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Paper Citation Record · LEDGER

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection

As of 7 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 3 inbound Pith citation observations for arXiv:2507.15042.

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

pith.paper-citation-record.v1
2507.15042 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:49:00.970194Z

measured 40 of 40 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T10:44:10.601057Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T20:00:07.849622Z

Reference resolution

37 of 37 outbound references displayed

  • verified exact2
  • verified fuzzy12
  • unresolved23
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5d655d0d-c75d-4cc5-b2dd-dd1bc81bc65a · outbound

This paper cites MS MARCO: A Human Generated MAchine Reading COmprehension Dataset.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection MS MARCO: A Human Generated MAchine Reading COmprehension Dataset

Reference 1

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unresolved
no resolver link, observed 2026-08-06T15:48:56.106561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:48:56.106561Z digest=sha256:b85720a541ef486f3b632937df0413cda3f11a71c9015e54832cd2dcecadb189

Observation 3a9a8c58-d999-40b8-be0d-4ac180811128 · outbound

This paper cites WWW’18 open challenge: Financial opinion mining and question answering.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection WWW’18 open challenge: Financial opinion mining and question answering

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:49:05.144970Z

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=2026-08-06T15:48:56.187227Z digest=sha256:81269f9abdca3c139574176b41828373baf6b4d4a0fbad742163d453ceeddec5

Observation a91a3ef5-86b5-4d5b-9afe-b04dcb38cc9e · outbound

This paper cites Fact or Fiction: Verifying Scientific Claims.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Fact or Fiction: Verifying Scientific Claims

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:49:04.846766Z

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=2026-08-06T15:48:56.277376Z digest=sha256:c93a4cda4456b568e92644011237a7c8538aa9f79c7927d7cfbdea82bcb06169

Observation 8183669c-5363-4780-acc4-f8cdfcc1192f · outbound

This paper cites FEVER: A large-scale dataset for fact extraction and VERification.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection FEVER: A large-scale dataset for fact extraction and VERification

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:49:04.619938Z

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=2026-08-06T15:48:56.362806Z digest=sha256:eed5fb00666cf76f265104cc90103989eafd50f5e88a27b902ccddf8d9e9712c

Observation 3bdc3bb4-e328-447f-a096-83ebf39b5f17 · outbound

This paper cites SQuAD: 100,000+ questions for machine comprehension of text.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection SQuAD: 100,000+ questions for machine comprehension of text

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:49:04.341382Z

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=2026-08-06T15:48:56.481652Z digest=sha256:e049b7b1bd6c8d25d41fef282ca82792c5c4c7aa312241dfaa10d3293d64fce9

Observation 32d60f6b-c450-4e6f-ae73-fa52e357ab80 · outbound

This paper cites BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models

Reference 6

Resolution
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no resolver link, observed 2026-08-06T15:48:56.617124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:48:56.617124Z digest=sha256:7ed740af3d135420515db64499f6485a25f1ec14b4b69f52fe4ee2e19c3264ed

Observation d9847514-dc4c-424c-a875-2971cb3b76eb · outbound

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

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:49:04.046023Z

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=2026-08-06T15:48:56.746555Z digest=sha256:cf0a4d1897383a81066f930119a5c6b731dbcafcd86610d1b45f3b769f75b8eb

Observation 92af87fd-150b-4984-8085-12ff84a97ae4 · outbound

This paper cites Differential evolution – a simple and efficient heuristic for global optimization over continuous spaces.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Differential evolution – a simple and efficient heuristic for global optimization over continuous spaces

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:49:03.810414Z

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=2026-08-06T15:48:56.864144Z digest=sha256:45e21c08ef793aee63d1a3333287e006687c36ef6625aee9a1fad8ee4e2809ea

Observation f6818379-ce7c-496d-b0e3-c8dd9fa3f5a5 · outbound

This paper cites Salem, and Ahmed E.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Salem, and Ahmed E

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:49:03.555565Z

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=2026-08-06T15:48:56.967589Z digest=sha256:34c8d5726dfb4e5d2e4d47b8dbab111e0a60b14fee2ccedf20d4594c81c221df

Observation a359d608-5344-4049-ac7d-a401460176e9 · outbound

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

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases

Reference 10

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no resolver link, observed 2026-08-06T15:48:57.081874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:48:57.081874Z digest=sha256:a1b06f0aa93eb37e749b5ebb528d2a556f55169190b19a17ed04d00870d6f1a8

Observation 630c11ab-c934-4e03-8fb2-5715dda31ee6 · outbound

This paper cites Targeting the Core: A Simple and Effective Method to Attack RAG-based Agents via Direct LLM Manipulation.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Targeting the Core: A Simple and Effective Method to Attack RAG-based Agents via Direct LLM Manipulation

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T15:48:57.225641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:48:57.225641Z digest=sha256:7a11e5f03acf38991a8de8ec108c55640171f981376b030cb818ba207a1da50e

Observation ea27f41a-2e62-4e1a-8a1a-c919c5fc8c86 · outbound

This paper cites BadRAG: Identifying Vulnerabilities in Retrieval Augmented Generation of Large Language Models.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection BadRAG: Identifying Vulnerabilities in Retrieval Augmented Generation of Large Language Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T15:48:57.340757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:48:57.340757Z digest=sha256:e2f148a6db7ae2b59d7f7f743ae2c50aaf8e302a8dc0a7a7d174a3afddc5eca0

Observation bcc68161-d6d3-4a8e-9e44-af07f4c51e9f · outbound

This paper cites Detecting Language Model Attacks with Perplexity.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Detecting Language Model Attacks with Perplexity

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T15:48:57.497059Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:48:57.497059Z digest=sha256:40130843d2ed90f3e26ec89ac38c85c527e95362addc5115d24a7cb34bffa696

Observation 55540e38-55c3-47d6-af28-bcc07804aa99 · outbound

This paper cites Robust Safety Classifier Against Jailbreaking Attacks: Adversarial Prompt Shield.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Robust Safety Classifier Against Jailbreaking Attacks: Adversarial Prompt Shield

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:49:03.327394Z

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=2026-08-06T15:48:57.685054Z digest=sha256:06bacc75ca1877437457c5147573fc0b6437ad1ed54596232dae20f1d9acd7c2

Observation 7e39d900-ffb7-4ff9-9304-3e2b534f6d06 · outbound

This paper cites CtrlRAG: Black-box Adversarial Attacks Based on Masked Lan- guage Models in Retrieval-Augmented Language Generation.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection CtrlRAG: Black-box Adversarial Attacks Based on Masked Lan- guage Models in Retrieval-Augmented Language Generation

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T15:48:57.797958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:48:57.797958Z digest=sha256:490ef16670c81899aea08ad50069fdf5201f88c26126e0e21d9c18406c797f68

Observation 283a017a-c98d-43e1-a8de-d9ec0d9e2f31 · outbound

This paper cites PRADA: Practical Black-box Adversarial Attacks against Neural Ranking Models.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection PRADA: Practical Black-box Adversarial Attacks against Neural Ranking Models

Reference 16

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no resolver link, observed 2026-08-06T15:48:57.903143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:48:57.903143Z digest=sha256:c4f976a2bc779102b46260d6c541badaf4cafcc6bf60ffa22dcb5799d1f96513

Observation 5e2d89c9-d531-433b-b9e0-93a1b4e3b595 · outbound

This paper cites One Pixel Attack for Fooling Deep Neural Networks.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection One Pixel Attack for Fooling Deep Neural Networks

Reference 17

Resolution
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no resolver link, observed 2026-08-06T15:48:58.038712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:48:58.038712Z digest=sha256:00ea71efcaeb88bcc338e504c21f78a74637955c0055f3b0d0915a12f387de37

Observation 75787886-0a10-4a7e-81a2-6873fad46b03 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T15:48:58.165779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:48:58.165779Z digest=sha256:651e01690f04e7516a33d98b8577d5fd1beffcd1db9ba89e1c3807110e74b0c1

Observation 57954197-763d-49be-905e-01ddf0c74363 · outbound

This paper cites Ignore Previous Prompt: Attack Techniques For Language Models.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Ignore Previous Prompt: Attack Techniques For Language Models

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T15:48:58.294900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:48:58.294900Z digest=sha256:e09c65fa5b09bb0e1abee774b7f9268c1570bc146591213214e0c836de0ade1c

Observation e7e68571-f96e-4f65-ada3-7426759e29b2 · outbound

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

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Automatic and Universal Prompt Injection Attacks against Large Language Models

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-06T15:48:58.472087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:48:58.472087Z digest=sha256:a721e535a775ed9de1175b79491305ef90c05e19207a464ce896431fd1695010

Observation 91050d90-8900-4fe2-a68c-2446cd62a221 · outbound

This paper cites Goal-guided Generative Prompt Injection Attack on Large Language Models.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Goal-guided Generative Prompt Injection Attack on Large Language Models

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-06T15:48:58.642580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:48:58.642580Z digest=sha256:3a96d44b73dbd342cbc8362bbe40fbcb861a02269564a6072b5a01648f70db24

Observation bd98d08a-721e-473e-af78-e6286c03d56b · outbound

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

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Jailbreaking Black Box Large Language Models in Twenty Queries

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-06T15:48:58.758345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:48:58.758345Z digest=sha256:0be9293803dfb8327e1ae8d4c77de8ddcae3a6c1341c929be3a8d1439017fe1c

Observation 9014105d-ea42-4b63-9c8d-5165e2519b28 · outbound

This paper cites Prompt Perturbation in Retrieval-Augmented Generation based Large Language Models.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Prompt Perturbation in Retrieval-Augmented Generation based Large Language Models

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-08-06T15:49:01.623652Z

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=2026-08-06T15:48:58.906697Z digest=sha256:7a0b2fda34c5d771f88a7eea7ace6c39b5b2e75426c4a102c75bb91059b673fb

Observation 5176bed5-3ecb-4986-945d-bf5989dd8968 · outbound

This paper cites TEMPEST: Multi-Turn Jailbreaking of Large Language Models with Tree Search.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection TEMPEST: Multi-Turn Jailbreaking of Large Language Models with Tree Search

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:49:03.044417Z

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=2026-08-06T15:48:59.050059Z digest=sha256:ea144936f2c7498c7452a41fa21e669539aa96d933d4b8d7925eaf2815d78e13

Observation 1a961bf6-c059-4e95-a1b3-03cbde47ff4e · outbound

This paper cites Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-06T15:48:59.178419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:48:59.178419Z digest=sha256:f4f6606e0dbe6b506305f92190c35adf4ad02ef41b2d607c98c5996b6bf66fce

Observation 2dd1cd2d-204b-4f1a-858e-be4a3f7284bf · outbound

This paper cites Release Strategies and the Social Impacts of Language Models.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Release Strategies and the Social Impacts of Language Models

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-06T15:48:59.296515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:48:59.296515Z digest=sha256:8ca0fa31b0c0cfa3def8b99b03a8098bc61f67aade19b700ce9603fbf4cd4538

Observation 31d56b97-da33-4b56-9e70-1cad8fd199f8 · outbound

This paper cites Black-box Adversarial Sample Generation Based on Differential Evolution.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Black-box Adversarial Sample Generation Based on Differential Evolution

Reference 28

Resolution
verified exact
local_arxiv, observed 2026-08-06T15:49:01.309111Z

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=2026-08-06T15:48:59.697092Z digest=sha256:6fa488b6095ca9c6bd12dd1a184e014a06c7ed446d67e37cee105cbec92ed71d

Observation 80dc2c97-6a6f-4fea-a748-0319b4caf0bc · outbound

This paper cites Black-Box Prompt Learning for Pre-trained Language Models.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Black-Box Prompt Learning for Pre-trained Language Models

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:49:02.776909Z

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=2026-08-06T15:48:59.802354Z digest=sha256:c40d938885386004d8144fd1d80be8300b9a73dfef196c644139076a13f72d56

Observation 7cd9529c-51c7-47a5-a0f0-311c75fa2bac · outbound

This paper cites Generative Representational Instruction Tuning.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Generative Representational Instruction Tuning

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-06T15:48:59.910252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:48:59.910252Z digest=sha256:8394401bccde9958ee91123a9b3502d43ef8956ec1487f7eda5ba121a495b215

Observation 84bbaabe-9546-4bca-8463-bf6be57a6fd4 · outbound

This paper cites Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models

Reference 31

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unresolved
no resolver link, observed 2026-08-06T15:49:00.035067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:49:00.035067Z digest=sha256:dc1679d2ab88ca89f691cbdb81773b950a5b21a487becaed81086c585bb99275

Observation fbc1b277-a695-4a6e-8905-ad112feabcc2 · outbound

This paper cites Token-Level Adversarial Prompt Detection Based on Perplexity Measures and Contextual Information.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Token-Level Adversarial Prompt Detection Based on Perplexity Measures and Contextual Information

Reference 32

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unresolved
no resolver link, observed 2026-08-06T15:49:00.202243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:49:00.202243Z digest=sha256:6fbb355a5e0982c83c1c3984c3584988b65856239f45c10925d49e0e53ef1e30

Observation ba24aec9-af6d-43cc-addf-a10ad5a86257 · outbound

This paper cites an unresolved cited work.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Unresolved cited work

Reference 33

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unresolved
no resolver link, observed 2026-08-06T15:49:00.374240Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:49:00.374240Z digest=sha256:baf1630453acdce513f15321eae5232e57a04bca59c635043b2dc66705a5d221

Observation 2d87080b-84f7-4314-b8b6-392c0126f2ca · outbound

This paper cites an unresolved cited work.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Unresolved cited work

Reference 34

Resolution
unresolved
raw_fallback, observed 2026-08-06T15:49:02.507055Z

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=2026-08-06T15:49:00.485686Z digest=sha256:d6d8337d78d33f222ec9207467087db8db7a97f4e8dc9f454c1061519e44d27d

Observation 08737cbd-b2c2-4bd1-89eb-03e6da87eac7 · outbound

This paper cites The Probabilistic Relevance Framework: BM25 and Beyond.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection The Probabilistic Relevance Framework: BM25 and Beyond

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:49:02.322604Z

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=2026-08-06T15:49:00.641358Z digest=sha256:bd5cccc0ae1593634c7cd71bb88757352333d9e38b772f36f6340ea83bf156cc

Observation fc70a480-734b-4b62-a382-fd83cec2d94f · outbound

This paper cites Download to CSV.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Download to CSV

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:49:02.064640Z

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=2026-08-06T15:49:00.970194Z digest=sha256:6768052411696d2dbfdec2f64d446c627c0670fb1291ba9e0f9e51a92f91b8a5

Observation 6d6ba860-845d-409d-b954-ada883c11048 · outbound

This paper cites an unresolved cited work.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Unresolved cited work

Reference 2009

Resolution
unresolved
no resolver link, observed 2026-08-06T15:49:00.794927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:49:00.794927Z digest=sha256:3ca932f41990588b38810dffb091c6a917a07f37c8d1d7c32b8841ab3e174364

Observation 3fb4155e-17e1-42f1-a4aa-c79b8b5123de · outbound

This paper cites EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizers.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizers

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-06T15:48:59.538886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:48:59.538886Z digest=sha256:6e67a9f3e5cb3addc91d7e8471586776416333f281b39f1af7c6da0e1b517bc6

Pith citing papers

Observation 349d7963-e035-454b-a5f8-dcefb9cfe494 · inbound

Evaluating the Robustness of Retrieval-Augmented Generation to Adversarial Evidence in the Health Domain cites this paper.

Evaluating the Robustness of Retrieval-Augmented Generation to Adversarial Evidence in the Health Domain DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-05T10:44:10.601057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:44:10.601057Z digest=sha256:87837b72a8b523418df4b41b3448d840a98fdc89dba9f61481e3697b7aacfb19

Observation 2a5047a3-ee61-4305-8648-5807f6b954a8 · inbound

Conflict-Aware Retriever Editing for Knowledge Injection Attacks on LLM-Based RAG Systems cites this paper.

Conflict-Aware Retriever Editing for Knowledge Injection Attacks on LLM-Based RAG Systems DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-07-03T21:28:59.112223Z

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=2026-06-27T00:29:09.121399Z digest=sha256:0ffbf78b9a9fe347080ccd1e6021c1c5e223b620514a8d094ae70391950f9e7b

Observation a06c6220-4bae-4214-864c-7ec085aefb4f · inbound

Security and Privacy in Retrieval-Augmented Generation: Architectures, Threats, Defenses, and Future Directions for Building Trustworthy Systems cites this paper.

Security and Privacy in Retrieval-Augmented Generation: Architectures, Threats, Defenses, and Future Directions for Building Trustworthy Systems DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection

Reference 60

Resolution
verified exact
arxiv_id, observed 2026-07-04T20:00:07.851452Z

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=2026-06-25T20:56:20.603088Z digest=sha256:52108a1bb2754cda053bb71b845106a3e58a2f7a65e088e7ac1717a0edaa4474