417962b63f · outbound

This paper cites Openai gpts, access in 2024.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Openai gpts, access in 2024

Reference 29

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source=pdf_text observed=2026-08-12T15:34:25.615814Z digest=sha256:0660951ccc5c6d973c2ad2f595b4abd7689ac475f7053749a908f3903619c680

Observation a3226ac6-df27-463b-8f0f-825bc807eda8 · outbound

This paper cites Openai gpts, access in 2024.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Openai gpts, access in 2024

Reference 30

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no resolver link, observed 2026-08-12T15:34:25.621109Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T15:34:25.621109Z digest=sha256:84c82a968570eff6b3e5ab6bf5909521a1f5dd7a2afa929a0d923a6478dcb821

Observation a88aef55-70ee-42ba-8732-d02578e1dff1 · outbound

This paper cites Bytedance coze, access in 2024.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Bytedance coze, access in 2024

Reference 31

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source=pdf_text observed=2026-08-12T15:34:25.627955Z digest=sha256:0a3001ac3ea3737f74c1e3b3ab6392191d915cc152439ec29e5c08da1cbbeb59

Observation 255d914c-773c-48d5-8b5a-25f2f9b9879c · outbound

This paper cites Owasp top 10 for llm applications, access in 2023.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Owasp top 10 for llm applications, access in 2023

Reference 32

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source=pdf_text observed=2026-08-12T15:34:25.636650Z digest=sha256:cc5889ed08394fdafa73710b445545e4ead5ac9358b0412c47b3167cc06b41d5

Observation fd52842b-b5c8-4c99-8643-03d92aab1f3a · outbound

This paper cites Ignore previous prompt: Attack techniques for language models.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Ignore previous prompt: Attack techniques for language models

Reference 33

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source=pdf_text observed=2026-08-12T15:34:25.641847Z digest=sha256:f603fbcecbfd9b539d3258c03295f6c9ac898563b542b33e6459519a9527e0ec

Observation 6011372c-18bb-4816-b8ec-004a63b35fac · outbound

This paper cites Formalizing and benchmarking prompt injection attacks and defenses.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Formalizing and benchmarking prompt injection attacks and defenses

Reference 34

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source=pdf_text observed=2026-08-12T15:34:25.648526Z digest=sha256:ddae106eaab96ba75a19b125374ddab846e19601f080cc8bbf0be1e7f2879dd1

Observation 9dcd3946-019b-438a-82ec-2d75acbc5f5f · outbound

This paper cites Tensor trust: Interpretable prompt injection attacks from an online game.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Tensor trust: Interpretable prompt injection attacks from an online game

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-12T15:34:28.810877Z

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=2026-08-12T15:34:25.654966Z digest=sha256:9f61865e42692228db22d16245d2ad8aa5c14a4926e3dcabe7b13a301dfefe79

Observation b3ef2fdd-2393-47f0-b52e-c5e6bce38ade · outbound

This paper cites Assessing prompt injection risks in 200+ custom gpts.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Assessing prompt injection risks in 200+ custom gpts

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-12T15:34:28.778076Z

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=2026-08-12T15:34:25.664352Z digest=sha256:5537ba14d83aeca8b422ad7a4f5dee908239b5512a8bca5a88a13f4f924cc56a

Observation 8f7edd3a-28e1-44dd-9552-1b72fb703062 · outbound

This paper cites Delimiters won’t save you from prompt injec- tion, 2024.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Delimiters won’t save you from prompt injec- tion, 2024

Reference 37

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raw_fallback, observed 2026-08-12T15:34:28.751980Z

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=2026-08-12T15:34:25.678789Z digest=sha256:20de1f255e38ded5a886db740d3570f7a13054025a5c1f195462f50f5b553d1d

Observation fa8e24da-2fe9-47bb-badb-b9c64242142d · outbound

This paper cites A survey on large language model based autonomous agents.Frontiers of Computer Science, 18(6):186345, 2024.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications A survey on large language model based autonomous agents.Frontiers of Computer Science, 18(6):186345, 2024

Reference 38

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:25.687846Z digest=sha256:834e79bd5f1db3f19ae2e4d92829c9b2151ed1a8f57bf21d400dd6740802d0e8

Observation 6b736009-65f4-4a6a-96b7-78a553de8e37 · outbound

This paper cites The Rise and Potential of Large Language Model Based Agents: A Survey.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications The Rise and Potential of Large Language Model Based Agents: A Survey

Reference 39

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no resolver link, observed 2026-08-12T15:34:25.702296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:25.702296Z digest=sha256:4b0f3825a298a6e76b56e983a4b1016013ea987d8a1ee1b3581da727b2390d6e

Observation 500a4d06-5fe7-4fdb-8512-661fe65ca02c · outbound

This paper cites A multitask, multilingual, multimodal evaluation of chatgpt on reasoning, hallucination, and interactivity.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications A multitask, multilingual, multimodal evaluation of chatgpt on reasoning, hallucination, and interactivity

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:34:28.702281Z

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=2026-08-12T15:34:25.710776Z digest=sha256:99ec15861af3e477b9f3ac88473ebbf7b01dbe31363e0edd119bcc690dd600fd

Observation 288c494c-998f-4760-932b-dfadf280b039 · outbound

This paper cites Modelscope-agent: Building your customizable agent system with open-source large language models.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Modelscope-agent: Building your customizable agent system with open-source large language models

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:34:28.674026Z

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=2026-08-12T15:34:25.719268Z digest=sha256:427fc38f0c9d2cbdf9528190df27e6fc4f8f9d20620ff5b1b85a121ad6c2a6dc

Observation 12f70592-1510-409b-9aed-b05c9aaa5415 · outbound

This paper cites Autogpt, 2023.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Autogpt, 2023

Reference 42

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raw_fallback, observed 2026-08-12T15:34:28.654770Z

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=2026-08-12T15:34:25.733535Z digest=sha256:684445387d3e0850349a9a35fe166017fc6e36c53bae58fbd74098522150a277

Observation f179d9c2-3daf-4458-92bc-a6181c26a262 · outbound

This paper cites Autogen: Enabling next-gen llm applications via multi-agent conversation.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Autogen: Enabling next-gen llm applications via multi-agent conversation

Reference 43

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no resolver link, observed 2026-08-12T15:34:25.746926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:25.746926Z digest=sha256:43e2ee1849149a5a4d2471a1cc1dbf685ee14e4f3e67f8651ae7ac7576f1a00d

Observation 59b30970-5b1b-4822-b4d0-07c2dc85a993 · outbound

This paper cites Langchain, access in 2024.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Langchain, access in 2024

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:34:28.608910Z

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=2026-08-12T15:34:25.759239Z digest=sha256:a8acda7c5008ad0420504230b50fff0215f91c16d316fc88ff2b1142738079d9

Observation 5fed379d-fe60-442c-b309-aa6c07b577b3 · outbound

This paper cites Tree of Attacks: Jailbreaking Black-Box LLMs Automatically.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Tree of Attacks: Jailbreaking Black-Box LLMs Automatically

Reference 45

Resolution
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no resolver link, observed 2026-08-12T15:34:25.767467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:25.767467Z digest=sha256:b81584e482c791a738138236e3b80b1852f8f670748e612c94d6423bdf8c45a6

Observation 51c03718-1f6a-4337-8adc-b5a10402d8bb · outbound

This paper cites A systematic survey of automatic prompt optimization techniques.arXiv preprint arXiv:2502.16923, 2025.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications A systematic survey of automatic prompt optimization techniques.arXiv preprint arXiv:2502.16923, 2025

Reference 46

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no resolver link, observed 2026-08-12T15:34:25.773721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:25.773721Z digest=sha256:31a8a10c8fcc53aff1d61004e147bf97a181017d3a0d0416df4fbf26303485ac

Observation 10c9274b-a669-4a6a-a53d-f1ed159f7122 · outbound

This paper cites The enron corpus: A new dataset for email classification research.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications The enron corpus: A new dataset for email classification research

Reference 47

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no resolver link, observed 2026-08-12T15:34:25.781498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:25.781498Z digest=sha256:48f6650f2193ede55f02aacc07d0124d734a1a8442b41746bc62734a1e3e1905

Observation b60f4a1b-3437-41e4-84b2-a3dbc0bfbcb5 · outbound

This paper cites [Online].

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications [Online]

Reference 48

Resolution
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raw_fallback, observed 2026-08-12T15:34:28.561506Z

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=2026-08-12T15:34:25.789610Z digest=sha256:832db7a95f43767f77eaefdcc12ce6148b2cbebd5ed507b28b26adba9b3832d8

Observation cffbdc55-57a8-4a44-93c2-afd14d799de6 · outbound

This paper cites Harry potter and the sorcerer’s stone, 2002.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Harry potter and the sorcerer’s stone, 2002

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:34:28.528847Z

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=2026-08-12T15:34:25.803784Z digest=sha256:5b71af860418e4b4f9bd06d83348a239fa91a957139034a3cc02841351d2b9b6

Observation 4261d929-c47f-46d7-aa06-8a131069c472 · outbound

This paper cites [Online].

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications [Online]

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:34:28.510476Z

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=2026-08-12T15:34:25.817554Z digest=sha256:f0e59206635117ecfbc361794e1cca4ea03d1d11cae2b463cbeb874d35acb625

Observation a53c07c0-9bab-41c6-9e36-bf7adc6b945f · outbound

This paper cites Eed: Extended edit distance measure for machine translation.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Eed: Extended edit distance measure for machine translation

Reference 51

Resolution
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no resolver link, observed 2026-08-12T15:34:25.825131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:25.825131Z digest=sha256:9b93fa7569cbfbd0c10550f4595fd9dfb5d2849d20640a8beb0d40f346711987

Observation d9bbd205-f4ca-4f84-8b22-234f989113a9 · outbound

This paper cites Pleak: Prompt leaking attacks against large language model applications.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Pleak: Prompt leaking attacks against large language model applications

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:34:28.469402Z

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=2026-08-12T15:34:25.835699Z digest=sha256:af5f962c621703cce0699414000d7c04118a6f7d042349f84687395d43839cd2

Observation adf2f1b9-d453-4938-b804-24549a2a5f40 · outbound

This paper cites Optimization-based Prompt Injection Attack to LLM-as-a-Judge.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Optimization-based Prompt Injection Attack to LLM-as-a-Judge

Reference 53

Resolution
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no resolver link, observed 2026-08-12T15:34:25.861020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:25.861020Z digest=sha256:76ea00d3f7ce5bf5ea49e7641fea1704564f75a40b66020390dddb9c15b73166

Observation 797f36df-48f7-4c85-892f-fe3318e39910 · outbound

This paper cites Automatic and Universal Prompt Injection Attacks against Large Language Models.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Automatic and Universal Prompt Injection Attacks against Large Language Models

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-12T15:34:25.880075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:25.880075Z digest=sha256:bff68a18469fb2a51a98795f544846c892489940da93092b48a4ddc73fab01ae

Observation 7fc6c2f4-56bd-4b92-9533-3cb3b2425591 · outbound

This paper cites StruQ: Defending Against Prompt Injection with Structured Queries.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications StruQ: Defending Against Prompt Injection with Structured Queries

Reference 55

Resolution
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no resolver link, observed 2026-08-12T15:34:25.888843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:25.888843Z digest=sha256:39a1076c26c23007ea18776a3a86cbb28a239114c23c35df3344c62b9c56834e

Observation 9137548e-9d65-4d63-870c-db1024ff4da1 · outbound

This paper cites Get my drift? Catching LLM Task Drift with Activation Deltas.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Get my drift? Catching LLM Task Drift with Activation Deltas

Reference 56

Resolution
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no resolver link, observed 2026-08-12T15:34:25.895226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:25.895226Z digest=sha256:7596f16196d34f40415a382fbe72901e1d24178e10bfb8c99539d5f8a8cfb53d

Observation fb7cec27-ee2e-4f96-938f-2db6c1eefe71 · outbound

This paper cites The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions

Reference 57

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no resolver link, observed 2026-08-12T15:34:25.906733Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:25.906733Z digest=sha256:4cf41e7761980abcc2e64319fa59d5004302c063d7fd1b2c77ce0c9bf7837a1f

Observation c198342c-57c7-4708-bee3-3ab481c97597 · outbound

This paper cites Extracting training data from large language models.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Extracting training data from large language models

Reference 58

Resolution
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raw_fallback, observed 2026-08-12T15:34:28.445410Z

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=2026-08-12T15:34:25.911468Z digest=sha256:6bf44391ba047429db80d23f7c00595bd4c425cf8131d1d02bd8cdc015a353a2

Observation 8a119bb7-b9c9-49f1-acd4-48871a1fdbe5 · outbound

This paper cites Are large pre-trained language models leaking your personal information? In 2022 Findings of the Association for Computational Linguistics: EMNLP 2022, 2022.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Are large pre-trained language models leaking your personal information? In 2022 Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:34:28.424643Z

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=2026-08-12T15:34:25.918823Z digest=sha256:13570260b60cf0739ada3a582f7d28c0357fe7da32a80302abfb1f2e2c6db53c

Observation 27ca3c03-ba36-4c5c-8f0c-ba88e006ca13 · outbound

This paper cites Multi-step jailbreaking privacy attacks on chatgpt.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Multi-step jailbreaking privacy attacks on chatgpt

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:34:28.403202Z

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=2026-08-12T15:34:25.928465Z digest=sha256:f090e2a40203f2313fa1614625d6d73c1a5ac6f0e6997ab1de4eb4a38ea62854

Observation 6bb42d7d-cdaf-49fb-b5a8-f20c23e68118 · outbound

This paper cites Ethicist: Targeted training data extraction through loss smoothed soft prompting and calibrated confidence estimation.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Ethicist: Targeted training data extraction through loss smoothed soft prompting and calibrated confidence estimation

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:34:28.376752Z

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=2026-08-12T15:34:25.933436Z digest=sha256:308aa4c18f0353348a792684753174078210c9b31ee5b9af7a8ba015410efa6e

Observation 51de4917-2e19-44bc-8e5b-acc47bd39224 · outbound

This paper cites Text Revealer: Private Text Reconstruction via Model Inversion Attacks against Transformers.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Text Revealer: Private Text Reconstruction via Model Inversion Attacks against Transformers

Reference 62

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no resolver link, observed 2026-08-12T15:34:25.941836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:25.941836Z digest=sha256:5320017a698d05245e6fe8a6e8524413da886564f0cd28e3680afc1af60df2ec

Observation e527c3ec-8d7d-4814-a78b-67c8bce8d0a4 · outbound

This paper cites Canary extraction in natural language understanding models.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Canary extraction in natural language understanding models

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:34:28.340224Z

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=2026-08-12T15:34:25.954060Z digest=sha256:6442c1127902ae1352dcd607adc36326b355e288f011328fc3f4f8a2adf3f687

Observation 3e2ff40f-abd9-4af2-8c49-19c5ed148bd4 · outbound

This paper cites Analyzing leakage of personally iden- tifiable information in language models.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Analyzing leakage of personally iden- tifiable information in language models

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:34:28.313743Z

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=2026-08-12T15:34:25.959845Z digest=sha256:c5422dae192072682518e1b90e57fbdb4ec28b6d123e9b48e8826302f4b88bed

Observation f58e6535-1dfe-458b-b565-10b3c71caefb · outbound

This paper cites Propile: Probing privacy leakage in large language models.Advances in Neural Information Processing Systems, 36, 2024.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Propile: Probing privacy leakage in large language models.Advances in Neural Information Processing Systems, 36, 2024

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:34:28.277025Z

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=2026-08-12T15:34:25.966676Z digest=sha256:b21c400c4601efbf8df04eb07ff1d2a7193a55a8aaafef0aa51754aea1dfde29

Observation 1da1af02-2afd-47f4-b7df-40631a1e4464 · outbound

This paper cites Quantifying association capabilities of large language models and its implications on privacy leakage.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Quantifying association capabilities of large language models and its implications on privacy leakage

Reference 66

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verified fuzzy
raw_fallback, observed 2026-08-12T15:34:28.242226Z

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=2026-08-12T15:34:25.974965Z digest=sha256:1307d19dcb06ae859c39352506cd147fbdc20f74230982bc65d6fd6e1669381c

Observation cf6d7924-3330-4df9-859a-fc152e67070a · outbound

This paper cites Quantifying memorization across neural language models.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Quantifying memorization across neural language models

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:34:28.218257Z

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=2026-08-12T15:34:25.986274Z digest=sha256:55345e92256f01673327c3b48e104479938635562340fbd3920a699a9b0b6fec

Observation 47a5f868-06aa-4f99-a433-117e15d70f80 · outbound

This paper cites Delimiters won’t save you from prompt injection,.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Delimiters won’t save you from prompt injection,

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:34:28.187772Z

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=2026-08-12T15:34:25.994695Z digest=sha256:bc33f3126d4918ca081892202ca48b68d2cad0cbe4b16aab0a923ab276403536

Observation b18ce7b2-a6e0-4335-b395-d6e90932a2e7 · outbound

This paper cites Don’t you (forget nlp): Prompt injection with control characters in chat- gpt.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Don’t you (forget nlp): Prompt injection with control characters in chat- gpt

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:34:28.126278Z

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=2026-08-12T15:34:26.009782Z digest=sha256:e52dd2632b18929b71fb56c86eddd221df17c2c33720e1b65a7ed3bd2e0af694

Observation 380d4e74-030b-4124-9ce5-5b6741b2452b · outbound

This paper cites Efficient Universal Goal Hijacking with Semantics-guided Prompt Organization.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Efficient Universal Goal Hijacking with Semantics-guided Prompt Organization

Reference 70

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unresolved
no resolver link, observed 2026-08-12T15:34:26.019681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:26.019681Z digest=sha256:8ede042d2adbda4d5d702392febd1a76caf5fadd0b13f7731d222aee6dab3d29

Observation bd94adf9-5763-4a64-9f99-193c4535f3ea · outbound

This paper cites Universal and Transferable Adversarial Attacks on Aligned Language Models.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 71

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:26.028554Z digest=sha256:fe7e46458b8bd155475bb35707496485e7c1a2c766e4cb91d7001263470cd61e

Observation 4f30b39f-2c2a-401d-b891-40dce09aa320 · outbound

This paper cites Effective Prompt Extraction from Language Models.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Effective Prompt Extraction from Language Models

Reference 72

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no resolver link, observed 2026-08-12T15:34:26.034571Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:26.034571Z digest=sha256:09df611fa5642faa60565dae0279c4f3ae17de1cc009feaec86a6f93483e8031

Observation b097165e-28e5-4d70-a8c6-1b100b080b11 · outbound

This paper cites PRSA: Prompt Stealing Attacks against Real-World Prompt Services.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications PRSA: Prompt Stealing Attacks against Real-World Prompt Services

Reference 73

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:26.047371Z digest=sha256:259c07bbba7fc281301e907151e3a59bd002e516c7f01745935a6ce6a1cd0779

Observation b2322a73-9c8f-434c-a2f1-e80f2fc90cdd · outbound

This paper cites Benchmarking and Defending Against Indirect Prompt Injection Attacks on Large Language Models.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Benchmarking and Defending Against Indirect Prompt Injection Attacks on Large Language Models

Reference 74

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no resolver link, observed 2026-08-12T15:34:26.057969Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T15:34:26.057969Z digest=sha256:d44d4d056ad793c196b8116ac0e04583fad7bcb2001d113d00b01422e8e15d05

Observation b29421f0-378f-408e-a8ec-5b5683af8c78 · outbound

This paper cites Jailbreaking Black Box Large Language Models in Twenty Queries.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Jailbreaking Black Box Large Language Models in Twenty Queries

Reference 75

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no resolver link, observed 2026-08-12T15:34:26.064097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:26.064097Z digest=sha256:b8d42aef02a8be808064ddb409d1a482de23b4413bb190239bb1664ad2347b74

Observation b6c5334c-0525-497a-88b9-915b739a0a74 · outbound

This paper cites "Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications "Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models

Reference 76

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no resolver link, observed 2026-08-12T15:34:26.071062Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:26.071062Z digest=sha256:a00e0aa996fce56e59317b5dae7fc62ba0225047209f0fbb16f2a846b290eadc

Observation e6f9ebe4-6202-4127-8421-233670ae64f7 · outbound

This paper cites Masterkey: Automated jailbreaking of large language model chatbots.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Masterkey: Automated jailbreaking of large language model chatbots

Reference 77

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verified fuzzy
raw_fallback, observed 2026-08-12T15:34:28.096597Z

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=2026-08-12T15:34:26.079606Z digest=sha256:8b8fa3f804d7a8212ae94bd824e55025fd01b555bb2fa9f3912d49a5b91df6f7

Observation f3a3da66-3e42-44cf-a286-21b2e6394892 · outbound

This paper cites Great, Now Write an Article About That: The Crescendo Multi-Turn LLM Jailbreak Attack.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Great, Now Write an Article About That: The Crescendo Multi-Turn LLM Jailbreak Attack

Reference 78

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no resolver link, observed 2026-08-12T15:34:26.085989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:26.085989Z digest=sha256:e87d0cd36be92cfa6c2a166e109bc745264614dc934f35ed5d110df7d47ae96d

Observation 89792c7d-18b6-4030-8417-c1ffb6c385df · outbound

This paper cites Practical Membership Inference Attacks against Fine-tuned Large Language Models via Self-prompt Calibration.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Practical Membership Inference Attacks against Fine-tuned Large Language Models via Self-prompt Calibration

Reference 79

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no resolver link, observed 2026-08-12T15:34:26.096668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:26.096668Z digest=sha256:a4011c89c12badccdde1a59c68a85bc8f21f0c1e15f4aad739c87f88afde37c5

Observation c66d1a50-2c07-4557-b933-6f2df2468ab5 · outbound

This paper cites Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models

Reference 80

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no resolver link, observed 2026-08-12T15:34:26.107803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:26.107803Z digest=sha256:4eb6a8b9de343fb1f91c1fbdd9ebd878585f79f781c6c657ad3f0c4b09b417de

Observation 84c458ae-1bb0-4160-8318-b5e07df3a45c · outbound

This paper cites Tensor trust: Interpretable prompt injection attacks from an online game.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Tensor trust: Interpretable prompt injection attacks from an online game

Reference 81

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verified fuzzy
raw_fallback, observed 2026-08-12T15:34:28.073449Z

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=2026-08-12T15:34:26.113215Z digest=sha256:63f601748c9c0dc1ad499e2857c65f12d982c00fae6887d3e96d732d8b8b33bd

Observation bc14caff-abb4-4d95-929d-12ec67c70ab2 · outbound

This paper cites Data stealing attacks against large language models via backdooring.Electronics, 13(14):2858, 2024.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Data stealing attacks against large language models via backdooring.Electronics, 13(14):2858, 2024

Reference 82

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verified fuzzy
raw_fallback, observed 2026-08-12T15:34:28.050920Z

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=2026-08-12T15:34:26.129246Z digest=sha256:74b655aafa7d359cbe111ab437bf6747dc7c75555959c6930322f2f330463d6e

Observation 54d2ebe1-170a-4ee1-9934-bad58fd454dd · outbound

This paper cites Badpre: Task-agnostic backdoor attacks to pre-trained nlp foundation models.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Badpre: Task-agnostic backdoor attacks to pre-trained nlp foundation models

Reference 83

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verified fuzzy
raw_fallback, observed 2026-08-12T15:34:28.017974Z

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=2026-08-12T15:34:26.141364Z digest=sha256:1e01f4dc76ffb470ff78ca9caffa5e235536c6c030f3c2390c18e3c05b6e4a10

Observation 69c618d2-8752-4933-8fae-db2178f15644 · outbound

This paper cites On the exploitability of instruction tuning.Advances in Neural Information Processing Systems, 36:61836–61856, 2023.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications On the exploitability of instruction tuning.Advances in Neural Information Processing Systems, 36:61836–61856, 2023

Reference 84

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T15:34:26.147700Z digest=sha256:99e917b88b22e44aa3154e1a1ca9a6ec10ddfd594d224e035d063d6947295de5

Observation ed7f6ec3-9c2b-448b-b8a5-560fc0de1906 · outbound

This paper cites Prompt as triggers for backdoor attack: Examining the vulnerability in language models.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Prompt as triggers for backdoor attack: Examining the vulnerability in language models

Reference 85

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verified fuzzy
raw_fallback, observed 2026-08-12T15:34:27.958437Z

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=2026-08-12T15:34:26.158024Z digest=sha256:18ca9277969ca43920570acd3fe4b987f3a435ec090c0e0b628c90b332f52363

Observation c50e3899-efa8-4949-a022-a6e51df335f5 · outbound

This paper cites No- table: Transferable backdoor attacks against prompt-based nlp models.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications No- table: Transferable backdoor attacks against prompt-based nlp models

Reference 86

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verified fuzzy
raw_fallback, observed 2026-08-12T15:34:27.923247Z

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=2026-08-12T15:34:26.162451Z digest=sha256:310d287bef5ed7ad71c8f6d6286e70dfca5a936af145969a34d885528dbd259c

Observation 486bdd61-d959-4ab2-a51b-87eaa5710ec7 · outbound

This paper cites Backdoor attacks for in-context learning with language models.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Backdoor attacks for in-context learning with language models

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:34:27.896601Z

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=2026-08-12T15:34:26.167987Z digest=sha256:9bdc29b3bedd6ae63b46603f080cadbda9bf364a12b5cc191f7be148c90c345e

Observation f776a8e4-7e49-493a-90e5-75122ef8dfb3 · outbound

This paper cites UOR: Universal Backdoor Attacks on Pre-trained Language Models.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications UOR: Universal Backdoor Attacks on Pre-trained Language Models

Reference 88

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no resolver link, observed 2026-08-12T15:34:26.173834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:26.173834Z digest=sha256:3fe9804300cf1356f8b9124cc120d1d576c3a4ff202532ae56fd8d91f4c4c423

Observation f7d3faca-ff1a-468f-9133-908b6f1e7f54 · outbound

This paper cites {context}.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications {context}

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:34:27.863093Z

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=2026-08-12T15:34:26.181761Z digest=sha256:50e07ed29aecc5c2ca92c65311556a26cba3110c797c9bfebf199dbf5b9aafb9

Observation c9c79eef-15be-4808-b17e-2b0b9e485854 · outbound

This paper cites an unresolved cited work.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Unresolved cited work

Reference 91

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raw_fallback, observed 2026-08-12T15:34:27.828559Z

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=2026-08-12T15:34:26.187624Z digest=sha256:6b8eb76bde39ac6627b96800b6686f67fdfcdaf4b490bb36c5110a9757ef38d5

Observation caa0abfa-c633-4dfe-9a7b-a61cda9fb71d · outbound

This paper cites an unresolved cited work.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Unresolved cited work

Reference 92

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unresolved
raw_fallback, observed 2026-08-12T15:34:27.809824Z

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=2026-08-12T15:34:26.197552Z digest=sha256:19d4f96a6ce16d243019424c68385d62fb0d130c5bbe8441963d120355582f0a

Observation 162ca48d-4ebc-429e-b0c8-f13e814a1d64 · outbound

This paper cites Begin! generated text: Here, we present the system prompts designed forCopy- BreakRAG, tailored for two different scenarios: Untargeted Attack and Targeted Attack.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Begin! generated text: Here, we present the system prompts designed forCopy- BreakRAG, tailored for two different scenarios: Untargeted Attack and Targeted Attack

Reference 93

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verified fuzzy
raw_fallback, observed 2026-08-12T15:34:27.791278Z

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=2026-08-12T15:34:26.207632Z digest=sha256:476634e2ee6d0a0ce5a85f37e40d94154eb3ca76e8b5866ca5e22be6fce09386

Observation 6e7bf802-1efd-4d88-ad55-37efd571c651 · outbound

This paper cites an unresolved cited work.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Unresolved cited work

Reference 94

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no resolver link, observed 2026-08-12T15:34:26.213819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:26.213819Z digest=sha256:f0c81512acdc8784602827f8440bd0a325c5f6b3e05b969e69f61fe54941e344

Observation 17bd0be5-90cb-48c3-aa55-f1b233eb4fd9 · outbound

This paper cites an unresolved cited work.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Unresolved cited work

Reference 95

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unresolved
raw_fallback, observed 2026-08-12T15:34:27.723576Z

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=2026-08-12T15:34:26.219792Z digest=sha256:6a2772d57d16ce8234343d2547425ae1cac4b39a97ff08f109ba5fceb4d19669

Observation 90ccd9ee-db44-4eaf-a299-f3f073ae4685 · outbound

This paper cites an unresolved cited work.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Unresolved cited work

Reference 96

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no resolver link, observed 2026-08-12T15:34:26.224940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:26.224940Z digest=sha256:0bf03f0606dd08ddf26954525e8dc439867531a7612834f2b10ded491dabc7f2

Observation 17884dd8-7a6a-4d06-a595-ab165489ff6b · outbound

This paper cites an unresolved cited work.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Unresolved cited work

Reference 97

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unresolved
no resolver link, observed 2026-08-12T15:34:26.230440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:34:26.230440Z digest=sha256:b7429eb23bea123fbf982b9659f7112298407c7704abe97920bf09256aee8fbb

Observation d5ac2512-5356-4ecb-8f8d-e1f9502fc95e · outbound

This paper cites Data: {chunk} Output Format: 1.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Data: {chunk} Output Format: 1

Reference 98

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verified fuzzy
raw_fallback, observed 2026-08-12T15:34:27.647975Z

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=2026-08-12T15:34:26.249199Z digest=sha256:039c6bd49df8a31a687e85e6875dade991e3fface6a441eb9b243ce0d3f91094

Observation 673edfdf-d63c-4431-a5a0-8dc8b3183e80 · outbound

This paper cites an unresolved cited work.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Unresolved cited work

Reference 99

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unresolved
raw_fallback, observed 2026-08-12T15:34:27.626207Z

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=2026-08-12T15:34:26.257764Z digest=sha256:2b3bb46881a440fb32502260edd1b58031381ee733b22940127be6752ae9c2ca

Observation 79734e8f-7294-4b2e-95b1-010ca4533f2a · outbound

This paper cites an unresolved cited work.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Unresolved cited work

Reference 100

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unresolved
raw_fallback, observed 2026-08-12T15:34:27.608801Z

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=2026-08-12T15:34:26.263341Z digest=sha256:972ae13c8df9ffb97e57baaaba9edb8c9a9dc0da31dfe7a125e40c7baa321a73

Observation e2904279-b88f-4137-8bdd-05dbd6ed134a · outbound

This paper cites an unresolved cited work.

Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications Unresolved cited work

Reference 101

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unresolved
raw_fallback, observed 2026-08-12T15:34:27.564992Z

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=2026-08-12T15:34:26.274730Z digest=sha256:9cb262ac269477ddd3f57a475ebee3f16e9c2a054045f817a3cddec9d5122bc4

Pith citing papers

Observation 9997a7d4-40b9-42ec-a01c-df6866c1fed5 · inbound

Pirates of the RAG: Adaptively Attacking LLMs to Leak Knowledge Bases cites this paper.

Pirates of the RAG: Adaptively Attacking LLMs to Leak Knowledge Bases Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 31

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unresolved
no resolver link, observed 2026-08-11T04:54:11.453761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T04:54:11.453761Z digest=sha256:f92ffe8ca86230ff1c0ca37d533f9bcf8b7e12b55ed7e70a4c01de6ddda4cc78

Observation bc8aa546-c75b-4337-b949-a217a0c8a94e · inbound

Riddle Me This! Stealthy Membership Inference for Retrieval-Augmented Generation cites this paper.

Riddle Me This! Stealthy Membership Inference for Retrieval-Augmented Generation Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 21

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no resolver link, observed 2026-08-09T19:32:34.261236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T19:32:34.261236Z digest=sha256:e3e4403414e677adc61bbadcca5e8d6e78f67bdffa168f836bc184683081d6fd

Observation b585542c-e123-40a6-9d1b-29df86cf6fb8 · inbound

Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey cites this paper.

Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 77

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unresolved
no resolver link, observed 2026-08-08T19:15:25.311316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:15:25.311316Z digest=sha256:7b397bb677e9765eaaef546b30d40abd31e754cb9674b0e689eec1225deb3375

Observation b6779668-fdef-40ec-9492-3702861ef1a1 · inbound

Towards Copyright Protection for Knowledge Bases of Retrieval-augmented Language Models via Reasoning cites this paper.

Towards Copyright Protection for Knowledge Bases of Retrieval-augmented Language Models via Reasoning Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 21

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unresolved
no resolver link, observed 2026-08-08T16:16:48.254855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T16:16:48.254855Z digest=sha256:4e7c1cf90e820a534c2dc1fa961d9a63ab5e62ffaf9ab07183ca45f7d685f56a

Observation ba73458c-46e0-449c-a172-0012277e0c68 · inbound

A Survey of Scaling in Large Language Model Reasoning cites this paper.

A Survey of Scaling in Large Language Model Reasoning Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 68

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:22:09.400785Z

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=2026-05-22T21:20:07.238992Z digest=sha256:9dfe992497034d2fb2e9df2e8ae77909079ba09ccb4e0bf52fa52695b09befc7

Observation 48ef783f-c0b5-4605-bd58-896bbd8bfa9b · inbound

Privacy-Preserving Federated Embedding Learning for Localized Retrieval-Augmented Generation cites this paper.

Privacy-Preserving Federated Embedding Learning for Localized Retrieval-Augmented Generation Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 34

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unresolved
no resolver link, observed 2026-08-16T06:05:57.556607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T06:05:57.556607Z digest=sha256:b7b20e9fd97db9beccf9d41c112b71541d8dde5cbec4b795ea97eabbd6f0d4bc

Observation b92f7b41-9985-4c99-b478-493066122a2e · inbound

Distributed Retrieval-Augmented Generation cites this paper.

Distributed Retrieval-Augmented Generation Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 29

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unresolved
no resolver link, observed 2026-08-16T04:46:38.677153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:46:38.677153Z digest=sha256:97ff5b2f65288679aca8f8e7fe385c8b850a862c44c2e6c21125342173544b75

Observation 4e07d835-3440-4e31-bb7c-0c3e86615258 · inbound

Security of Internet of Agents: Attacks and Countermeasures cites this paper.

Security of Internet of Agents: Attacks and Countermeasures Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 58

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unresolved
no resolver link, observed 2026-08-15T22:26:18.005246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:26:18.005246Z digest=sha256:4c62e85839bddac6a435f387c5fea367e87726e2e4dc3ad2a89f15a93fcd99a6

Observation 5bc2f338-6643-4a2c-b706-dbd069c44919 · inbound

Think Twice Before You Act: Enhancing Agent Behavioral Safety with Thought Correction cites this paper.

Think Twice Before You Act: Enhancing Agent Behavioral Safety with Thought Correction Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 39

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unresolved
no resolver link, observed 2026-08-15T21:05:35.024384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:05:35.024384Z digest=sha256:78e669966bf10d6cebaabff0cad8f2039ac0359743a2df6531b865f49b168c7e

Observation 11ef88db-0564-4add-aea8-30e540ca2488 · inbound

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation cites this paper.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 36

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unresolved
no resolver link, observed 2026-08-07T14:32:57.001435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:57.001435Z digest=sha256:ae8f27e32f09c7cdcf2742d4face6a7e78b027ace6453785eda2d44f3879dbbd

Observation d41199b9-8103-4ce2-b16f-939dd3d6b5c0 · inbound

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem cites this paper.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 77

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unresolved
no resolver link, observed 2026-08-15T19:45:09.832411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:45:09.832411Z digest=sha256:a7db59cc31e543f46d708183d7bad7c48ede8b8ff5a4ca293885dcbf43663b44

Observation 5034812a-5b1b-49cb-965a-3983366067ff · inbound

DCMI: A Differential Calibration Membership Inference Attack Against Retrieval-Augmented Generation cites this paper.

DCMI: A Differential Calibration Membership Inference Attack Against Retrieval-Augmented Generation Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 21

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unresolved
no resolver link, observed 2026-08-05T04:42:13.727824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T04:42:13.727824Z digest=sha256:cd76a4a0a04ecf34a32b9a53f9ce646fd128088b9d9509aefe2d55d1bc271a90

Observation b1a97668-23ef-4fe4-bb52-20e3a61e2dd8 · inbound

External Data Extraction Attacks against Retrieval-Augmented Large Language Models cites this paper.

External Data Extraction Attacks against Retrieval-Augmented Large Language Models Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 28

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unresolved
no resolver link, observed 2026-08-04T12:43:24.684491Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T12:43:24.684491Z digest=sha256:3968deea6d8b8430a4e2c74a1ad09754f7948d7478ac2ce9965f98b9c15015f7

Observation da8ec137-a077-422c-901c-cd1646fd02c6 · inbound

SPARK: Search Personalization via Agent-Driven Retrieval and Knowledge-sharing cites this paper.

SPARK: Search Personalization via Agent-Driven Retrieval and Knowledge-sharing Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 21

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unresolved
no resolver link, observed 2026-08-03T13:31:10.286463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T13:31:10.286463Z digest=sha256:88599327d20653d0e83c973231ff5d865219f018883c85769a4527ffa3d88623

Observation 48f68ae5-1b3b-4265-99ed-235828e82f77 · inbound

Graphs Don't Stay Secret: Practical Subgraph Reconstruction Attacks on Defended Graph RAG cites this paper.

Graphs Don't Stay Secret: Practical Subgraph Reconstruction Attacks on Defended Graph RAG Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 19

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unresolved
no resolver link, observed 2026-08-03T03:57:25.970105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T03:57:25.970105Z digest=sha256:a97237e3aeffb970ebedf7fce50e14de3c9789df9eeb5557fca1aa33b047b94b

Observation d3350705-3ade-4ec1-b090-f1276c00d835 · inbound

Benchmarking Knowledge-Extraction Attack and Defense on Retrieval-Augmented Generation cites this paper.

Benchmarking Knowledge-Extraction Attack and Defense on Retrieval-Augmented Generation Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 24

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unresolved
no resolver link, observed 2026-08-03T03:04:47.741689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T03:04:47.741689Z digest=sha256:810fa2d3af289c6277906fb171e374d8e7ca41c66e7b42bb65d7bec61ec212be

Observation 67262dd0-507d-4192-997a-6d5629c37434 · inbound

AgentWorm: Self-Propagating Attacks Across LLM Agent Ecosystems cites this paper.

AgentWorm: Self-Propagating Attacks Across LLM Agent Ecosystems Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 18

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unresolved
no resolver link, observed 2026-08-02T18:10:37.685799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T18:10:37.685799Z digest=sha256:23e37b9b82608a7f24cc8595ba74fe47fe53e2c3ce2d310c6a728f5b1ad2e3cd

Observation bdbb2baf-7a45-42d7-b3f5-cc58cf41e593 · inbound

Hierarchical Long-Term Semantic Memory for LinkedIn's Hiring Agent cites this paper.

Hierarchical Long-Term Semantic Memory for LinkedIn's Hiring Agent Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 9

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verified exact
arxiv_id, observed 2026-05-12T08:56:24.858380Z

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=2026-05-07T13:32:24.889097Z digest=sha256:41dab2cb7f9fd452466e406306d00933e84f4396e45952f3bf46ba6710d93af6

Observation b50336a9-7d84-4bce-a255-3e431021084f · inbound

Hierarchical Long-Term Semantic Memory for LinkedIn's Hiring Agent cites this paper.

Hierarchical Long-Term Semantic Memory for LinkedIn's Hiring Agent Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-07-01T09:25:40.508077Z

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=2026-07-01T09:07:57.475223Z digest=sha256:4223c2078886cd55d088d123cad3c7b5adb5cc487355c7256ff0fcb47989577e

Observation a5520cb9-1785-4ed9-9962-384057efdc58 · inbound

ShadowMerge: A Novel Poisoning Attack on Graph-Based Agent Memory via Relation-Channel Conflicts cites this paper.

ShadowMerge: A Novel Poisoning Attack on Graph-Based Agent Memory via Relation-Channel Conflicts Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 56

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:37:05.532516Z

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=2026-05-12T02:27:03.154390Z digest=sha256:7c21badb3f459fe1274c67280b687c5ac74f21a68849a69235d677f7b8d830ad

Observation 52577fce-3aff-4308-a3d7-ff1b6955e3ce · inbound

ShadowMerge: A Novel Poisoning Attack on Graph-Based Agent Memory via Relation-Channel Conflicts cites this paper.

ShadowMerge: A Novel Poisoning Attack on Graph-Based Agent Memory via Relation-Channel Conflicts Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 55

Resolution
verified exact
arxiv_id, observed 2026-05-15T06:09:49.291163Z

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=2026-05-15T06:09:36.338641Z digest=sha256:d0c2aab305c9e71a36b001f7189933df990264a03774f6b2cff08a52c302042f

Observation 21a3d6ef-803c-43b5-b4e3-a5600a753df5 · inbound

ShadowMerge: A Novel Poisoning Attack on Graph-Based Agent Memory via Relation-Channel Conflicts cites this paper.

ShadowMerge: A Novel Poisoning Attack on Graph-Based Agent Memory via Relation-Channel Conflicts Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 54

Resolution
metadata mismatch
arxiv_id, observed 2026-05-19T17:42:42.387294Z

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=2026-05-19T17:38:45.919637Z digest=sha256:e370733b971c59dab57e082660ff06e5d398981cca8138265b629191a7f24e75

Observation 245ef95d-fe71-4811-a21d-82b214918a0b · inbound

Knowledge Poisoning Attacks on Medical Multi-Modal Retrieval-Augmented Generation cites this paper.

Knowledge Poisoning Attacks on Medical Multi-Modal Retrieval-Augmented Generation Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 61

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verified exact
arxiv_id, observed 2026-05-12T05:31:23.624767Z

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=2026-05-12T05:29:41.946357Z digest=sha256:39254b3095161fc2d8cebf93b3a36f4a68e8bd0a523e0c5b4c6ea8042dd3aa51

Observation 468e04db-fe73-42d4-9a72-5f6d6d4e3c7a · inbound

ALDEN: Boosting Private Data Extraction from Retrieval-Augmented Generation Systems via Active Learning and Distribution Estimation cites this paper.

ALDEN: Boosting Private Data Extraction from Retrieval-Augmented Generation Systems via Active Learning and Distribution Estimation Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 13

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verified exact
arxiv_id, observed 2026-05-21T10:04:58.941670Z

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=2026-05-21T10:04:45.173272Z digest=sha256:a7fd43a3f5dc51a9efe846aba0d2b25e6095ce129afec010cbdc7010b8913695

Observation 6e069097-43cb-426b-9567-b3c0e59a4a47 · inbound

Agents That Know Too Much: A Data-Centric Survey of Privacy in LLM Agents cites this paper.

Agents That Know Too Much: A Data-Centric Survey of Privacy in LLM Agents Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-07-04T14:09:53.300284Z

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=2026-06-26T04:29:16.386339Z digest=sha256:58299a5984133d00d4af0f0b22033f7af2deaca1920150a05c4d06ad51fbf633

Observation dc13bef8-f132-494f-9f70-d3217d8d8464 · inbound

Isolated but Exposed: Persistence-Based Memory Extraction Attack on LLM Agents cites this paper.

Isolated but Exposed: Persistence-Based Memory Extraction Attack on LLM Agents Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 9

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unresolved
no resolver link, observed 2026-07-30T22:03:09.878034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T22:03:09.878034Z digest=sha256:5f6921fbe163a81f8c217eff324b6123fe2f224cdbabbdf135fe3858a42eb969

Observation df16059e-f23d-4528-88ee-1db3a74d2e76 · inbound

Mind the Hook: Source-Level Auditing of Privacy Defenses in Retrieval-Augmented Generation cites this paper.

Mind the Hook: Source-Level Auditing of Privacy Defenses in Retrieval-Augmented Generation Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 4

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unresolved
no resolver link, observed 2026-08-14T04:23:42.190859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:23:42.190859Z digest=sha256:746d5e90126381d472af89ca0a48f5bac8d6b7c4cc3df1081b0cfab60de2cea2

Observation e7dee2d1-2b81-467e-91ed-c234a269f472 · inbound

Privacy-Preserving RAG by Concealing Sensitive Information from External LLMs cites this paper.

Privacy-Preserving RAG by Concealing Sensitive Information from External LLMs Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 17

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unresolved
no resolver link, observed 2026-08-16T04:52:12.393002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:52:12.393002Z digest=sha256:f38dd9173fe2e70c5afa08d920e91f01cfd22a940adb6cdf63b32b80e5c5a113