Pith. sign in

Paper Citation Record · LEDGER

On the Risk of Misinformation Pollution with Large Language Models

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:2305.13661.

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

pith.paper-citation-record.v1
2305.13661 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:20:04.715116Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T08:30:31.653552Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a4ddbc1f-2308-4042-aa7b-e7005b125903 · inbound

TrustLLM: Trustworthiness in Large Language Models cites this paper.

TrustLLM: Trustworthiness in Large Language Models On the Risk of Misinformation Pollution with Large Language Models

Reference 226

Resolution
verified exact
arxiv_id, observed 2026-05-18T11:17:08.646509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-18T11:17:08.108565Z digest=sha256:4e156b36924d4e093cef91b420b4c5376ac81e8a66091850b366382407b68671

Observation 369c9f5d-19ac-4f14-9f20-aba51671f76a · inbound

Scaling Synthetic Data Creation with 1,000,000,000 Personas cites this paper.

Scaling Synthetic Data Creation with 1,000,000,000 Personas On the Risk of Misinformation Pollution with Large Language Models

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-16T00:03:55.768468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-16T00:03:55.599967Z digest=sha256:e8f8288fcb24064b14d11f5e2a0ae9d06e0fa3ac9eb52244e4dd731e47f96fb9

Observation a9305830-6ec0-42de-a771-1a3b14a0cf8a · inbound

Political Fact-Checking Efforts are Constrained by Deficiencies in Coverage, Speed, and Reach cites this paper.

Political Fact-Checking Efforts are Constrained by Deficiencies in Coverage, Speed, and Reach On the Risk of Misinformation Pollution with Large Language Models

Reference 2

Resolution
malformed identifier
no resolver link, observed 2026-08-11T13:20:04.715116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:20:04.715116Z digest=sha256:1668dc12b4ea66688a9ba4c55b3cf5f30a8b465201290ffaafc7b0fb1bafd0f8

Observation 604fd72d-c5f1-41cf-9fc1-eb3ff5469233 · inbound

RbFT: Robust Fine-tuning for Retrieval-Augmented Generation against Retrieval Defects cites this paper.

RbFT: Robust Fine-tuning for Retrieval-Augmented Generation against Retrieval Defects On the Risk of Misinformation Pollution with Large Language Models

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-09T23:48:53.978600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T23:48:53.978600Z digest=sha256:500638cbd44286d6de969a7955877ae60aa6f7376f963c599c5944e8d10a8603

Observation 456ac9fa-8c7a-413d-a80e-457b130df0b1 · inbound

Knowledge Synthesis of Photosynthesis Research Using a Large Language Model cites this paper.

Knowledge Synthesis of Photosynthesis Research Using a Large Language Model On the Risk of Misinformation Pollution with Large Language Models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-09T16:47:18.180264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:47:18.180264Z digest=sha256:669219b0a5ba9bcf002a6c4bbb63813de79a5fafc89b54cc52b0dc4a4038f0e7

Observation 5867cb47-aca7-4d90-8547-0e62d67274b8 · inbound

XAttnMark: Learning Robust Audio Watermarking with Cross-Attention cites this paper.

XAttnMark: Learning Robust Audio Watermarking with Cross-Attention On the Risk of Misinformation Pollution with Large Language Models

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-05-25T08:30:31.657186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-25T08:30:15.011210Z digest=sha256:0c2b01a4be766549c0e9164f1c3bcce9e57e66ccaa33f67f7aa18fc355224041

Observation d04cee5b-e914-4db7-827a-78d179741f41 · inbound

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training cites this paper.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training On the Risk of Misinformation Pollution with Large Language Models

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-07T15:36:06.410393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:36:06.410393Z digest=sha256:f085f5211ee53e3e38a9f64b7b9cf828577965eef64d6be2b9adbb12950e836f

Observation a94a1d61-8e0d-470a-8a80-68e877edd8e6 · inbound

Helpful Agent Meets Deceptive Judge: Understanding Vulnerabilities in Agentic Workflows cites this paper.

Helpful Agent Meets Deceptive Judge: Understanding Vulnerabilities in Agentic Workflows On the Risk of Misinformation Pollution with Large Language Models

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T11:10:45.601797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:10:45.601797Z digest=sha256:8e3e5a9a38b9242ab711c0650b935250d36b9ddc4947473a3b31525f0c58b208

Observation e0f22039-0711-4706-bcb8-8cd547586be4 · inbound

Through the Stealth Lens: Attention-Aware Defenses Against Poisoning in RAG cites this paper.

Through the Stealth Lens: Attention-Aware Defenses Against Poisoning in RAG On the Risk of Misinformation Pollution with Large Language Models

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-25T08:15:34.219419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-25T08:10:31.473565Z digest=sha256:689173da699d5e26040bcaf533551089f063b0b945031805ffc93c1c8279e6f2

Observation 12e09c67-67cb-4726-9a63-d2b8fc67e563 · inbound

Can LLM Improve for Expert Forecast Combination? Evidence from the European Central Bank Survey cites this paper.

Can LLM Improve for Expert Forecast Combination? Evidence from the European Central Bank Survey On the Risk of Misinformation Pollution with Large Language Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T21:52:49.456154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:52:49.456154Z digest=sha256:0a8e7da223e61849f868dc8583e87e1a633714c2d39c6425d3f1c14042f40be3

Observation 9ea4db15-e08d-4a15-95cb-518b36463e43 · inbound

A Survey on Data Security in Large Language Models cites this paper.

A Survey on Data Security in Large Language Models On the Risk of Misinformation Pollution with Large Language Models

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-06T05:05:02.833864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:05:02.833864Z digest=sha256:8712a79a6bf5fb839ca3075cd7ef2f80150d22f35c4b06b0b6ed2fb5c4febe7d

Observation 36163fad-1904-40fb-be2e-3beac8dea23a · inbound

An Audit and Analysis of LLM-Assisted Health Misinformation Jailbreaks Against LLMs cites this paper.

An Audit and Analysis of LLM-Assisted Health Misinformation Jailbreaks Against LLMs On the Risk of Misinformation Pollution with Large Language Models

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-06T01:02:15.400138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T01:02:15.400138Z digest=sha256:137faab02e52e5da14c788d6151d06f5d47c50d0aa1005f450f3095667ccc326

Observation 39101130-0891-47da-9435-b7e2c21d9ce1 · inbound

A Symbolic Adversarial Learning Framework for Evolving Fake News Generation and Detection cites this paper.

A Symbolic Adversarial Learning Framework for Evolving Fake News Generation and Detection On the Risk of Misinformation Pollution with Large Language Models

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-05T15:42:16.699061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:42:16.699061Z digest=sha256:1bcf4866846e6fd44d13d5266607aa6d9041d4d3251ab3eff1e262c3184abebb

Observation e8bc2aae-fe5d-44f5-973b-62393fbe13f5 · 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) On the Risk of Misinformation Pollution with Large Language Models

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-05T15:18:34.810186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:18:34.810186Z digest=sha256:4b1e7d87cf40b35334abfd20d300c0886cdeaebd1b22b2019988462d128c7e04

Observation 7111869e-e6d1-4816-a02c-187590ade5a5 · inbound

Embodied AI: Emerging Risks and Opportunities for Policy Action cites this paper.

Embodied AI: Emerging Risks and Opportunities for Policy Action On the Risk of Misinformation Pollution with Large Language Models

Reference 82

Resolution
unresolved
no resolver link, observed 2026-08-05T14:37:25.719508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:37:25.719508Z digest=sha256:4e929ed9f2f324361663fbf5f27275c0abb4e44eda1ddb0db78bd715c54fca6b

Observation b4daad6c-7921-4261-af1b-f8909e2767a6 · inbound

Detecting LLM-Generated Spam Reviews by Integrating Language Model Embeddings and Graph Neural Network cites this paper.

Detecting LLM-Generated Spam Reviews by Integrating Language Model Embeddings and Graph Neural Network On the Risk of Misinformation Pollution with Large Language Models

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-18T10:42:36.038548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-18T10:41:30.529576Z digest=sha256:a4f5a5138b363719ceddf494d6cdd070f6742ea7e71e6fd92bac2b3e42c54ba5

Observation 0dd0f213-58b3-4586-9a68-1c7c6bc25bcb · inbound

Pop Quiz Attack: Black-box Membership Inference Attacks Against Large Language Models cites this paper.

Pop Quiz Attack: Black-box Membership Inference Attacks Against Large Language Models On the Risk of Misinformation Pollution with Large Language Models

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-11T20:26:09.089251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-08T09:14:12.034025Z digest=sha256:91550adc72c60fae763a8512333b17c810ee24a196acde12fd6d9e98e826d2c7

Observation cc6b1b18-4780-49c2-919b-bbe5ade5d68e · inbound

Information Discernment in Large Language Models cites this paper.

Information Discernment in Large Language Models On the Risk of Misinformation Pollution with Large Language Models

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-02T13:26:25.863764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T13:26:25.863764Z digest=sha256:f57a276dfe76fc124355a9cd12aef0316c509c2db35c674d19f44b19162057b8