Pith. sign in

Paper Citation Record · LEDGER

Benchmarking Poisoning Attacks against Retrieval-Augmented Generation

As of 7 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:eb7e819c6d9215a5a8c102bd992fbdd22b23dfed8f06d13fcacdbc7c0f273d47

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=sha256:193307ab944ee7ddee0ea1ce9ed8f878f622b46de4369715aadd0582a580362e

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=sha256:81673870fb866ad9e8fc1ac70da9043d1a043873306d8bd9f40c52e9b63bed7a

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=sha256:8d3a619bb8bc51a75c0e9b1cacc22978aa64654328849739404e3d2074b87859

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:c2b57afabfbede5ed0377584c9d9d68de0ef824883ce05012b1dec89084762af

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=sha256:10952d0251dfa956792e05a906fc53e9ad810adbe503a9796116d770f847a3c1

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:a2e26e38ec65cbb3395b6ca1ca2467a3eed3f564643ad6d188d2d4003da2aa34

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:a115a6f99f6fcc6453bc29441ffa23ab3be7b4f82b9db88bce18bb00bebf3d00

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=sha256:6572fb5609b45cb15c5d995e5ed808df04c346f1b7d1dd48b91cf63c97b9e1cd

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=sha256:315905f43d8e91bc68fc4daf45ff527f79c7d43cdd5b4a8a0150f16bd17d6bcb

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:f71d428868c69563eb45cbfb74e43d4b61523285f1a9b8b486830d4f8578e5f8

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=sha256:46b2d1e230d06aea2b892b472bcf6ecaaacd869b8f7aaf94eb8d3379c0e97bb4

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=sha256:7b2cb709efaf3446832a3cdd3bc7efc84c88b8db548d74a8c843e78e79376ed7

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=sha256:7e7baecea0d5ac42980b6a6eeeeaf4d9e8c4bd4f6017d52f53d5694c0f78e0f7

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=sha256:20c88bcf61e304e9c22309ac97991d732000e4742873c0d24d3936c57da1af60

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:b6be7898521e4b21366e1421358aed5fe86d951137898c6db7952a44a47f6d74

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=sha256:19f5ab1606d37b661c217a243ed26140611acf5c96149e52d45f4e028b1164eb

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=sha256:69ca79c97b135cd2342c7a648d99348d811825f4e078077c805fef6cc0757813

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=sha256:28d697863d201582fe5269007db74a697d354086acbe3ea1e306bca2a74cf683

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=sha256:767082710af50657725a9192f21843cc1dba7799c35ecd4f6dce24922ffb7520

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=sha256:7e697f7d3c70c2743d7471a0b0a1bff057b4642b097b78e89ceffb42c58fc7c3

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:f70ee0d0357ebb74b96956b92d8234f6211c7055506ef04c54c84b5f5b460d61

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:b5422b3d8b7a194eea69a509f569ef60845d21557c047bdf1c2f5451d46427ff

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=sha256:80280f9b2615a098523b5b8f24436a01c4976d4eaebd668c2a779e2eec49b6d3

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:f423e3844aca15efeb14ba2c148c45487c73e01594ab81a13cb2752ef7eb33ca

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=sha256:72c3f560a2d5d3f03d07104103a71bebb417b009f7054e14a71d922793a3d1ac

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:a642bbe339c2b6a04f97daa8abc0592d88a4a4a282b59ccc4f882191ba31f74e

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=sha256:19d2ca69ce1315738ddc72d6d2a4e753075ac4bad138aecd240401535e4b6edc

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=sha256:7d1cb6b0670f7b0a60be523c37cd05812e6242afe355875f16c9a21654e67c39

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:a243d6fe0f86a629f843a320e804f0319bc8b1cc437b12edf50f78fb3e34ddcc

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=sha256:8e039e257e77f65e3114354c423cc9e1691e94e983a02dbbe8a7f0d03370c10f

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:c158794e02b8a6447807d529747326a78d0b012ff295c35e09a4e5bb3e28c6ce

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=sha256:66258a68d6a787e8edc831b350494c5a44b4f41518f6b5ac8b981b48cfe66e4f

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=sha256:702f76b2129246e862f4bbe5eaf34d8e64ce703c5c2ce4bd9d50facac5549391

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=sha256:9e55758d45a9f15d329787fe68dcdc24404ddf3d63b003839a1e95c8e44fc4d5

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:e92b0f00b9f3897d0b84aa6330ec95b43b943a7469b90e99d1bb9f18ad97a7de

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=sha256:2301c83d46015c2eac5e31611a2240adc88d29b280da768ebc00d6d47be9cbf7

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=sha256:0c8602714b833eb80a5f270efbe74127e8bb9debc9d7d5c55cf4060acca70d60

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=sha256:55fc348507c9054f906d84f29509102069bacc49c6c42119bfbd1fa566abfd4e

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=sha256:8bd2d212f1db78daad488e1125bd80df2740d43bebb4cded56fc5880332e2b69

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:d67fe885753e71f543244995dd0863867c70421985c68baf750f0df384faac86

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=sha256:601052ff079cb75aee240e7f255e0288800d124ca06a2803ab6a1462c5218443

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=sha256:36d846dabebb7702d7568795f66536dd782ee09673374f4849906d1fd650e3e3

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=sha256:19e2e4a9d2554ac47c8b9eb5acb87b3c72928f62e7ae2bd90969e13e5aa18c59

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=sha256:91f33fbdd2b0c33b06a36fc7a9b94387ed63c1206ccff7baf3a780d1503cef1a

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=sha256:11f03a275eb2319e142ae64c5b1d98a0663242eb366a3e97cdac8a80a1a6036d

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:f37e20351f5b4bb89961ccc5ec1bd329394e7548428a61edd9451bd64a87ee5a

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=sha256:02f189515a445936066f6ece827253ef66faa2ae4f0145dfddd07917fa7824c9

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:d3fe5a09fc2c1e908db92fa5ca0d1588e8836c4d5642a4f5a05f10e525de8759

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=sha256:03b131c1a652a978c1f03804b2e1337d0d574f6376b1c1d0dd83f2ea6a452e7f

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=sha256:07ccf94aae0558b8bfe73ac9b577786f91c373d90c7ca9b9d9daa0762c2ce489

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=sha256:877862d36050e835c1b4e8f36e1558ad81172d4164c3ad6e84f18596dd6f0b59

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=sha256:1627b5e557765463ca850901afc53a0093fe1c7a5a880f17302f2afa1043401c

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=sha256:24acaea4dcc03737cb9562127a748e572f93a26ca94e2c3ce5b1e88e1f09a165

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:e4afd0b36a6b61d915d9c0674ae1724ccf08da08651173bd77ca94982222eaad

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:d7d9e6dd3661d4ebf6535fea1ddce2068837ac9338b565e75d04a49b6cc6de56

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=sha256:2f728a301dc140f67b8a619ea427c66af5b8f167ab7e8f34348b2765ec0d0cec

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=sha256:24ab89a3e5014ce1b88f52108032dbe19fe220ab903d696d64e5efe531e86523

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=sha256:5c90951c46d811d8322c30e78de3d459590eb16313b27c2650501d99b806b45d

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=sha256:253766cda865e9222a89e3a3d32a2458e7cc5ecb6a1a0ffa3c3698a9435ab8f1

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:f05c8bca668fa7f3775946bf829c3c3f3cbefedf30c521072577c24a24bb3688

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=sha256:4cdacfd456442f9882f1c0f087fc1e94f15cf4210cd6ddc5ad9485f485da99ea

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:c98ecdbec0134a1ae674afb7b3b793d5300d02a2ac0dce331768add949d7a09f

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=sha256:1d31e94e24ae6bd2cd48d68208dda1a9c8ae6abcd8551a22c69c2333e3d21cb7

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=sha256:8b82b4cab5f8e053e90d8ad07fff73c39e0f037f296d21dea31d1ce3fad8672a

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:b5bc64c472bef570c2b825bee53ad2277fd119db47bd935b0edd996e00e02dcd

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:be934c606c961c22afabc4486a2eb98b543ca8e19aace8e3cfac9ebdb6ac8e97

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:d0fae1758c1c57f165f8683ee23685e9b04d55736e09032dd7cdea54c98f5f48

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=sha256:5711775b36c66a2598e72d25cfdea569f4d496f3ead84e4fc8d55a7bdf2c98d9

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:bcbb51979c904cb78d50593fd68b6e1cbb17d20ec95332fbbe84c1c4750552c9

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=sha256:2580ef1aef7b0ed7e9b9c0a139b95bcb9b0b91c5be6cb2f75c0c536c431553ed

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=sha256:8d093cea5698f4651ff63ce42a137314ea9b865078c8ff772260eb9d710a9a92

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=sha256:44bb46b38c55835c7e500f4e44acde3c916744338e9b1d7d1cdd7e4d862dc5b0

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=sha256:534f5f3424bec57c78a9616e7f933b9425a0c3b43402ea961713f8e9fa00b20b

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=sha256:5fb63e3a60a692dd8f3d80b7a6195ed5cfe0338ece199765e1ac31f54daca9ac

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=sha256:695a0a3552948fa438f8af91ebc395138221ea334128355ed64513da8560bab2

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=sha256:94e8b5fda09346930e09e73dfadcdb2bf85ea01508f2a2bed5b1b37f360ec0a3

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:b8083871f81e29f550133afb150103c6718e1e222e12c849b11940b701043479

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=sha256:4a671dba031c87b7c4502b0d971d4e5df44fed983244a29fbda0fd7fe3e7a4d6

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:c056e612b9e7f62a653c2b6d9ad1032d5d44bd2360c13240a5ed96d380c7fe81

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=sha256:77d78e844278441b9a74b3c1b742ce00ababd8cb000efec43a834efd7273b3af

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=sha256:75edd52f3fb68adb1227b934bb1e74143b243fdaad40d88ec4bbea9e7d4b4c73

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:d4949a0f128e4c4b9dabe272312e859788ae6417c7c0a4f3c811474caccc9d78

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=sha256:9bc818f08ae871831ea43109b7c5878eeabe540eaefead0b9c5f9b8967dded8b

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=sha256:7dc737fe90a0e57bb1c157d80dd260fd0773ac751101c835158582440fe261da

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=sha256:11bd686c0598e7eae6c58f26780da7a4975486418b9ba92062e5161ea1a410b5

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=sha256:6a71b3cb5edc6e6872a4e00a731aefe806f48197c6b45ed2da467570b4daeefe

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=sha256:049676abda4526dc7695e48e489d06513686bc267c630db08abbf6633610320a

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=sha256:9794f4a5811a7af5cf9f6a96bea98f10ce02c4ce51854db5343ba1b1dcc6f10f

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=sha256:35be20e6d4f444ba20f3dbd2bc11da135dc955435b4c962158156002a846a3f1

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=sha256:4d901e13517da350d13a72f502a44b968c7a93b6280b88afd2acbe09e475be64

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=sha256:5e9800188c0ce61ae4fbf151518389e9ce1352178a9c64927ddd07a697ed7248

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=sha256:69c695f213486779ae4462a01b6d3515ca1708dea4ef21502b2f104de2bc0c9c

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=sha256:61a6c5b4ac3e90d6475536c32929c70f1f1c22af9ba7f09f6e8d4db5615685b4

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:b2c0ec03dea737a8bbc4746378e3d7d5db733a11c03fa0cc4511ccaf26e6eb0f

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:e940bd068364f183e14a2403a3ed0d1051f86839c0bb8b06495ad79bfd1e960d

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:f66b5a99bfd90a5c165019a75e340ee7fc4029760d1823191329ed309500990f

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:e0c52265a6aeaf9b268b63dddae71713566eaa87f42fd5b213e1497ed7c8e9ad

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=sha256:11f7a10e3bc6fe46e4d30155266f91596995af835646956573cc47170a869240

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=sha256:544170ef92f812e87c38ac1d61d1bdbc8b157e4d9d9d815b447a2961776b41ea

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=sha256:2e7546ab02971dba700533fe999462233775b42e5c40958cdd3f868d428a03ce

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:f8e1535dcbd0e66399f236d0d7690bb41121e6761c0ffb4b250bbe0a8314acc0

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:db54b92c833a861711a2694b198a8550f006346f70a428647e8315ac92ec7f37

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:cc705f752916228e781a2171a41090f1f5cb46d64dafcc821ec2857646000a41

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=sha256:5b40d652c3d3495cb7189dc44c85b277e1431e31bdb8f6d81e3af8ca11aa381a

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=sha256:0fdb2e974b77d9ee5d1213d54afdc7a2152a1931ae0cc8ba2c2460a46954821c

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=sha256:855b46baf919ee12cb72a94673d7737901e6ffe548dbb67a0c1b572715ad8ed7

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=sha256:83e7f91db2f0dc221f32defae252814fc3c46284ed9d338eb3981418763f80f0