Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:33:01.360877Z
Paper Citation Record · LEDGER
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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:33:01.360877Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T15:18:36.938530Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
99 of 99 outbound references displayed
External citation measurements
0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Observation eb515526-36eb-4ddb-ac1d-6403d158fcc6 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation https://www.anthropic.com/news/claude-3-7-sonnet
Reference 1
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Observation ae8db373-cc3f-40cb-a7de-59a73978ca30 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation https://blog.google/ technology/google-deepmind/google-gemini-ai-update-december-2024
Reference 2
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Observation 0857b61f-942c-4c97-bef6-67570aa588ab · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation https://openai.com/index/gpt-4-1
Reference 3
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Observation 643ff895-629f-499f-ac38-a81905bcf1a5 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation https://modelcontextprotocol.io/ introduction
Reference 4
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Observation 58c03155-f4a8-40ac-9815-68c44326f6db · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation https://www.llama.com/models/llama-4
Reference 5
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Observation 6e4f394b-0e7b-49e4-93df-4e9fc216083a · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Unresolved cited work
Reference 6
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Observation 7023bea6-c370-4cc5-a31c-916988a544f6 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation GPT-4 Technical Report
Reference 7
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Observation 64299fff-671c-49d4-aaf4-19f231b63137 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Trec ikat 2023: A test collection for evaluating conversational and interactive knowledge assistants
Reference 8
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Observation aba5cffd-0f26-43ef-92b9-ea45c14f564c · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation PaLM 2 Technical Report
Reference 9
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Observation c43278b2-fc8d-4757-b363-d31da86312d4 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Improving language models by retrieving from trillions of tokens
Reference 10
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Observation 23918784-0ac5-4ee5-b537-342b8cfdf8ea · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Language models are few-shot learners
Reference 11
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Observation 38dc0dc6-1b9b-4457-8321-342623c23181 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Poisoning web-scale training datasets is practical
Reference 12
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Observation fa32781c-72a6-42de-83ed-2a3ed211942f · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generation
Reference 13
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Observation 64cfae5a-c39a-413e-966f-63f4d9274ef6 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation One Shot Dominance: Knowledge Poisoning Attack on Retrieval-Augmented Generation Systems
Reference 14
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Observation 4c67b0c5-ddc2-4d7f-acf8-be75083c4300 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Phantom: General trigger attacks on retrieval augmented language generation
Reference 15
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Observation 50c12053-cd4b-4c95-ba21-572ceb7fb9e2 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Benchmarking large language mod- els in retrieval-augmented generation
Reference 16
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Observation cc5f52d0-1f83-43f5-b11b-3be84cc33e1f · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text
Reference 17
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Observation c1780cfb-b22e-4278-807b-4b7dcdd9248a · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Can Pre-trained Vision and Language Models Answer Visual Information-Seeking Questions?
Reference 18
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Observation cd8320f5-4d1a-443a-9a54-047f25fc888a · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Agentpoison: Red-teaming llm agents via poisoning memory or knowledge bases
Reference 19
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Observation d4bf530a-d7be-4bf1-8238-a5dbb768c4b2 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Flipedrag: Black-box opinion manipulation attacks to retrieval- augmented generation of large language models
Reference 20
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Observation c6a40ba3-7413-49b3-ba06-8121ceb5ab82 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation TrojanRAG: Retrieval-Augmented Generation Can Be Backdoor Driver in Large Language Models
Reference 21
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Observation c2dcd335-ad68-4fca-a280-e63feeea52f7 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation CORAL: Benchmarking Multi-turn Conversational Retrieval-Augmentation Generation
Reference 22
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Observation 5e4051a2-0940-449c-bbcc-940cfc2150f4 · outbound
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
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Observation af08a444-e465-442d-913d-d06fea622b93 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation The rag paradox: A black-box attack exploiting unintentional vulnerabilities in retrieval-augmented generation systems
Reference 24
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Observation 0cd633ec-05aa-4362-ab10-094ec0fb47af · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions
Reference 25
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Observation 2e4aeb03-d6d5-4a7a-92dc-0872acf117ef · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation The power of noise: Redefining retrieval for rag systems
Reference 26
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Observation 9d2fd507-02b2-4ea7-b9a0-48579515f91d · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Retrieval-Augmented Generation for Large Language Models: A Survey
Reference 27
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Observation 3a2643ec-c27c-4d98-971e-af52f1cc1db8 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Did aristotle use a laptop? a question answering benchmark with implicit reasoning strategies
Reference 28
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Observation e8743175-d732-43ce-b914-a907cefe0218 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Topic-fliprag: Topic-orientated adversarial opinion manipulation attacks to retrieval-augmented generation models
Reference 29
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Observation c0b00558-31dd-4191-a7ce-c8bbc7b5da10 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Reference 30
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Observation da75b75a-9208-4cc9-a5a5-c2e6981ba25d · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation GPT-4o System Card
Reference 31
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Observation fbd9e164-e37c-4b57-956f-3305db231dda · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Unsupervised Dense Information Retrieval with Contrastive Learning
Reference 32
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Observation f16bfc5d-3549-4832-ab58-81d609ddc017 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Baseline Defenses for Adversarial Attacks Against Aligned Language Models
Reference 33
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Observation b5043607-4dc8-4f12-bf13-abc547788d41 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Interpolated estimation of markov source parameters from sparse data
Reference 34
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Observation 00b2ce9f-8a68-46c1-9a83-0d7152b1a3bf · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity
Reference 35
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Observation 11ef88db-0564-4add-aea8-30e540ca2488 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications
Reference 36
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Observation ce9e1479-6608-4898-b3ed-06f61f811288 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Active Retrieval Augmented Generation
Reference 37
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Observation 78610109-bc3a-4a30-a63e-a61d16299297 · outbound
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
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Observation e3930e9d-7551-46ad-b14b-e66ab494071f · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Research
Reference 39
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Observation 759c364f-7a02-4b20-9ba5-983c77c6b480 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Dense Passage Retrieval for Open-Domain Question Answering
Reference 40
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Observation b814be3e-e3fc-48e9-8bed-c17ed713b0eb · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation MTRAG: A Multi-Turn Conversational Benchmark for Evaluating Retrieval-Augmented Generation Systems
Reference 41
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Observation 752c2593-87c5-4ba8-a28c-f27132dbc365 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMs
Reference 42
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Observation 3748f086-724c-41fd-a4f5-1bb7ec0b7c11 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation RAD-Bench: Evaluating Large Language Models Capabilities in Retrieval Augmented Dialogues
Reference 43
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Observation f386655e-c817-471e-9fe2-c9f55c3f2ae5 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Natural questions: a benchmark for question answering research
Reference 44
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Observation 0edb92d7-7eee-4ece-8bd8-34a34f868674 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation AlzheimerRAG: Multimodal Retrieval Augmented Generation for Clinical Use Cases using PubMed articles
Reference 45
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Observation 894c6faf-ea8b-46d8-b131-31dafac7bfc8 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Retrieval-augmented generation for knowledge-intensive nlp tasks
Reference 46
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Observation 729a7a0f-0f24-42ec-a575-6b483fbbb14c · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Seeing is believing: Black-box member- ship inference attacks against retrieval augmented generation
Reference 47
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Observation 68520974-af71-4bd0-88a9-2bde47f4dfa4 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation SafeRAG: Benchmarking Security in Retrieval-Augmented Generation of Large Language Model
Reference 48
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Observation d958df5b-73a0-4c35-8156-ce0fa693c920 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation DeepSeek-V3 Technical Report
Reference 49
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Observation a97f2a88-7634-424f-851f-340b3af38c68 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Poisoned-MRAG: Knowledge Poisoning Attacks to Multimodal Retrieval Augmented Generation
Reference 50
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Observation 4a77545b-7d76-4a18-9cbe-493bd037948d · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Formalizing and benchmarking prompt injection attacks and defenses
Reference 51
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Observation 33ab162c-ddc5-420f-8af4-294eeee17022 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Backdoor attacks on dense passage retrievers for disseminating misinformation
Reference 52
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 5e2d1d09-bd51-4d8c-b069-5f0ea0f5f0ef · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Making llms worth every penny: Resource-limited text classification in banking
Reference 53
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 9f49b828-256e-4597-8975-7a03c49259bd · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation A Language Agent for Autonomous Driving
Reference 54
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Observation a66ddbce-4b21-4dfe-bb4f-fcc24468d40a · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation A Survey of Conversational Search
Reference 55
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Observation ef56b0a2-998e-459a-8780-63760ddd077d · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Riddle Me This! Stealthy Membership Inference for Retrieval-Augmented Generation
Reference 56
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Observation 088a6e46-0538-449b-a100-58205d8fc4ba · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Ms marco: A human-generated machine reading comprehension dataset
Reference 57
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Observation 6fe3f7de-d08f-40df-b732-c9742e05cb1b · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation SQuAD: 100,000+ Questions for Machine Comprehension of Text
Reference 58
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Observation cb8b98b8-0102-46c7-8d13-1c1f8179ec3a · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation ConfusedPilot: Confused Deputy Risks in RAG-based LLMs
Reference 59
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Observation 949958ee-935c-452c-af47-0e47b10c7c1a · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Ragchecker: A fine-grained framework for diagnosing retrieval-augmented generation
Reference 60
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 61cde023-59f1-48aa-91e2-9cd438cb00ab · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Evaluating retrieval quality in retrieval-augmented gen- eration
Reference 61
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 280d1d1c-91cd-405a-b6ca-2e22dfb36e5c · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Machine Against the RAG: Jamming Retrieval-Augmented Generation with Blocker Documents
Reference 62
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Observation 44637546-37a4-45af-9f19-36450d15649f · outbound
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
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Observation 1e7a13bf-88d0-4fc8-b588-1283af6c392b · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Trec 2019 news track overview
Reference 64
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Observation 01b51a31-8c53-41c4-82da-36c89d5806a2 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Corpus Poisoning via Approximate Greedy Gradient Descent
Reference 65
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Observation cbad8f2e-2d8e-4b62-bb0a-ba33a3ec1543 · outbound
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
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 75222880-261e-4c65-8a19-c9aa0d4cc94e · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation "Glue pizza and eat rocks" -- Exploiting Vulnerabilities in Retrieval-Augmented Generative Models
Reference 67
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Observation bcd31753-1910-4442-a9b9-d4de92e25569 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Beir: A heterogeneous benchmark for zero-shot evaluation of information retrieval models
Reference 68
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Observation 917588d1-f70d-4afd-8621-b167c17b6a8e · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation LaMDA: Language Models for Dialog Applications
Reference 69
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Observation 49dde00f-fef8-4e05-8ceb-a73949af8933 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions
Reference 70
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Observation b094a397-d9c0-48d4-9396-90462ab27fff · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Astute RAG: Overcoming Imperfect Retrieval Augmentation and Knowledge Conflicts for Large Language Models
Reference 71
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Observation bab4faa9-f060-4f28-8b19-f0627f7af40a · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Instructrag: Instructing retrieval-augmented genera- tion with explicit denoising
Reference 72
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Observation 69e9cec2-5a46-42f0-af9d-c514275dfb14 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models
Reference 73
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Observation aad991db-5542-4be9-84e5-a84ddb59b9d6 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Rule: Reliable multimodal rag for factuality in medical vision language models
Reference 74
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 36f41795-19dd-4f66-a508-f3d77d94cd33 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Certifiably robust rag against retrieval corruption
Reference 75
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Observation 35dd4be1-c704-4bc1-ac10-5a8f157b14a0 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval
Reference 76
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Observation 9dfdf5fe-7b53-4217-8534-df99030e04b0 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentation
Reference 77
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Observation 328b8b7c-44b9-4a1d-b583-a54246d7c18b · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation BadRAG: Identifying Vulnerabilities in Retrieval Augmented Generation of Large Language Models
Reference 78
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Observation 5fb72a77-095b-4c06-bc10-d5c4256a4135 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Enhanced Multimodal RAG-LLM for Accurate Visual Question Answering
Reference 79
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Observation 3c9dd4a4-71a5-4be1-9b76-4be3947826da · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Crag-comprehensive rag benchmark
Reference 80
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 3da186e8-03a7-42e3-a4fc-11b50ab9f50f · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering
Reference 81
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Observation a24b545a-b500-4a86-ba09-7fe218373904 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation EcoSafeRAG: Efficient Security through Context Analysis in Retrieval-Augmented Generation
Reference 82
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 3c3dd768-3858-4b86-a3ae-64f0cbae3c84 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation React: Synergizing reasoning and acting in language models
Reference 83
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Observation 4abb05db-97fe-44d8-8124-7054cf98dd77 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation VisRAG: Vision-based Retrieval-augmented Generation on Multi-modality Documents
Reference 84
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Observation 126e37ed-acf7-4ace-89db-519f13d9ed63 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Augmentation-Adapted Retriever Improves Generalization of Language Models as Generic Plug-In
Reference 85
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Observation 82062636-8a73-4d13-bf89-ec7da18732a9 · outbound
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
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Observation 5807f233-d77a-478e-9990-9eda9eb5250e · outbound
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
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Observation 5405aeb7-8c82-41ac-afbe-09cf504416b0 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Prac- tical poisoning attacks against retrieval-augmented generation.arXiv preprint arXiv:2504.03957, 2025
Reference 88
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Observation 43ee4f78-7ab8-46b4-b85b-c2fe9fa0e5e6 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Traceback of poisoning attacks to retrieval-augmented generation
Reference 89
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Observation 762e2534-1435-43ae-8809-1f94fcf01c5a · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation HijackRAG: Hijacking Attacks against Retrieval-Augmented Large Language Models
Reference 90
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Observation 3039fba3-61c1-4592-a67f-e6dc240e32cb · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Retrieval Augmented Generation and Understanding in Vision: A Survey and New Outlook
Reference 91
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Observation 98309379-6233-4c3a-a018-9a47b5a839bd · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Poisoning Retrieval Corpora by Injecting Adversarial Passages
Reference 92
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Observation ff9632c2-972f-46cc-9595-ad9beed8f68c · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation TrustRAG: Enhancing Robustness and Trustworthiness in Retrieval-Augmented Generation
Reference 93
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Observation 326fd7ad-7c2b-4b08-8ad2-78965bd338d8 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Trustworthiness in Retrieval-Augmented Generation Systems: A Survey
Reference 94
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Observation bb8f74b6-d050-4ddb-90ca-f43407a4faae · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Black-Box Opinion Manipulation Attacks to Retrieval- Augmented Generation of Large Language Models
Reference 95
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Observation 5d67b7c0-c373-4489-9c4d-1f2d00a4253b · outbound
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Reference 96
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Observation 6951ad8d-3dae-4e5f-8580-95152a033014 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Unresolved cited work
Reference 97
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Observation 35d8ab91-5b40-4207-8dea-15bfd4730770 · outbound
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation Unresolved cited work
Reference 98
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Observation 9a6c75c7-028d-4474-94b1-d707242aa2c3 · outbound
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Reference 99
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Observation ad58ddcf-7096-454f-a151-4e085f27729b · inbound
DisarmRAG: Stealthy Retriever-Centric Poisoning to Disable Self-Correction in Retrieval-Augmented Generation (Extended Version) Benchmarking Poisoning Attacks against Retrieval-Augmented Generation
Reference 81
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Observation ab14dd36-08ab-453a-9f47-4b60ddb3c842 · inbound
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Reference 69
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Observation 1717e7d8-6ee6-49d4-8634-cf2877b4504e · inbound
Benchmarking Knowledge-Extraction Attack and Defense on Retrieval-Augmented Generation Benchmarking Poisoning Attacks against Retrieval-Augmented Generation
Reference 39
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Observation d62086f3-1289-4a9d-9122-28d30bf569f6 · inbound
RAGShield: Detecting Numerical Claim Manipulation in Government RAG Systems Benchmarking Poisoning Attacks against Retrieval-Augmented Generation
Reference 11
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Observation 34db4841-77b2-405e-9cc4-9e5b2f3cae30 · inbound
Beyond Explicit Refusals: Soft-Failure Attacks on Retrieval-Augmented Generation Benchmarking Poisoning Attacks against Retrieval-Augmented Generation
Reference 6
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1a48d20e-4d14-47e9-8eec-0afedf1b35b6 · inbound
Needle-in-RAG: Prompt-Conditioned Character-Level Traceback of Poisoned Spans in Retrieved Evidence Benchmarking Poisoning Attacks against Retrieval-Augmented Generation
Reference 62
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Observation 83afcb06-1e9c-4027-a6cc-d3f14ce00e72 · inbound
Oracle Poisoning: Corrupting Knowledge Graphs to Weaponise AI Agent Reasoning Benchmarking Poisoning Attacks against Retrieval-Augmented Generation
Reference 31
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Observation d41c560b-076f-4b89-bed5-7b7230de202b · inbound
SilentRetrieval: Hijacking Retrieval-Augmented Generation via Semantically-Preserving Adversarial Data Poisoning Benchmarking Poisoning Attacks against Retrieval-Augmented Generation
Reference 34
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 61e0e649-2c5d-45e0-ba93-81d2ba35811d · inbound
TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation Benchmarking Poisoning Attacks against Retrieval-Augmented Generation
Reference 15
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