Pith. sign in

Paper Citation Record · LEDGER

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

As of 10 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 2026-08-10T06:31:04.303077+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

Resolution
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:e6528b7380913a46f0127a952249bae23dab783be122705009c784417b85383a

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:48:56.187227Z digest=sha256:2bd64baf6691c5e66df4c0cdf1adda0014309ad4cc87b94fbcdada504a915a73

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:48:56.277376Z digest=sha256:0dfa292066718000f996a664cc1fe51e4b9d485eee7928b6c880deef04c35167

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:48:56.362806Z digest=sha256:7ceab4fc17bab920f336001f927ed7fbaaf57bf65c0db07424d6cc3f230fb0e4

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:48:56.481652Z digest=sha256:b591c545fc69e921132e5e8847db495c7c5ff4ae9127a66c6c57842d9d8cb38d

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
unresolved
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=sha256:3d40e0c915b210003e81f9a39334544fdad5f24cc537fca131b4cfaf3e59c119

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:48:56.746555Z digest=sha256:0fbc69b5a8465f38788290783e1b0a2dcb512ab1deac6a8cbf2f88ec68cf7b17

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:48:56.864144Z digest=sha256:ec4540cdf6f4c46bc09d7e0c8a83006b997fb07d188beddea34f98f5fbf17cc3

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:48:56.967589Z digest=sha256:ff9d86ecc9337a0f9fd17efe2627429c611e23f48e58171ff690d1fc3dff77a4

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

Resolution
unresolved
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=sha256:349692e33a884cdf21809cbd648f1a8f65119aeea49c8e16627d89ffdfd9bdf1

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=sha256:533a05ed6198e05dadf65c6cd6e3a2f45c1839e1946cc052fa49743269027813

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=sha256:1120ff2d767477bbaf4177b7bf3ab27370603c8867ffbbb058ef599588e0c341

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=sha256:81f7907194b9df13dd5ef289c287ce9ff8baf1d80fd74bd8928fe75156f3d0fe

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:48:57.685054Z digest=sha256:8c1c6b8b895ef2a425468a55e957fe3b70e42c79bf404b72c8efb1c347217afe

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=sha256:9c883c4c8fb8538f3729cc29e35fa8051935d2afa962c6fc4ad533e085ba60ea

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

Resolution
unresolved
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:dc85943ccfcbcdb7723941e015529028ebc1e8a7c204010b954aa5071125c283

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
unresolved
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=sha256:764d3722e9963b365baa79aa94c35083623b10b319ec73a4c4a73437bfb0be0c

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=sha256:8eea546adfc6cbf7057c49bef3fde6df81d9a64d93edbd0e639639b6237064d8

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:f12cb0bbd813916cb75784bc440746ba5debada16796334058d94df2e15b02b8

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=sha256:9de8bb54a34a26be4e1b6df5f2556578b984fe00949faf1994f5993d354e38a2

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=sha256:311cd1158deef96809c384f9557e35a8122625c0cb56da327085ae90dd914426

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=sha256:8d5d5362e61b73bd96d3466d10dc03c7bf801aad521c282a21cbae8541927498

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:48:58.906697Z digest=sha256:73370849bce2a5972b45ed90a7452e1cfabeda726b4f38778609a84b614aadc1

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:48:59.050059Z digest=sha256:0a294b8183cf43edf4fdff314075eb89f68c5edfdf9816843acc30a158470e26

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=sha256:7baa9a3db719d84699f0ba48c32e079447fe16ffcba53885e7092e3bce853f5c

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=sha256:067bb8e22acb06a6f81e8dd2ebaf5b022731b2b3c73f7c38e54b468a3bc05db4

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:48:59.697092Z digest=sha256:ebba9387581dcc329effec5a1284f82428c615564498884c6fb13e3792371e73

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:48:59.802354Z digest=sha256:2e2084b9d9a6eccef8c8c995f177fe75f3cfad35340954d9dcd92c6842b6cf4e

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=sha256:82f29af235d1b55ad49eebab224891f1d7a0b273dc98ed6ea0c698284abed89a

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

Resolution
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:c0be590a89bc3c06f1deca6c3c98850133d623faaa345db04398776f0cd416a7

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

Resolution
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=sha256:7a77e650a05dc93cbd72347a6260031a09369ee3bba7a37b1b351713c7303e4d

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

Resolution
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=sha256:46ea0ad49c612515b60f6a47f7c7d5d1f43ee552339516116a7bff03080b97a3

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:49:00.485686Z digest=sha256:c78dab4e71f7c9702793e56bacfae304729553204ee90b11e384e1b7c2938bfa

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:49:00.641358Z digest=sha256:6add123938a31dfaecd1bf0c62ca0c57ef8189c77f51c609586f0bb32193ca42

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T15:49:00.970194Z digest=sha256:9e95ddca88f51746936e2948f5555f7be8fee1397f191e690d0bcfa644c24859

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=sha256:5b10f53952c4d301abe902ea5cab64a8db771241eb4f2568cedfca7acecd5ba7

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=sha256:4220534b581df32ad6790d3e7169bdd26e395d386d3510f78f921576fd3e89e7

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=sha256:11a6bbee550a2cedd3ce85b1723716525151e079b3e5329a395ebeb99089fd72

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-27T00:29:09.121399Z digest=sha256:398bbba18f74d638cdae932a5266363add5f44d024170f881c4d9f67cd056679

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-25T20:56:20.603088Z digest=sha256:4093c4cd8b74786d783160867ba37f9a3fdcb91836bf4963e8bdc3063e25030e