Paper Citation Record · LEDGER

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution

As of 15 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2605.30802.

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

pith.paper-citation-record.v1
2605.30802 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T20:59:43.961420Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

46 of 46 outbound references displayed

verified exact5
verified fuzzy0
unresolved40
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 51ea1c1d-b561-460b-aee2-2b89cd99158d · outbound

This paper cites The promise of prediction markets.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution The promise of prediction markets

Reference 1

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Source-reported events for the cited work

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Observation 97dab8a6-a4b8-49a5-b8d9-b627c3c7656c · outbound

This paper cites Prediction market accuracy in the long run.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Prediction market accuracy in the long run

Reference 2

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Observation 96e7e660-346d-40ca-a965-71e3cd2c2b01 · outbound

This paper cites https://www.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution https://www

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-28T20:59:43.961420Z

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Observation 4d84e94e-c7da-4bc0-afbb-cabafb5fb2d2 · outbound

This paper cites Understanding the blockchain oracle problem: A call for action.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Understanding the blockchain oracle problem: A call for action

Reference 4

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Observation 92d580cd-af0b-4c79-8c23-276c68422378 · outbound

This paper cites an unresolved cited work.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Unresolved cited work

Reference 5

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Observation c831bb2a-7a85-44cb-a54d-185774584a7e · outbound

This paper cites https://research.chain.link/whitepaper-v2.pdf.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution https://research.chain.link/whitepaper-v2.pdf

Reference 6

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Observation 9bdd1c3c-39aa-4064-b141-b22dc6269971 · outbound

This paper cites an unresolved cited work.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Unresolved cited work

Reference 7

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Observation 2fc07c7e-750a-4024-82d1-e11c759fbf90 · outbound

This paper cites https://help.kalshi.com/markets/markets-101/market-outcomes.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution https://help.kalshi.com/markets/markets-101/market-outcomes

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-28T20:59:43.961420Z

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Observation 6193f200-b605-445e-9e95-7244f5d734de · outbound

This paper cites https://blog.chain.link/ai-oracles/.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution https://blog.chain.link/ai-oracles/

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-28T20:59:43.961420Z

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Unavailable: canonical work link unavailable.

Observation 256e9b97-1efa-4b15-a3a8-d92330736775 · outbound

This paper cites https : / / blog.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution https : / / blog

Reference 10

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Observation dbe96fb3-cf0f-4f13-a4ac-9e24e2f22c21 · outbound

This paper cites Correlated Errors in Large Language Models.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Correlated Errors in Large Language Models

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-07-01T20:36:11.302923Z

Source-reported events for the cited work

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Observation e5c03a0a-efc0-4285-bd05-0c54a7d98051 · outbound

This paper cites Do large language models know what they don’t know?.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Do large language models know what they don’t know?

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-07-01T20:36:11.299467Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 99c930cb-1714-4cfe-a566-96ee0df3e79f · outbound

This paper cites The use of knowledge in society.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution The use of knowledge in society

Reference 13

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Observation 71acf922-5b6d-41b3-8d94-ffa5daf294dd · outbound

This paper cites A meta-analysis of prediction markets accuracy.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution A meta-analysis of prediction markets accuracy

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-28T20:59:43.961420Z

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Observation d5668e1d-92c7-4628-a6b7-cc8a35b3942c · outbound

This paper cites Chainalysis Blog.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Chainalysis Blog

Reference 15

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Observation 3303e6dd-018e-49f4-8cda-8d1c0b1e5a10 · outbound

This paper cites A primer on oracle economics.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution A primer on oracle economics

Reference 16

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Observation b6ca2ad2-38ea-429f-8f27-f7d40ce30610 · outbound

This paper cites https://github.com/Polymarket/uma-ctf-adapter.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution https://github.com/Polymarket/uma-ctf-adapter

Reference 17

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Observation 20b0e75b-8bbe-4e29-99e1-b5f50472de08 · outbound

This paper cites FEVER: A large-scale dataset for fact extraction and verification.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution FEVER: A large-scale dataset for fact extraction and verification

Reference 18

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Observation f85b6769-3f5a-42fb-9d3a-20d1a402ce92 · outbound

This paper cites Survey of hallucination in natural language generation.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Survey of hallucination in natural language generation

Reference 19

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Observation e91c6a9f-d9b0-4c22-be1d-66415ca3b102 · outbound

This paper cites A survey on hallucination in large language models: Principles, taxonomy, chal- lenges, and open questions.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution A survey on hallucination in large language models: Principles, taxonomy, chal- lenges, and open questions

Reference 20

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Observation 8bc7c75d-f91e-42ce-b70e-3c141f2bbedb · outbound

This paper cites Sycophancy in LLMs: Causes, consequences, and mitigation strategies.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Sycophancy in LLMs: Causes, consequences, and mitigation strategies

Reference 21

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Unavailable: canonical work link unavailable.

Observation e11c3170-14d4-4539-aaa2-f1e938e12929 · outbound

This paper cites On optimum recognition error and reject tradeoff.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution On optimum recognition error and reject tradeoff

Reference 22

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Unavailable: canonical work link unavailable.

Observation ba37a97d-6b9c-4f2a-8802-f4f413f0eefd · outbound

This paper cites Selective classification for deep neural networks.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Selective classification for deep neural networks

Reference 23

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Observation 81c6f9b6-dd35-4c03-b10e-fcb4e8b7f723 · outbound

This paper cites Refining LLM outputs with itera- tive consensus ensemble (ICE).

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Refining LLM outputs with itera- tive consensus ensemble (ICE)

Reference 24

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Observation 055131ef-23f2-4e3a-8273-00d393bc6f5d · outbound

This paper cites Improving Factuality and Reasoning in Language Models through Multiagent Debate.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Improving Factuality and Reasoning in Language Models through Multiagent Debate

Reference 25

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Source-reported events for the cited work

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Observation 5fdd0219-d849-4632-a671-8225149acef9 · outbound

This paper cites Consistent Estimators for Learning to Defer to an Expert.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Consistent Estimators for Learning to Defer to an Expert

Reference 26

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Observation 55215593-01c3-4422-827a-05da96461477 · outbound

This paper cites Trust or Escalate: LLM Judges with Provable Guarantees for Human Agreement.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Trust or Escalate: LLM Judges with Provable Guarantees for Human Agreement

Reference 27

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Unavailable: canonical work link unavailable.

Observation 2e75ad24-38be-4a01-8636-7f885e3af26e · outbound

This paper cites On the Tyranny of the Majority: How multi-agent debate can im- prove upon majority voting.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution On the Tyranny of the Majority: How multi-agent debate can im- prove upon majority voting

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-28T20:59:43.961420Z

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Observation c76b4f53-1036-4d4f-b1a9-e62cadfc26f0 · outbound

This paper cites Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5bbcc5d9-92ea-44ef-8c1f-a75b59560999 · outbound

This paper cites Why Do Multi-Agent LLM Systems Fail?.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Why Do Multi-Agent LLM Systems Fail?

Reference 30

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 59a4c7f5-28ec-4b38-afcf-90cb83308083 · outbound

This paper cites Princeton University Press, 2011.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Princeton University Press, 2011

Reference 31

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Observation ebd238b0-0b69-42a0-93a1-10ee630e37cd · outbound

This paper cites Generative monoculture in large language models.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Generative monoculture in large language models

Reference 32

Resolution: unresolved; no resolver link, observed 2026-06-28T20:59:43.961420Z

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Observation 114fc5b5-3c42-4050-8c08-a0f2c2b9560e · outbound

This paper cites Measuring and addressing systematic bias in LLM decision-making.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Measuring and addressing systematic bias in LLM decision-making

Reference 33

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Observation ca4e7155-03e7-4a18-9b06-980130550f84 · outbound

This paper cites Does the whole exceed its parts? The effect of AI explanations on comple- mentary team performance.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Does the whole exceed its parts? The effect of AI explanations on comple- mentary team performance

Reference 34

Resolution: unresolved; no resolver link, observed 2026-06-28T20:59:43.961420Z

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Observation a462e1f9-9864-4282-a307-97643bdacb2a · outbound

This paper cites Towards a cascaded LLM framework for cost-effective human-AI decision-making.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Towards a cascaded LLM framework for cost-effective human-AI decision-making

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-07-01T20:36:11.297537Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7362ca04-f20f-4f6e-a470-3ba8a7f64aee · outbound

This paper cites Prioritize information describing outcomes that have already occurred.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Prioritize information describing outcomes that have already occurred

Reference 38

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Observation 526745a4-5489-4682-9f56-037688841426 · outbound

This paper cites an unresolved cited work.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Unresolved cited work

Reference 40

Resolution: unresolved; no resolver link, observed 2026-06-28T20:59:43.961420Z

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Observation f50d2c38-e66d-4de1-9fc4-eb8e8ce4fda5 · outbound

This paper cites an unresolved cited work.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Unresolved cited work

Reference 41

Resolution: unresolved; no resolver link, observed 2026-06-28T20:59:43.961420Z

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Observation 2a64e4c2-d1b8-4066-bd6f-b03f2bfca917 · outbound

This paper cites an unresolved cited work.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Unresolved cited work

Reference 42

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Observation 0b7352cc-e586-43b4-8954-6ef016c4c942 · outbound

This paper cites You should prioritize information that describes an outcome that happened.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution You should prioritize information that describes an outcome that happened

Reference 43

Resolution: unresolved; no resolver link, observed 2026-06-28T20:59:43.961420Z

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Observation 2562c239-beb5-41ec-bb67-fc34bb95546d · outbound

This paper cites an unresolved cited work.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Unresolved cited work

Reference 44

Resolution: unresolved; no resolver link, observed 2026-06-28T20:59:43.961420Z

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Observation 4f15ed27-4444-48cb-9bb8-96cacc71dda2 · outbound

This paper cites Each agent independently resolves the market using a shared evidence packet and outputs a structured JSON decision, confidence score, and evidence-grounded reasoning.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Each agent independently resolves the market using a shared evidence packet and outputs a structured JSON decision, confidence score, and evidence-grounded reasoning

Reference 45

Resolution: unresolved; no resolver link, observed 2026-06-28T20:59:43.961420Z

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Observation c46b4446-685d-4b25-a4b8-a3e711f68a99 · outbound

This paper cites an unresolved cited work.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Unresolved cited work

Reference 46

Resolution: unresolved; no resolver link, observed 2026-06-28T20:59:43.961420Z

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Observation 552e69e5-18ea-4d01-9218-4fd434404053 · outbound

This paper cites an unresolved cited work.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Unresolved cited work

Reference 47

Resolution: unresolved; no resolver link, observed 2026-06-28T20:59:43.961420Z

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Observation 271108c3-e751-42eb-885a-0fe84cdfb9b1 · outbound

This paper cites an unresolved cited work.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution Unresolved cited work

Reference 48

Resolution: unresolved; no resolver link, observed 2026-06-28T20:59:43.961420Z

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Unavailable: canonical work link unavailable.

Observation 5bf53fb7-eb9d-4eb0-9414-d17681737535 · outbound

This paper cites A” and “B.

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution A” and “B

Reference 49

Resolution: unresolved; no resolver link, observed 2026-06-28T20:59:43.961420Z

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Pith citing papers

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