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Paper Citation Record · LEDGER

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

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2412.04415.

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

pith.paper-citation-record.v1
2412.04415 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:48:57.225641Z

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

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

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

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 11684f58-8985-41b4-bf1d-4a50310f2080 · inbound

Large Language Model Agent: A Survey on Methodology, Applications and Challenges cites this paper.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Targeting the Core: A Simple and Effective Method to Attack RAG-based Agents via Direct LLM Manipulation

Reference 204

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.166276Z

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=2026-05-22T21:51:34.309870Z digest=sha256:cb4c7fb47e4a80a08cde9e838910ff54501601ba0f01a25b6d8db36a94c1bb4e

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

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

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

Reference 11

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Observation 879e6b36-f716-45b9-9c35-f541527b06ff · inbound

REALISTA: Realistic Latent Adversarial Attacks that Elicit LLM Hallucinations cites this paper.

REALISTA: Realistic Latent Adversarial Attacks that Elicit LLM Hallucinations Targeting the Core: A Simple and Effective Method to Attack RAG-based Agents via Direct LLM Manipulation

Reference 177

Resolution
verified exact
arxiv_id, observed 2026-05-14T20:17:56.426097Z

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=arxiv_source observed=2026-05-14T20:13:10.814899Z digest=sha256:cda6fbc2cf6669a213de198a5f8b1cb002f817735b095103f4fbb0ec9a466f00

Observation 2fdb6195-7f4d-4130-bd74-0d544adc3be3 · inbound

Game-Theoretic Multi-Agent Control for Robust Contextual Reasoning in LLMs cites this paper.

Game-Theoretic Multi-Agent Control for Robust Contextual Reasoning in LLMs Targeting the Core: A Simple and Effective Method to Attack RAG-based Agents via Direct LLM Manipulation

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-07-03T05:47:41.220684Z

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=2026-06-27T13:05:57.618969Z digest=sha256:d2670e1da136d36c2d578391e1a1f2e39b5a3f0a99444bcdc4382cd7d5d4fd03

Observation 19877523-1032-4b91-9261-1aaf35107fa0 · inbound

The Containment Gap: How Deployed Agentic AI Frameworks Fail Public-Facing Safety Requirements cites this paper.

The Containment Gap: How Deployed Agentic AI Frameworks Fail Public-Facing Safety Requirements Targeting the Core: A Simple and Effective Method to Attack RAG-based Agents via Direct LLM Manipulation

Reference 13

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T13:58:21.498891Z

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=arxiv_source observed=2026-06-27T07:25:32.556071Z digest=sha256:db4d219ca1fce061bc2ad38c275a08b2e87090d6d5187a04ad7daaf7ea0461c4