Pith. sign in

Paper Citation Record · LEDGER

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation

As of 8 August 2026, this Paper Citation Record lists 99 of 99 outbound references and 9 inbound Pith citation observations for arXiv:2505.18543.

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

pith.paper-citation-record.v1
2505.18543 v1

Coverage vector

measured 99 of 99 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:33:01.360877Z

measured 108 of 108 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 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:18:36.938530Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

99 of 99 outbound references displayed

  • verified exact2
  • verified fuzzy12
  • unresolved85
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation eb515526-36eb-4ddb-ac1d-6403d158fcc6 · outbound

This paper cites https://www.anthropic.com/news/claude-3-7-sonnet.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation https://www.anthropic.com/news/claude-3-7-sonnet

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:54.584518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:54.584518Z digest=sha256:c24228d5d8647e1390c11c48b4f24f0e8af17f4b6b70d207c560756bee408b07

Observation ae8db373-cc3f-40cb-a7de-59a73978ca30 · outbound

This paper cites https://blog.google/ technology/google-deepmind/google-gemini-ai-update-december-2024.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation https://blog.google/ technology/google-deepmind/google-gemini-ai-update-december-2024

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:54.611951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:54.611951Z digest=sha256:bec25627fb106483ed3b971338309b3378211a72c8d34ce4395761b16c0b0308

Observation 0857b61f-942c-4c97-bef6-67570aa588ab · outbound

This paper cites https://openai.com/index/gpt-4-1.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation https://openai.com/index/gpt-4-1

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:54.633958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:54.633958Z digest=sha256:366e624be0e5b7e803703d880c779970d257426673bf7090aa2cddbb53e17860

Observation 643ff895-629f-499f-ac38-a81905bcf1a5 · outbound

This paper cites https://modelcontextprotocol.io/ introduction.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation https://modelcontextprotocol.io/ introduction

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:54.681873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:54.681873Z digest=sha256:84a6fdf7a4cf12145c2ff89880ed85f543a0f093a186ff9fa70904080228fb60

Observation 58c03155-f4a8-40ac-9815-68c44326f6db · outbound

This paper cites https://www.llama.com/models/llama-4.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation https://www.llama.com/models/llama-4

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:54.740720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:54.740720Z digest=sha256:22e7fae32586be94bb76c46331f76e08af41216081d4c8b98c86c652c33ba2af

Observation 6e4f394b-0e7b-49e4-93df-4e9fc216083a · outbound

This paper cites an unresolved cited work.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Unresolved cited work

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:54.758341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:54.758341Z digest=sha256:c92a3ae4690879e7d6f60c0c5194d6b6853551c1c3a72fc27669df8b76588cb8

Observation 7023bea6-c370-4cc5-a31c-916988a544f6 · outbound

This paper cites GPT-4 Technical Report.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation GPT-4 Technical Report

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:54.807646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:54.807646Z digest=sha256:cd278839df7ccc8ce8c5e7725f35b3193d02e3d3e1e97ad723a97864a21182e4

Observation 64299fff-671c-49d4-aaf4-19f231b63137 · outbound

This paper cites Trec ikat 2023: A test collection for evaluating conversational and interactive knowledge assistants.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Trec ikat 2023: A test collection for evaluating conversational and interactive knowledge assistants

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:54.846051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:54.846051Z digest=sha256:c7b61e82b91b4dfbbd1947ab7b9b55ec412fa50d7f2456fafe3747cf392099ba

Observation aba5cffd-0f26-43ef-92b9-ea45c14f564c · outbound

This paper cites PaLM 2 Technical Report.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation PaLM 2 Technical Report

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:54.871001Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:54.871001Z digest=sha256:12e5c3fab47612e1145f591d82f112351073f19016111a76643219114b7e1a40

Observation c43278b2-fc8d-4757-b363-d31da86312d4 · outbound

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

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Improving language models by retrieving from trillions of tokens

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:54.920453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:54.920453Z digest=sha256:6d45c16243ba48e3dff1965c0c3096a24c61a01c3f7df65e6a18b2e6868da955

Observation 23918784-0ac5-4ee5-b537-342b8cfdf8ea · outbound

This paper cites Language models are few-shot learners.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Language models are few-shot learners

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:55.070616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:55.070616Z digest=sha256:a8a222d8933ee646435d113ad2e5b7094a6f1ea2d288f5d71e7c1c374899ac67

Observation 38dc0dc6-1b9b-4457-8321-342623c23181 · outbound

This paper cites Poisoning web-scale training datasets is practical.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Poisoning web-scale training datasets is practical

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:55.208722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:55.208722Z digest=sha256:3481d15c186a4aa5f57c4d0e8761e3920045de66ed83032a1df4b561a72b7420

Observation fa32781c-72a6-42de-83ed-2a3ed211942f · outbound

This paper cites RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generation.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generation

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:55.354259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:55.354259Z digest=sha256:d4ca6f049ab7a167fa1470f0c087de171c994f4f6558c6d7a121a9255acd8e7e

Observation 64cfae5a-c39a-413e-966f-63f4d9274ef6 · outbound

This paper cites One Shot Dominance: Knowledge Poisoning Attack on Retrieval-Augmented Generation Systems.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation One Shot Dominance: Knowledge Poisoning Attack on Retrieval-Augmented Generation Systems

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:55.442214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:55.442214Z digest=sha256:397d1e71425b46a2c5a4626654d01659cfebe9fc118e77f075c889c78d37a599

Observation 4c67b0c5-ddc2-4d7f-acf8-be75083c4300 · outbound

This paper cites Phantom: General trigger attacks on retrieval augmented language generation.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Phantom: General trigger attacks on retrieval augmented language generation

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:55.545101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:55.545101Z digest=sha256:2cf665b4d31120d05681679aae3be69fcd93e05b56db3a3002db54ee98b4a4a9

Observation 50c12053-cd4b-4c95-ba21-572ceb7fb9e2 · outbound

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

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Benchmarking large language mod- els in retrieval-augmented generation

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:55.637930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:55.637930Z digest=sha256:307ac99856366326180d32452c0a941be4d9bde6bd9dabd1419286b660fbe1b4

Observation cc5f52d0-1f83-43f5-b11b-3be84cc33e1f · outbound

This paper cites MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:55.658464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:55.658464Z digest=sha256:bd7eb8fc21e01fafee29b5c7cec75f9d83ca9704eadf667d45783380678e1b4b

Observation c1780cfb-b22e-4278-807b-4b7dcdd9248a · outbound

This paper cites Can Pre-trained Vision and Language Models Answer Visual Information-Seeking Questions?.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Can Pre-trained Vision and Language Models Answer Visual Information-Seeking Questions?

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:55.697518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:55.697518Z digest=sha256:ed8b7f3aff3417d5de32cf6143afb738ec64ce27262e8e235644e805726be902

Observation cd8320f5-4d1a-443a-9a54-047f25fc888a · outbound

This paper cites Agentpoison: Red-teaming llm agents via poisoning memory or knowledge bases.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Agentpoison: Red-teaming llm agents via poisoning memory or knowledge bases

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:55.773914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:55.773914Z digest=sha256:de7f6c762dfccdb2ddb2333dca23c04e7beec0641f0555bdb23678c2ba660a6b

Observation d4bf530a-d7be-4bf1-8238-a5dbb768c4b2 · outbound

This paper cites Flipedrag: Black-box opinion manipulation attacks to retrieval- augmented generation of large language models.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Flipedrag: Black-box opinion manipulation attacks to retrieval- augmented generation of large language models

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:55.887118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:55.887118Z digest=sha256:fb394a3d129602d093e55215b49441f229b3ef9a19651623be53b54e98ccc4aa

Observation c6a40ba3-7413-49b3-ba06-8121ceb5ab82 · outbound

This paper cites TrojanRAG: Retrieval-Augmented Generation Can Be Backdoor Driver in Large Language Models.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation TrojanRAG: Retrieval-Augmented Generation Can Be Backdoor Driver in Large Language Models

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:55.989945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:55.989945Z digest=sha256:a5bd62a16ab2f03b44c91a8cdeb635a719155b119f9bb3c87dbaf4dadbd1670d

Observation c2dcd335-ad68-4fca-a280-e63feeea52f7 · outbound

This paper cites CORAL: Benchmarking Multi-turn Conversational Retrieval-Augmentation Generation.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation CORAL: Benchmarking Multi-turn Conversational Retrieval-Augmentation Generation

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:56.150927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:56.150927Z digest=sha256:4675f45fc708489e25fd16bbb1216be9855757caf99122b1ef840ca64a6b560c

Observation 5e4051a2-0940-449c-bbcc-940cfc2150f4 · outbound

This paper cites Typos that Broke the RAG's Back: Genetic Attack on RAG Pipeline by Simulating Documents in the Wild via Low-level Perturbations.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Typos that Broke the RAG's Back: Genetic Attack on RAG Pipeline by Simulating Documents in the Wild via Low-level Perturbations

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:56.319699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:56.319699Z digest=sha256:72ae1fe5700aa9e351d06919728fd46380d5592c015079b411f8e9cff93b0dda

Observation af08a444-e465-442d-913d-d06fea622b93 · outbound

This paper cites The rag paradox: A black-box attack exploiting unintentional vulnerabilities in retrieval-augmented generation systems.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation The rag paradox: A black-box attack exploiting unintentional vulnerabilities in retrieval-augmented generation systems

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:56.452133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:56.452133Z digest=sha256:d5ba34681bb5471e121a63abb55e6e0766739247dce995b7b517b49a2d44a3cc

Observation 0cd633ec-05aa-4362-ab10-094ec0fb47af · outbound

This paper cites BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:56.493361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:56.493361Z digest=sha256:36d496256e54662c0a55fcfdedd78be4b1e79c3891e20e1796ffe44de548b5e7

Observation 2e4aeb03-d6d5-4a7a-92dc-0872acf117ef · outbound

This paper cites The power of noise: Redefining retrieval for rag systems.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation The power of noise: Redefining retrieval for rag systems

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:56.531007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:56.531007Z digest=sha256:ff141b5cb82031225639b213adf91006f22f8d923f09c31f4477386a1822f1bb

Observation 9d2fd507-02b2-4ea7-b9a0-48579515f91d · outbound

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

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:56.573813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:56.573813Z digest=sha256:5d8ade88d4e215862b7dfc4ed8d5294ab3befd2f281c55a7fcee9d4f6e5961d3

Observation 3a2643ec-c27c-4d98-971e-af52f1cc1db8 · outbound

This paper cites Did aristotle use a laptop? a question answering benchmark with implicit reasoning strategies.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Did aristotle use a laptop? a question answering benchmark with implicit reasoning strategies

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:56.680823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:56.680823Z digest=sha256:085d1bb9ea9e9563be1322f335e2c652da3dbf16924199a4da2292db66123bb5

Observation e8743175-d732-43ce-b914-a907cefe0218 · outbound

This paper cites Topic-fliprag: Topic-orientated adversarial opinion manipulation attacks to retrieval-augmented generation models.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Topic-fliprag: Topic-orientated adversarial opinion manipulation attacks to retrieval-augmented generation models

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:56.692225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:56.692225Z digest=sha256:55ab8680be69ed4f491198b945ce4dbb88f4139c9803503d35ae97100bceb059

Observation c0b00558-31dd-4191-a7ce-c8bbc7b5da10 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:56.696425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:56.696425Z digest=sha256:5fa55d50f5e968597fe9614b9fe87a638c126e474fe8af1b3930b30a8576e029

Observation da75b75a-9208-4cc9-a5a5-c2e6981ba25d · outbound

This paper cites GPT-4o System Card.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation GPT-4o System Card

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:56.786445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:56.786445Z digest=sha256:d554f5b6b1315ace9b2a679cd8b4c90f1ded196866371adcfb121e0ff4975059

Observation fbd9e164-e37c-4b57-956f-3305db231dda · outbound

This paper cites Unsupervised Dense Information Retrieval with Contrastive Learning.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Unsupervised Dense Information Retrieval with Contrastive Learning

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:56.815949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:56.815949Z digest=sha256:f6333deb3c4a2fda6cdd6425a25364129ab14b27dce00536d1ec720fd34eaf2f

Observation f16bfc5d-3549-4832-ab58-81d609ddc017 · outbound

This paper cites Baseline Defenses for Adversarial Attacks Against Aligned Language Models.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Baseline Defenses for Adversarial Attacks Against Aligned Language Models

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:56.855487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:56.855487Z digest=sha256:ad7d651dc21f36ec946528406f54839faf5ee6e0822f3c78a68b7d201840e380

Observation b5043607-4dc8-4f12-bf13-abc547788d41 · outbound

This paper cites Interpolated estimation of markov source parameters from sparse data.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Interpolated estimation of markov source parameters from sparse data

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:56.885628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:56.885628Z digest=sha256:6232483250e21fb0622de5b40de53bd900a303d29c5b3fca301c12c277bafbd1

Observation 00b2ce9f-8a68-46c1-9a83-0d7152b1a3bf · outbound

This paper cites Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:56.955402Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:56.955402Z digest=sha256:a2d6dce6bbaa872996111fe5087f0c1011b8553a8a2a8841daf101728b24f621

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

This paper cites Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications.

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

Reference 36

Resolution
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=sha256:997ff6ed4d64143e84cd00b713b773a184f821a778c51a0103432074ccfea4cc

Observation ce9e1479-6608-4898-b3ed-06f61f811288 · outbound

This paper cites Active Retrieval Augmented Generation.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Active Retrieval Augmented Generation

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:57.036232Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:57.036232Z digest=sha256:6295fd930352add8180fff6b0dd723bf44839e8397221b74d55d78078ea13ecf

Observation 78610109-bc3a-4a30-a63e-a61d16299297 · outbound

This paper cites PR-Attack: Coordinated Prompt-RAG Attacks on Retrieval-Augmented Generation in Large Language Models via Bilevel Optimization.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation PR-Attack: Coordinated Prompt-RAG Attacks on Retrieval-Augmented Generation in Large Language Models via Bilevel Optimization

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:57.110743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:57.110743Z digest=sha256:2b12911972abd730928511ec96d08b4bf557b9fdcbdb5a6afee4ed0959c5cd12

Observation e3930e9d-7551-46ad-b14b-e66ab494071f · outbound

This paper cites FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Research.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Research

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:57.144351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:57.144351Z digest=sha256:5f3365074f190daec878939666e87b6a421b28fffc6a2f70ff56e362d26c3314

Observation 759c364f-7a02-4b20-9ba5-983c77c6b480 · outbound

This paper cites Dense Passage Retrieval for Open-Domain Question Answering.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Dense Passage Retrieval for Open-Domain Question Answering

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:57.180310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:57.180310Z digest=sha256:bf1d53ffab6a3a0548a5c7b09f48a9f1537680e122394607ba3ab9894177341f

Observation b814be3e-e3fc-48e9-8bed-c17ed713b0eb · outbound

This paper cites MTRAG: A Multi-Turn Conversational Benchmark for Evaluating Retrieval-Augmented Generation Systems.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation MTRAG: A Multi-Turn Conversational Benchmark for Evaluating Retrieval-Augmented Generation Systems

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:57.233051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:57.233051Z digest=sha256:3632e8a59d2522b876e2b20129f11166daf8439f1f39ab81a567f15b85b28141

Observation 752c2593-87c5-4ba8-a28c-f27132dbc365 · outbound

This paper cites SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMs.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMs

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:57.295105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:57.295105Z digest=sha256:f317ca4291830a5ce8db75eda589a2b840bcf5859fd9bea98c4898dad880f467

Observation 3748f086-724c-41fd-a4f5-1bb7ec0b7c11 · outbound

This paper cites RAD-Bench: Evaluating Large Language Models Capabilities in Retrieval Augmented Dialogues.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation RAD-Bench: Evaluating Large Language Models Capabilities in Retrieval Augmented Dialogues

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:57.345015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:57.345015Z digest=sha256:f2a04928d61b3ac37d85f44a0c4999b2d7dac4336d7f34c0432e4b006b2d4624

Observation f386655e-c817-471e-9fe2-c9f55c3f2ae5 · outbound

This paper cites Natural questions: a benchmark for question answering research.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Natural questions: a benchmark for question answering research

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:57.398975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:57.398975Z digest=sha256:bec71b6478066df6b67941a5fe7582b5fb9253484cd2bc653a82572708c9456f

Observation 0edb92d7-7eee-4ece-8bd8-34a34f868674 · outbound

This paper cites AlzheimerRAG: Multimodal Retrieval Augmented Generation for Clinical Use Cases using PubMed articles.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation AlzheimerRAG: Multimodal Retrieval Augmented Generation for Clinical Use Cases using PubMed articles

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:57.426171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:57.426171Z digest=sha256:178cd906075715e046b43d6f6d803b8616566a0903841eaf53b9bbb6f8b7fd12

Observation 894c6faf-ea8b-46d8-b131-31dafac7bfc8 · outbound

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

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Retrieval-augmented generation for knowledge-intensive nlp tasks

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:57.461562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:57.461562Z digest=sha256:0d04cb75031335257e76c4daf0420c8f1ce7653889992677a232c28aba21b601

Observation 729a7a0f-0f24-42ec-a575-6b483fbbb14c · outbound

This paper cites Seeing is believing: Black-box member- ship inference attacks against retrieval augmented generation.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Seeing is believing: Black-box member- ship inference attacks against retrieval augmented generation

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:57.498679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:57.498679Z digest=sha256:366eb0c4f32cd85b84bb770dfbb6dda8cbf3fb6c24cdee08ff02d35b3830f67f

Observation 68520974-af71-4bd0-88a9-2bde47f4dfa4 · outbound

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

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation SafeRAG: Benchmarking Security in Retrieval-Augmented Generation of Large Language Model

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:57.580657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:57.580657Z digest=sha256:632c1c04b0304516defee0764ee51c3e0d8caa0e4cbc59ad525fd7356503bafb

Observation d958df5b-73a0-4c35-8156-ce0fa693c920 · outbound

This paper cites DeepSeek-V3 Technical Report.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation DeepSeek-V3 Technical Report

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:57.638696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:57.638696Z digest=sha256:ae9d4a8b70bcbbef9ba64d88c8d26c9ae996f743d910ce7664c08ed679b661ae

Observation a97f2a88-7634-424f-851f-340b3af38c68 · outbound

This paper cites Poisoned-MRAG: Knowledge Poisoning Attacks to Multimodal Retrieval Augmented Generation.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Poisoned-MRAG: Knowledge Poisoning Attacks to Multimodal Retrieval Augmented Generation

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:57.726747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:57.726747Z digest=sha256:3c561b9ac44f8d03f8e46e442d13b06af88454a7daf70744950e585ed5e496db

Observation 4a77545b-7d76-4a18-9cbe-493bd037948d · outbound

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

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Formalizing and benchmarking prompt injection attacks and defenses

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:57.761534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:57.761534Z digest=sha256:fe2104504db166500ca2b358aea759da7fe5e3749cef84a8a0dfaba79cb0926f

Observation 33ab162c-ddc5-420f-8af4-294eeee17022 · outbound

This paper cites Backdoor attacks on dense passage retrievers for disseminating misinformation.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Backdoor attacks on dense passage retrievers for disseminating misinformation

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:33:05.173215Z

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=2026-08-07T14:32:57.811453Z digest=sha256:e529818c871b34908c7c1d0febcec3b089727ea63acc07456fd810725cd51b3a

Observation 5e2d1d09-bd51-4d8c-b069-5f0ea0f5f0ef · outbound

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

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Making llms worth every penny: Resource-limited text classification in banking

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:33:04.999994Z

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=2026-08-07T14:32:57.873477Z digest=sha256:aaf09fb0524d64383238f44a88206a0b26e6834e01911a4c11780807699ee3f4

Observation 9f49b828-256e-4597-8975-7a03c49259bd · outbound

This paper cites A Language Agent for Autonomous Driving.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation A Language Agent for Autonomous Driving

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:57.939867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:57.939867Z digest=sha256:9c87a8bf8e52a0ba1103c875db0a3f839f4f1c982cb098072f2a3039e604c908

Observation a66ddbce-4b21-4dfe-bb4f-fcc24468d40a · outbound

This paper cites A Survey of Conversational Search.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation A Survey of Conversational Search

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:58.003425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:58.003425Z digest=sha256:eae9c3d9b27da53c09f9584ff5fdb458d260b3cb83c2b8ea56c16cb1f9577353

Observation ef56b0a2-998e-459a-8780-63760ddd077d · outbound

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

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Riddle Me This! Stealthy Membership Inference for Retrieval-Augmented Generation

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:58.039510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:58.039510Z digest=sha256:e043073b247ebdb41cf84a9af4806b1e5fd8631799725709b515891bd240e9da

Observation 088a6e46-0538-449b-a100-58205d8fc4ba · outbound

This paper cites Ms marco: A human-generated machine reading comprehension dataset.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Ms marco: A human-generated machine reading comprehension dataset

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:58.065588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:58.065588Z digest=sha256:66884cc22c09e132750d8b6301bac3f74250973618e497cbb3fe1d51b5272e88

Observation 6fe3f7de-d08f-40df-b732-c9742e05cb1b · outbound

This paper cites SQuAD: 100,000+ Questions for Machine Comprehension of Text.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation SQuAD: 100,000+ Questions for Machine Comprehension of Text

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:58.087928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:58.087928Z digest=sha256:a0a94e442387ca265ab98c645d3ce46b2055a834f45dba8fbedbb2180edcabb8

Observation cb8b98b8-0102-46c7-8d13-1c1f8179ec3a · outbound

This paper cites ConfusedPilot: Confused Deputy Risks in RAG-based LLMs.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation ConfusedPilot: Confused Deputy Risks in RAG-based LLMs

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:58.142259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:58.142259Z digest=sha256:1e7317090c7a32d602382219c5ad8f6d6391ce7336ea8ce87f4e7410042b73b8

Observation 949958ee-935c-452c-af47-0e47b10c7c1a · outbound

This paper cites Ragchecker: A fine-grained framework for diagnosing retrieval-augmented generation.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Ragchecker: A fine-grained framework for diagnosing retrieval-augmented generation

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:33:04.834256Z

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=2026-08-07T14:32:58.217110Z digest=sha256:e8e558f36895fce8b74650da201ed633bbcb3b7d12cd99c382cadb244650051d

Observation 61cde023-59f1-48aa-91e2-9cd438cb00ab · outbound

This paper cites Evaluating retrieval quality in retrieval-augmented gen- eration.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Evaluating retrieval quality in retrieval-augmented gen- eration

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:33:04.673482Z

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=2026-08-07T14:32:58.286145Z digest=sha256:a7ec742499b8e4d858cd99ea9bb9618588971da0a4713497b24887ffc3aa72fd

Observation 280d1d1c-91cd-405a-b6ca-2e22dfb36e5c · outbound

This paper cites Machine Against the RAG: Jamming Retrieval-Augmented Generation with Blocker Documents.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Machine Against the RAG: Jamming Retrieval-Augmented Generation with Blocker Documents

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:58.335827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:58.335827Z digest=sha256:2fc8e0fb6a914e263c589afbd4051ce8dbbf4f3d48dfd26e379f283d81e048c0

Observation 44637546-37a4-45af-9f19-36450d15649f · outbound

This paper cites EHRAgent: Code Empowers Large Language Models for Few-shot Complex Tabular Reasoning on Electronic Health Records.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation EHRAgent: Code Empowers Large Language Models for Few-shot Complex Tabular Reasoning on Electronic Health Records

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:58.376475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:58.376475Z digest=sha256:42959058f12c2f7f08b2f916efb764a96c0e4c98ece6da4b741c5156f0f8c7ff

Observation 1e7a13bf-88d0-4fc8-b588-1283af6c392b · outbound

This paper cites Trec 2019 news track overview.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Trec 2019 news track overview

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:33:04.479907Z

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=2026-08-07T14:32:58.417532Z digest=sha256:a8f20fd5ca3449772c77f56247ca49b5889681bb45bb7e94825c25b558dc0e1a

Observation 01b51a31-8c53-41c4-82da-36c89d5806a2 · outbound

This paper cites Corpus Poisoning via Approximate Greedy Gradient Descent.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Corpus Poisoning via Approximate Greedy Gradient Descent

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:58.465950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:58.465950Z digest=sha256:17bfcd62b0ba2da02d89695750af252384b7ba781a857afb8c7619435f677019

Observation cbad8f2e-2d8e-4b62-bb0a-ba33a3ec1543 · outbound

This paper cites Hoist with His Own Petard: Inducing Guardrails to Facilitate Denial-of-Service Attacks on Retrieval-Augmented Generation of LLMs.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Hoist with His Own Petard: Inducing Guardrails to Facilitate Denial-of-Service Attacks on Retrieval-Augmented Generation of LLMs

Reference 66

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:33:02.217503Z

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=2026-08-07T14:32:58.527972Z digest=sha256:fb237bebfa23c155b2e36ffd9f35f6903edbf4ce55fe67bb6616a4e669eeba59

Observation 75222880-261e-4c65-8a19-c9aa0d4cc94e · outbound

This paper cites "Glue pizza and eat rocks" -- Exploiting Vulnerabilities in Retrieval-Augmented Generative Models.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation "Glue pizza and eat rocks" -- Exploiting Vulnerabilities in Retrieval-Augmented Generative Models

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:58.562417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:58.562417Z digest=sha256:9546eae9d97dd3ac98116301d7da3a7f82896a85c1bc9964565ca0c79a0c5ed8

Observation bcd31753-1910-4442-a9b9-d4de92e25569 · outbound

This paper cites Beir: A heterogeneous benchmark for zero-shot evaluation of information retrieval models.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Beir: A heterogeneous benchmark for zero-shot evaluation of information retrieval models

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:33:04.330229Z

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=2026-08-07T14:32:58.621428Z digest=sha256:94acc1b16862e660618d40749d3ba00bf8d962d8eed204213001ffd974b4ede8

Observation 917588d1-f70d-4afd-8621-b167c17b6a8e · outbound

This paper cites LaMDA: Language Models for Dialog Applications.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation LaMDA: Language Models for Dialog Applications

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:58.663864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:58.663864Z digest=sha256:d5d6a225a52f8d14b7e28608439ab54b04651a4be1575324e22a71055ebb7302

Observation 49dde00f-fef8-4e05-8ceb-a73949af8933 · outbound

This paper cites Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:58.713934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:58.713934Z digest=sha256:f37f23cbd74853df29f5e7f6b85266f379cb0465e0359bc62cee1309d08a3f18

Observation b094a397-d9c0-48d4-9396-90462ab27fff · outbound

This paper cites Astute RAG: Overcoming Imperfect Retrieval Augmentation and Knowledge Conflicts for Large Language Models.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Astute RAG: Overcoming Imperfect Retrieval Augmentation and Knowledge Conflicts for Large Language Models

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:58.813809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:58.813809Z digest=sha256:8c2530f474b2645ab98c086475041367b5229f8459176a43dfa727a0f64d470c

Observation bab4faa9-f060-4f28-8b19-f0627f7af40a · outbound

This paper cites Instructrag: Instructing retrieval-augmented genera- tion with explicit denoising.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Instructrag: Instructing retrieval-augmented genera- tion with explicit denoising

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:33:04.155188Z

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=2026-08-07T14:32:58.883795Z digest=sha256:331ec8011b93b5499435217b6e70095d1140a0211da57c13c7b5b0aad0d39950

Observation 69e9cec2-5a46-42f0-af9d-c514275dfb14 · outbound

This paper cites MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:58.946846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:58.946846Z digest=sha256:2070b7c8850334fefa06bd3bf15bbf9be3c13134198abff248f45c5d007fff30

Observation aad991db-5542-4be9-84e5-a84ddb59b9d6 · outbound

This paper cites Rule: Reliable multimodal rag for factuality in medical vision language models.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Rule: Reliable multimodal rag for factuality in medical vision language models

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:33:03.986860Z

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=2026-08-07T14:32:58.983915Z digest=sha256:220f932ec897b33956fab4d9eed0c3daf6157a877c8a86b2c56410274eae379c

Observation 36f41795-19dd-4f66-a508-f3d77d94cd33 · outbound

This paper cites Certifiably robust rag against retrieval corruption.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Certifiably robust rag against retrieval corruption

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:59.042846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:59.042846Z digest=sha256:3e2c6a16bb19831d59d12ace3f76f7c0f45818ee44c3ac43f3505edb62318a6e

Observation 35dd4be1-c704-4bc1-ac10-5a8f157b14a0 · outbound

This paper cites Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:59.112188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:59.112188Z digest=sha256:431b28db2df321e8f93d2fa37706f60b8396d76f3c63056b3d2224a923792c07

Observation 9dfdf5fe-7b53-4217-8534-df99030e04b0 · outbound

This paper cites RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentation.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentation

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:59.202577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:59.202577Z digest=sha256:3ab10eb3e23503436ec81870601433ba0c5bb54cd23e2ffe8586790ea26c198d

Observation 328b8b7c-44b9-4a1d-b583-a54246d7c18b · outbound

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

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation BadRAG: Identifying Vulnerabilities in Retrieval Augmented Generation of Large Language Models

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:59.243279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:59.243279Z digest=sha256:a9cc264653e07117667b34c5e1029a6bcb516ecd9868db0d897c2d5cbf05e72a

Observation 5fb72a77-095b-4c06-bc10-d5c4256a4135 · outbound

This paper cites Enhanced Multimodal RAG-LLM for Accurate Visual Question Answering.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Enhanced Multimodal RAG-LLM for Accurate Visual Question Answering

Reference 79

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:59.328846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:59.328846Z digest=sha256:9a3676f1063c623928b5af3e607b67f8b12c9e2e91d3fb3a490c7b593c045de0

Observation 3c9dd4a4-71a5-4be1-9b76-4be3947826da · outbound

This paper cites Crag-comprehensive rag benchmark.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Crag-comprehensive rag benchmark

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:33:03.785713Z

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=2026-08-07T14:32:59.436766Z digest=sha256:f6b4784b28935a2374a470f5e785c1b3066c79448178fe29f709365ba5da4116

Observation 3da186e8-03a7-42e3-a4fc-11b50ab9f50f · outbound

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

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

Reference 81

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:59.543585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:59.543585Z digest=sha256:aba4afe5caf026c6700d209c9817e65a53ac4a0174a61cdcad99b5fa01b2509e

Observation a24b545a-b500-4a86-ba09-7fe218373904 · outbound

This paper cites EcoSafeRAG: Efficient Security through Context Analysis in Retrieval-Augmented Generation.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation EcoSafeRAG: Efficient Security through Context Analysis in Retrieval-Augmented Generation

Reference 82

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:33:01.824614Z

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=2026-08-07T14:32:59.652064Z digest=sha256:5bf43f666f42efc6a0837001755d18c59cee7b458fc48e1810718dd304302719

Observation 3c3dd768-3858-4b86-a3ae-64f0cbae3c84 · outbound

This paper cites React: Synergizing reasoning and acting in language models.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation React: Synergizing reasoning and acting in language models

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:59.762327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:59.762327Z digest=sha256:be402453f5d2e5d0f8229fa60af1881d1eec47b82ab4bbee737bdf32e368e1fe

Observation 4abb05db-97fe-44d8-8124-7054cf98dd77 · outbound

This paper cites VisRAG: Vision-based Retrieval-augmented Generation on Multi-modality Documents.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation VisRAG: Vision-based Retrieval-augmented Generation on Multi-modality Documents

Reference 84

Resolution
unresolved
no resolver link, observed 2026-08-07T14:32:59.883563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:32:59.883563Z digest=sha256:560d9c47cbc31ec92152c7738fef556a4638b49a6240482b33ecca1332f497c0

Observation 126e37ed-acf7-4ace-89db-519f13d9ed63 · outbound

This paper cites Augmentation-Adapted Retriever Improves Generalization of Language Models as Generic Plug-In.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Augmentation-Adapted Retriever Improves Generalization of Language Models as Generic Plug-In

Reference 85

Resolution
unresolved
no resolver link, observed 2026-08-07T14:33:00.003486Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:33:00.003486Z digest=sha256:5840f83fc2559b50a4ab33ba6066007dc94b4b03e405eacb0f44bdd7a6e0210d

Observation 82062636-8a73-4d13-bf89-ec7da18732a9 · outbound

This paper cites Rag-driver: Generalisable driving explanations with retrieval-augmented in-context learning in multi-modal large language model.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Rag-driver: Generalisable driving explanations with retrieval-augmented in-context learning in multi-modal large language model

Reference 86

Resolution
unresolved
no resolver link, observed 2026-08-07T14:33:00.106610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:33:00.106610Z digest=sha256:4518d1b31ff21fde05b2ee688d28f934b1126431124f8b5df070d0655569cc5a

Observation 5807f233-d77a-478e-9990-9eda9eb5250e · outbound

This paper cites Worse than zero-shot? a fact-checking dataset for evaluating the robustness of rag against misleading retrievals.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Worse than zero-shot? a fact-checking dataset for evaluating the robustness of rag against misleading retrievals

Reference 87

Resolution
unresolved
no resolver link, observed 2026-08-07T14:33:00.174389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:33:00.174389Z digest=sha256:08cfd465aa7b95a5189ec720144fc2508d4aa1e8533f23bb49dd1c63453e48b3

Observation 5405aeb7-8c82-41ac-afbe-09cf504416b0 · outbound

This paper cites Prac- tical poisoning attacks against retrieval-augmented generation.arXiv preprint arXiv:2504.03957, 2025.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Prac- tical poisoning attacks against retrieval-augmented generation.arXiv preprint arXiv:2504.03957, 2025

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-07T14:33:00.291225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:33:00.291225Z digest=sha256:1c1dfa35c303d7775e0a4a99d93c1f0d359b54fcfbbd26c541425bd98aed21ee

Observation 43ee4f78-7ab8-46b4-b85b-c2fe9fa0e5e6 · outbound

This paper cites Traceback of poisoning attacks to retrieval-augmented generation.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Traceback of poisoning attacks to retrieval-augmented generation

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:33:03.643093Z

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=2026-08-07T14:33:00.401057Z digest=sha256:d405a3d666bda00847ae88154d4558fb1e78d37b1145fdde90562ea7e120ea2b

Observation 762e2534-1435-43ae-8809-1f94fcf01c5a · outbound

This paper cites HijackRAG: Hijacking Attacks against Retrieval-Augmented Large Language Models.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation HijackRAG: Hijacking Attacks against Retrieval-Augmented Large Language Models

Reference 90

Resolution
unresolved
no resolver link, observed 2026-08-07T14:33:00.474010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:33:00.474010Z digest=sha256:b84229ddff2060b9672106aedcc13858fcc2c3b27a0212d375b453c5dc1915da

Observation 3039fba3-61c1-4592-a67f-e6dc240e32cb · outbound

This paper cites Retrieval Augmented Generation and Understanding in Vision: A Survey and New Outlook.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Retrieval Augmented Generation and Understanding in Vision: A Survey and New Outlook

Reference 91

Resolution
unresolved
no resolver link, observed 2026-08-07T14:33:00.592379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:33:00.592379Z digest=sha256:3323ce5af9292c527f91b0e01b9bc94c5b1814810dae6c0f878a08621a5f5b7c

Observation 98309379-6233-4c3a-a018-9a47b5a839bd · outbound

This paper cites Poisoning Retrieval Corpora by Injecting Adversarial Passages.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Poisoning Retrieval Corpora by Injecting Adversarial Passages

Reference 92

Resolution
unresolved
no resolver link, observed 2026-08-07T14:33:00.710112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:33:00.710112Z digest=sha256:fcd61e5939406bfcd992a21d54d3fd114407b726df4a55121aab7bf213551620

Observation ff9632c2-972f-46cc-9595-ad9beed8f68c · outbound

This paper cites TrustRAG: Enhancing Robustness and Trustworthiness in Retrieval-Augmented Generation.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation TrustRAG: Enhancing Robustness and Trustworthiness in Retrieval-Augmented Generation

Reference 93

Resolution
unresolved
no resolver link, observed 2026-08-07T14:33:00.835351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:33:00.835351Z digest=sha256:d925eb1f38935000796d11d0a93eadf88db37f29699deda6eb30ff3c0e46f5ff

Observation 326fd7ad-7c2b-4b08-8ad2-78965bd338d8 · outbound

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

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Trustworthiness in Retrieval-Augmented Generation Systems: A Survey

Reference 94

Resolution
unresolved
no resolver link, observed 2026-08-07T14:33:00.919539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:33:00.919539Z digest=sha256:766740d6936ea993d043b2beabdddf9d31f3c45d3bf79bbc38d9b39d8061244b

Observation bb8f74b6-d050-4ddb-90ca-f43407a4faae · outbound

This paper cites Black-Box Opinion Manipulation Attacks to Retrieval- Augmented Generation of Large Language Models.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Black-Box Opinion Manipulation Attacks to Retrieval- Augmented Generation of Large Language Models

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:33:03.498516Z

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=2026-08-07T14:33:00.983684Z digest=sha256:938c60171b5787b7ee6f0bc8684b7207ef1e0f6f808f50cac47464b392fc73e6

Observation 5d67b7c0-c373-4489-9c4d-1f2d00a4253b · outbound

This paper cites an unresolved cited work.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Unresolved cited work

Reference 96

Resolution
unresolved
raw_fallback, observed 2026-08-07T14:33:03.346808Z

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=2026-08-07T14:33:01.071775Z digest=sha256:cbc4a32c14d7b9f21446bbd0467c7bb83f4f18c90aae33acbf47917bc007f34a

Observation 6951ad8d-3dae-4e5f-8580-95152a033014 · outbound

This paper cites an unresolved cited work.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Unresolved cited work

Reference 97

Resolution
unresolved
raw_fallback, observed 2026-08-07T14:33:03.171172Z

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=2026-08-07T14:33:01.170470Z digest=sha256:7520d5847d9617db39b8005f577d17612ec16ce799bf882d02ade69ab1dc88fa

Observation 35d8ab91-5b40-4207-8dea-15bfd4730770 · outbound

This paper cites an unresolved cited work.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Unresolved cited work

Reference 98

Resolution
unresolved
raw_fallback, observed 2026-08-07T14:33:03.009966Z

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=2026-08-07T14:33:01.247518Z digest=sha256:eadbbe4bec51f576de7e40019d4705a9fc9896d5b222e5873d7dd8414a77ed54

Observation 9a6c75c7-028d-4474-94b1-d707242aa2c3 · outbound

This paper cites class" (standalone or non-standalone) and the.

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation class" (standalone or non-standalone) and the

Reference 99

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:33:02.825102Z

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=2026-08-07T14:33:01.360877Z digest=sha256:b8c88a9824b20bad4c68292b3235dc98a31b1b1d24b78b99011e142a3fb77baa

Pith citing papers

Observation ad58ddcf-7096-454f-a151-4e085f27729b · inbound

DisarmRAG: Stealthy Retriever-Centric Poisoning to Disable Self-Correction in Retrieval-Augmented Generation (Extended Version) cites this paper.

DisarmRAG: Stealthy Retriever-Centric Poisoning to Disable Self-Correction in Retrieval-Augmented Generation (Extended Version) Benchmarking Poisoning Attacks against Retrieval-Augmented Generation

Reference 81

Resolution
unresolved
no resolver link, observed 2026-08-05T15:18:36.938530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:18:36.938530Z digest=sha256:a5db76a3600f2a156a867baeb79010cf420cc77a31c6a70283b32695885c7c7f

Observation ab14dd36-08ab-453a-9f47-4b60ddb3c842 · inbound

SafeSearch: Automated Red-Teaming of LLM-Based Search Agents cites this paper.

SafeSearch: Automated Red-Teaming of LLM-Based Search Agents Benchmarking Poisoning Attacks against Retrieval-Augmented Generation

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-04T14:43:56.610925Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T14:43:56.610925Z digest=sha256:9ca6b40b7022de48b648695ebd0ff24211adda2a7c00723a3e394dab01c27065

Observation 1717e7d8-6ee6-49d4-8634-cf2877b4504e · inbound

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

Benchmarking Knowledge-Extraction Attack and Defense on Retrieval-Augmented Generation Benchmarking Poisoning Attacks against Retrieval-Augmented Generation

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-03T03:04:47.779862Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T03:04:47.779862Z digest=sha256:586f4942e11c4b402aa9bb67fa15ca3db80409335119530388dfeb83697524ad

Observation d62086f3-1289-4a9d-9122-28d30bf569f6 · inbound

RAGShield: Detecting Numerical Claim Manipulation in Government RAG Systems cites this paper.

RAGShield: Detecting Numerical Claim Manipulation in Government RAG Systems Benchmarking Poisoning Attacks against Retrieval-Augmented Generation

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-13T23:18:25.905684Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-13T23:14:47.704353Z digest=sha256:ec711d01594a2c621ce983608f2f99673948e7ca42cb6654eca12667026a77c2

Observation 34db4841-77b2-405e-9cc4-9e5b2f3cae30 · inbound

Beyond Explicit Refusals: Soft-Failure Attacks on Retrieval-Augmented Generation cites this paper.

Beyond Explicit Refusals: Soft-Failure Attacks on Retrieval-Augmented Generation Benchmarking Poisoning Attacks against Retrieval-Augmented Generation

Reference 6

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T11:05:08.995921Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-10T04:56:37.758533Z digest=sha256:3f179780526a69e8c654365cbcada4552b4e904e2d8be6d7f5ae6903683d9787

Observation 1a48d20e-4d14-47e9-8eec-0afedf1b35b6 · inbound

Needle-in-RAG: Prompt-Conditioned Character-Level Traceback of Poisoned Spans in Retrieved Evidence cites this paper.

Needle-in-RAG: Prompt-Conditioned Character-Level Traceback of Poisoned Spans in Retrieved Evidence Benchmarking Poisoning Attacks against Retrieval-Augmented Generation

Reference 62

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T11:31:00.568084Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-10T14:52:32.202125Z digest=sha256:6e5f1768e978eb212e2b774d01578109cf49e0e017d60a1ab9133a80ab8ca35c

Observation 83afcb06-1e9c-4027-a6cc-d3f14ce00e72 · inbound

Oracle Poisoning: Corrupting Knowledge Graphs to Weaponise AI Agent Reasoning cites this paper.

Oracle Poisoning: Corrupting Knowledge Graphs to Weaponise AI Agent Reasoning Benchmarking Poisoning Attacks against Retrieval-Augmented Generation

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:37:03.462355Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-12T02:27:06.805794Z digest=sha256:251157c1702491da3f07e25c9b9c0c285d9e4554d8d3ef6cb3e96e9a43d80378

Observation d41c560b-076f-4b89-bed5-7b7230de202b · inbound

SilentRetrieval: Hijacking Retrieval-Augmented Generation via Semantically-Preserving Adversarial Data Poisoning cites this paper.

SilentRetrieval: Hijacking Retrieval-Augmented Generation via Semantically-Preserving Adversarial Data Poisoning Benchmarking Poisoning Attacks against Retrieval-Augmented Generation

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-06-29T11:53:23.247611Z

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=2026-06-29T11:49:32.880569Z digest=sha256:4890144c89927ae887f173a287561589784dbbe5afdde48ad76ac7a30b791f2d

Observation 61e0e649-2c5d-45e0-ba93-81d2ba35811d · inbound

TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation cites this paper.

TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation Benchmarking Poisoning Attacks against Retrieval-Augmented Generation

Reference 15

Resolution
unresolved
no resolver link, observed 2026-07-30T10:56:48.116996Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T10:56:48.116996Z digest=sha256:a9b44f2529a2e7ee516381164d89e10032f99b733d6b9c3a3af9a929eeb5cec7