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Paper Citation Record · LEDGER

Decision Protocols in Multi-Agent Large Language Model Conversations

As of 12 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 0 inbound Pith citation observations for arXiv:2607.05477.

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

pith.paper-citation-record.v1
2607.05477 v1

Coverage vector

measured 61 of 61 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-11T10:52:59.410307Z

measured 61 of 61 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

61 of 61 outbound references displayed

  • verified exact3
  • verified fuzzy0
  • unresolved57
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 138dbaaa-0ebb-4b70-9fa9-50bc73337592 · outbound

This paper cites The elephant in the room: Analyzing the presence of big tech in natural language processing research,.

Decision Protocols in Multi-Agent Large Language Model Conversations The elephant in the room: Analyzing the presence of big tech in natural language processing research,

Reference 1

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Observation 25d34a01-f886-46c1-852e-7a22364c8cf4 · outbound

This paper cites The computational difficulty of manipulating an election,.

Decision Protocols in Multi-Agent Large Language Model Conversations The computational difficulty of manipulating an election,

Reference 2

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Observation 3cae7159-d2d4-4b6a-9446-f3d444261b01 · outbound

This paper cites Multi-Agent Large Language Models for Conversational Task-Solving.

Decision Protocols in Multi-Agent Large Language Model Conversations Multi-Agent Large Language Models for Conversational Task-Solving

Reference 3

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Observation 36be5089-0445-44cf-8036-402417f9f51d · outbound

This paper cites Language models are few-shot learners,.

Decision Protocols in Multi-Agent Large Language Model Conversations Language models are few-shot learners,

Reference 4

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:2a2f4eaf55e1cc7d9fea178de2a48dbf4f8f024940ebc4e13b92d8e7e3d8c5dd

Observation af3f459b-e8e9-4fd6-96ee-9f6454409628 · outbound

This paper cites Available: https : / / proceedings.

Decision Protocols in Multi-Agent Large Language Model Conversations Available: https : / / proceedings

Reference 5

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:f9be0ce7e4986eaf82913cc3ce1fe3fcb07fd51c33fdd8c288e036ac2d1420fa

Observation 7b1dae5b-0d5d-4d78-927b-aab7851dace5 · outbound

This paper cites an unresolved cited work.

Decision Protocols in Multi-Agent Large Language Model Conversations Unresolved cited work

Reference 6

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doi, observed 2026-07-11T10:57:58.369074Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation f0e897ec-60b5-443d-b9e1-2404d4a12cec · outbound

This paper cites ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs.

Decision Protocols in Multi-Agent Large Language Model Conversations ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs

Reference 7

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:eaf7735563cc137e960832c580c6c620eae2317716a70bc7ff8800420d2385ba

Observation c46b3981-4e72-4a0a-9f05-b811f97897eb · outbound

This paper cites G., Sampling techniques (Sampling techniques).

Decision Protocols in Multi-Agent Large Language Model Conversations G., Sampling techniques (Sampling techniques)

Reference 8

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Observation 2830a226-fbbd-4b53-9049-d2b79812b66d · outbound

This paper cites Social Pressure Influences Decisions of Individuals: Evidence from the Behavior of Football Referees,.

Decision Protocols in Multi-Agent Large Language Model Conversations Social Pressure Influences Decisions of Individuals: Evidence from the Behavior of Football Referees,

Reference 9

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:e29e2f4c4724b5d40da70bbe565c1b47cfb6dbd4a1845b32af33251fc4c54400

Observation 544fe79b-89c8-4419-99a7-1567173897f3 · outbound

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

Decision Protocols in Multi-Agent Large Language Model Conversations Improving Factuality and Reasoning in Language Models through Multiagent Debate

Reference 10

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:5983aea7e0a30ab20393356a3ac4294d2158f11b12b1094414f25a8239cb531b

Observation 0bf33a40-f55f-455a-8e7a-f9a26052636c · outbound

This paper cites The Llama 3 Herd of Models.

Decision Protocols in Multi-Agent Large Language Model Conversations The Llama 3 Herd of Models

Reference 11

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:d1443792e0fcbbec7b09b797c7bd499ecf71e53a78f08fd13e6ade02e370b739

Observation c35bfd5b-7bbb-42a6-b236-48debeb5d86d · outbound

This paper cites Did aristotle use a laptop? a question answering benchmark with implicit reasoning strategies,.

Decision Protocols in Multi-Agent Large Language Model Conversations Did aristotle use a laptop? a question answering benchmark with implicit reasoning strategies,

Reference 12

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:61b56e3418cd6628a399adfdfff76aa96dd1594cf578a1d9548a164f9b45ef33

Observation 6d5d71e8-88b8-4d25-ab39-ba873a5bb663 · outbound

This paper cites WORKING DOCUMENT on overcoming the deadlock of unanimity voting,.

Decision Protocols in Multi-Agent Large Language Model Conversations WORKING DOCUMENT on overcoming the deadlock of unanimity voting,

Reference 13

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:bb7837566679390743181a5c8b878e502b3ed43dc5811274ef73602b02005224

Observation 7f9a7b1b-240c-4c62-b072-2ff46b49f2c3 · outbound

This paper cites Measuring massive multitask language under- standing,.

Decision Protocols in Multi-Agent Large Language Model Conversations Measuring massive multitask language under- standing,

Reference 14

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:d0bf585a85febf7b4807cbbc30ec3d8182f59f5878fd08ff94bf925424c3c3a6

Observation e0354189-3e82-42a2-88b0-2f7c41312245 · outbound

This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

Decision Protocols in Multi-Agent Large Language Model Conversations Measuring Mathematical Problem Solving With the MATH Dataset

Reference 15

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:f4b9e5f66aabe7b9f2406edf83cea4a9bf640ce8884b6119c40d2140a9a535f9

Observation f2424485-1985-47bc-b8bb-c02d244a341e · outbound

This paper cites MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework.

Decision Protocols in Multi-Agent Large Language Model Conversations MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework

Reference 16

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:e2ed4cd153eb8b1a23fa94a6b18104e7b64a77e1bf874f4bb831bc9467f79211

Observation 971b6596-612a-4b2b-81e2-d0a7c7e0624f · outbound

This paper cites Large Language Models Cannot Self-Correct Reasoning Yet.

Decision Protocols in Multi-Agent Large Language Model Conversations Large Language Models Cannot Self-Correct Reasoning Yet

Reference 17

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:4ae1f4de5071ad170b284e0d3a10e42e07e84763fd60196e8d3e0eaced981594

Observation 8eef395b-87cf-4e92-acb3-442f74de21ed · outbound

This paper cites PersonaLLM: Investigating the ability of large language models to express personality traits,.

Decision Protocols in Multi-Agent Large Language Model Conversations PersonaLLM: Investigating the ability of large language models to express personality traits,

Reference 18

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:8db956a879fcaf02ceedce4f8191056ea586c579e857a32f92ad61e0b77ed910

Observation 626ccc4b-3ed6-45c5-b9ce-507a8a388907 · outbound

This paper cites A comparison of consensus and voting in public decision making,.

Decision Protocols in Multi-Agent Large Language Model Conversations A comparison of consensus and voting in public decision making,

Reference 19

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:82b153871c0a0d954c4465135df0def6af78fd321a8941adfa6d110d897e599c

Observation 25935f0f-c51b-49d7-a30c-0badbf0c0493 · outbound

This paper cites Persona is a Double-edged Sword: Mitigating the Negative Impact of Role-playing Prompts in Zero-shot Reasoning Tasks.

Decision Protocols in Multi-Agent Large Language Model Conversations Persona is a Double-edged Sword: Mitigating the Negative Impact of Role-playing Prompts in Zero-shot Reasoning Tasks

Reference 20

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:630e371b8781ff540caca00ee1a25fb873c2052d126ef801581297d4d43ceaba

Observation 8ad200b0-671b-475f-8a2a-85d079d84497 · outbound

This paper cites Conformity in Groups: The Effects of Others’ Views on Expressed Attitudes and Attitude Change,.

Decision Protocols in Multi-Agent Large Language Model Conversations Conformity in Groups: The Effects of Others’ Views on Expressed Attitudes and Attitude Change,

Reference 21

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:8e584d5c77cfc461255b195048f03bdf6cb5e844b578692fe2daf6e6f2e10747

Observation 9a288006-6e93-4f3f-8317-cde45ab16e1b · outbound

This paper cites The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models.

Decision Protocols in Multi-Agent Large Language Model Conversations The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models

Reference 22

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:daea71155659f796cb426a569e4546a9409431ce619f538297c322c273f8cbf1

Observation 2137dcb1-f15b-4d69-8b56-cde4ad75e9d2 · outbound

This paper cites Social Choice Theory,.

Decision Protocols in Multi-Agent Large Language Model Conversations Social Choice Theory,

Reference 23

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:f6a04447a8c4e5768defdf3ca6c65c69f54c4c599e7a0994f2be4321941f94b2

Observation 957408e8-c072-4e44-9061-bb2f70610292 · outbound

This paper cites Available: https://plato.stanford.edu/archives/win2022/entries/ social-choice/.

Decision Protocols in Multi-Agent Large Language Model Conversations Available: https://plato.stanford.edu/archives/win2022/entries/ social-choice/

Reference 24

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Observation 47b9a131-126a-4446-819c-9a81b3bb0d49 · outbound

This paper cites Green AI: Exploring Carbon Footprints, Mitigation Strategies, and Trade Offs in Large Language Model Training.

Decision Protocols in Multi-Agent Large Language Model Conversations Green AI: Exploring Carbon Footprints, Mitigation Strategies, and Trade Offs in Large Language Model Training

Reference 25

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Observation b570a0b7-732b-4dce-9c34-f8f1e94e9513 · outbound

This paper cites Self-refine: Iterative refinement with self-feedback,.

Decision Protocols in Multi-Agent Large Language Model Conversations Self-refine: Iterative refinement with self-feedback,

Reference 26

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:bbbf4f890753c23a6c3355c27f1f6c24ff08ead2bb0f6fd5bc789202cbb02c1a

Observation 3c050e97-27e2-4c09-b797-16edda3466e7 · outbound

This paper cites The effects of information and social conformity on opinion change,.

Decision Protocols in Multi-Agent Large Language Model Conversations The effects of information and social conformity on opinion change,

Reference 27

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correction dated 2020-03-18. Source: crossref record 10.1371/journal.pone.0230728->10.1371/journal.pone.0196600:correction, observed 2026-07-11T03:00:22.064553+00:00. This notice travels one citation hop only.

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Observation 05d72693-4409-4b76-99d2-171e444020e4 · outbound

This paper cites The Society of Mind,.

Decision Protocols in Multi-Agent Large Language Model Conversations The Society of Mind,

Reference 28

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:bfe7f88e369217169b97f1b0f934988f037fc4b28a4c2cf12df975d100fef1c8

Observation a4b2d98a-13b0-4feb-ad78-6ba27c259849 · outbound

This paper cites A Comprehensive Overview of Large Language Models.

Decision Protocols in Multi-Agent Large Language Model Conversations A Comprehensive Overview of Large Language Models

Reference 29

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:6e5b10ea9a217b6e51805027a0dedb18fa81914541a7b073021e23a74418a619

Observation 0900cacb-8242-4b06-86f6-aeaf8881fc61 · outbound

This paper cites GPT-4 Technical Report.

Decision Protocols in Multi-Agent Large Language Model Conversations GPT-4 Technical Report

Reference 30

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:a30bc1112a50d32763df509cb5acb587b5fb6698847403e40b1bb167dee4a37e

Observation f9f224a3-092d-413f-a796-7b361e513cc1 · outbound

This paper cites Know what you don’t know: Unanswerable questions for SQuAD,.

Decision Protocols in Multi-Agent Large Language Model Conversations Know what you don’t know: Unanswerable questions for SQuAD,

Reference 31

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:86e670ecd9da3cb541ac6c75f517e677be5e8400cd1227f23ccd36389e0d954c

Observation 14a9c95e-d9f7-4359-b1ea-9cab452a3356 · outbound

This paper cites Reporting score distributions makes a difference: Performance study of LSTM-networks for sequence tagging,.

Decision Protocols in Multi-Agent Large Language Model Conversations Reporting score distributions makes a difference: Performance study of LSTM-networks for sequence tagging,

Reference 32

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:63ecf7e3c0ce3d63d2c59cc59f1d6b7737cdcca49e01a8cd794327ca351f8bc2

Observation b4ca6938-3cd4-4ee0-b785-487543736551 · outbound

This paper cites Sentence-BERT: Sentence embeddings using Siamese BERT- networks,.

Decision Protocols in Multi-Agent Large Language Model Conversations Sentence-BERT: Sentence embeddings using Siamese BERT- networks,

Reference 33

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:6e3b5c7a0d348dfa730079ea0cf0e7b4d767d0a508837b4054111deb9ec32e8e

Observation 950460d2-69af-4fe3-85bc-867d22b034a5 · outbound

This paper cites GPQA: A Graduate-Level Google-Proof Q&A Benchmark.

Decision Protocols in Multi-Agent Large Language Model Conversations GPQA: A Graduate-Level Google-Proof Q&A Benchmark

Reference 34

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:8841a8f3f9f2379003b6ba81dba5668bf3e3934384971097bb03cdac1425d449

Observation 9ad1f356-dbdf-4d29-a800-1520479f6057 · outbound

This paper cites P., Zhou, Y., et al., PersonaGym: Evaluating Persona Agents and LLMs ,.

Decision Protocols in Multi-Agent Large Language Model Conversations P., Zhou, Y., et al., PersonaGym: Evaluating Persona Agents and LLMs ,

Reference 35

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:c77a87c61d517f0135d6f11a681ed3c3f15129f051ab4d00c199100d8fa5e7b8

Observation 3a76ebdc-bfaf-41b6-9fc8-55aa97ebb9a4 · outbound

This paper cites PersonaGym: Evaluating Persona Agents and LLMs.

Decision Protocols in Multi-Agent Large Language Model Conversations PersonaGym: Evaluating Persona Agents and LLMs

Reference 36

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:46d235d36a37bce292274e44233531e61b5cba5b8995d8d637db7e094b2064ef

Observation 337f106a-26db-489b-b9b6-e557fa6dc052 · outbound

This paper cites Towards Understanding Sycophancy in Language Models.

Decision Protocols in Multi-Agent Large Language Model Conversations Towards Understanding Sycophancy in Language Models

Reference 37

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:f3d3d3767a02517519d432ef9fc69e8cfa29a467a53116c5fcdfa038651fc5f9

Observation bd12a692-b356-4052-badc-7b97fe338872 · outbound

This paper cites Large language models can be easily distracted by irrelevant context,.

Decision Protocols in Multi-Agent Large Language Model Conversations Large language models can be easily distracted by irrelevant context,

Reference 38

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:04e0de4bdb35be5a80012eb043ec1551e0ad0094d7d9aa12be98a07dbf912c08

Observation 6b706f26-fad3-4a66-b240-656d82ebcf35 · outbound

This paper cites Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters.

Decision Protocols in Multi-Agent Large Language Model Conversations Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Reference 39

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:4a95db7d3ab374441515f76831d98a168deaf011387f053e96a32d3b82675147

Observation f06e78ac-9e95-43b1-b3b0-bcc57de3e20d · outbound

This paper cites MuSR: Testing the Limits of Chain-of-thought with Multistep Soft Reasoning.

Decision Protocols in Multi-Agent Large Language Model Conversations MuSR: Testing the Limits of Chain-of-thought with Multistep Soft Reasoning

Reference 40

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:96c0965f126186fe2c4eeb5dcb697a44eea17d2a9e7f546c7794bb8737633339

Observation e467ab20-ac03-4074-a1d8-7d5be0e62563 · outbound

This paper cites The future of ai development.

Decision Protocols in Multi-Agent Large Language Model Conversations The future of ai development

Reference 41

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:b263129d0c75ba44279203a4e93522265da397fae162a51950989b6155f87752

Observation 42e86e27-3764-45db-a572-722ae107be2f · outbound

This paper cites [Online].

Decision Protocols in Multi-Agent Large Language Model Conversations [Online]

Reference 42

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:62854a8dc429aa3deb8546c9d1bfa41a4809dabdd4f0585a151888fb44a1dffd

Observation 0830db47-2b7f-49ac-93ee-ba1c32d1de96 · outbound

This paper cites K., Sampling (Wiley series in probability and statistics), 3rd ed.

Decision Protocols in Multi-Agent Large Language Model Conversations K., Sampling (Wiley series in probability and statistics), 3rd ed

Reference 43

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:13fc3e4f530c2debf57342b956f1e42482e114235d2ddfb4bbf334362e2a46d2

Observation f93f89a1-d80c-4ac9-98ed-c03e91f73307 · outbound

This paper cites Are Neural Language Models Good Plagiarists? A Benchmark for Neural Paraphrase Detection,.

Decision Protocols in Multi-Agent Large Language Model Conversations Are Neural Language Models Good Plagiarists? A Benchmark for Neural Paraphrase Detection,

Reference 44

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:e0c78e3372d72dc4ed6329e48424dc2875d05606c65c21362311295bace85e3b

Observation f139e863-c93c-42b4-9f8d-a1669a699bf3 · outbound

This paper cites Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key?.

Decision Protocols in Multi-Agent Large Language Model Conversations Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key?

Reference 45

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:24521e0de8d407a97643afa68dfe7db0aeabb50a82ac09496c9e855d1ab27347

Observation ef864a8b-9f0a-4d2b-9c28-b3655849fa67 · outbound

This paper cites Self-consistency improves chain of thought reasoning in language models,.

Decision Protocols in Multi-Agent Large Language Model Conversations Self-consistency improves chain of thought reasoning in language models,

Reference 46

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:91ee7ad8b1781151ced20ce9aea1a96b2235ad130a103db6d3ca76b6d2438348

Observation 68fd3ed2-88ab-4472-96f1-e89d769baa5b · outbound

This paper cites MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark.

Decision Protocols in Multi-Agent Large Language Model Conversations MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark

Reference 47

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:4fa874c49ec19fb3a87346a8121913677437b344780f6b3f30c1472cdf4fc0d6

Observation f33ec06c-4183-4d55-ad00-aecb6c0b6791 · outbound

This paper cites Unleashing the emergent cognitive syn- ergy in large language models: A task-solving agent through multi-persona self-collaboration,.

Decision Protocols in Multi-Agent Large Language Model Conversations Unleashing the emergent cognitive syn- ergy in large language models: A task-solving agent through multi-persona self-collaboration,

Reference 48

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:45bc778c62443c58331b25945a6c44864eaeb06153c48774b0e47ffd3c7ce404

Observation 6bc33608-d43f-4f58-a2cd-9f4bf93bd394 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models,.

Decision Protocols in Multi-Agent Large Language Model Conversations Chain-of-thought prompting elicits reasoning in large language models,

Reference 49

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:20140ac9e99f3d21c6a06e334cf47d6e3790ebe15e49fb4bf9a21a4d08d22a02

Observation 45d48394-2ce3-4bd5-9300-5b569facd1df · outbound

This paper cites System 2 thinking in OpenAI's o1-preview model: Near-perfect performance on a mathematics exam.

Decision Protocols in Multi-Agent Large Language Model Conversations System 2 thinking in OpenAI's o1-preview model: Near-perfect performance on a mathematics exam

Reference 50

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:4835a4c5c7143c02d7a81efff85cd96294f19b04456c93a76ee21cf4eaca1947

Observation 8f1b8b54-4ffc-4aa4-ab65-ec339d59c128 · outbound

This paper cites AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation.

Decision Protocols in Multi-Agent Large Language Model Conversations AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 51

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:f8b175c63029466ce0d56cb6a56de85313e46608d09c025e31465c131fbbb27f

Observation e7df11a0-041c-4552-943e-14ff7ca2d251 · outbound

This paper cites Qwen2 Technical Report.

Decision Protocols in Multi-Agent Large Language Model Conversations Qwen2 Technical Report

Reference 52

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:f495866f0f55d331a7c5e243d2335c91866c8522c9057398d4c177184380b895

Observation 1de8b833-6476-47c1-80c1-0eaca50c7066 · outbound

This paper cites Can We Trust LLMs? Mitigate Overconfidence Bias in LLMs through Knowledge Transfer.

Decision Protocols in Multi-Agent Large Language Model Conversations Can We Trust LLMs? Mitigate Overconfidence Bias in LLMs through Knowledge Transfer

Reference 53

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:064ce839128fec915c2b93857f2af349bf5e12123a36851c0a223dd6984dd027

Observation fc4faac9-8966-40e3-9bfc-0eae5dc901de · outbound

This paper cites LLM Voting: Human Choices and AI Collective Decision Making.

Decision Protocols in Multi-Agent Large Language Model Conversations LLM Voting: Human Choices and AI Collective Decision Making

Reference 54

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:436f5ccd98d1a6b36c21ad8a5f11cbb551b57160cde529fb9c54b66d31bd93c9

Observation 15ecd5e7-5bc7-4810-a823-22c7098952ff · outbound

This paper cites Exchange-of-thought: Enhancing large language model capabilities through cross-model communication,.

Decision Protocols in Multi-Agent Large Language Model Conversations Exchange-of-thought: Enhancing large language model capabilities through cross-model communication,

Reference 55

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:0d8023d4cd39821d3344568d2f0c1c0f3b4df0d7ea3066b4123fc6612b31c8a9

Observation f8649dfa-c345-43d4-ab66-4608aeb170cc · outbound

This paper cites Judging llm-as-a-judge with mt-bench and chat- bot arena,.

Decision Protocols in Multi-Agent Large Language Model Conversations Judging llm-as-a-judge with mt-bench and chat- bot arena,

Reference 56

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:79f07a6e7dc9935bb45a5f4970cd029328df81a4882e2638fd627d35e182573e

Observation 7474d135-bfd3-4aff-83f3-bf9de738c6f8 · outbound

This paper cites [Online].

Decision Protocols in Multi-Agent Large Language Model Conversations [Online]

Reference 57

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:b7b736f915d468e6c8b7c25936e5fe33f8a431689b66cfd733f31d24b5eba2cd

Observation 318eda41-66cb-42ea-bb5f-f97354fbbb6d · outbound

This paper cites https://api.openai.com/v1.

Decision Protocols in Multi-Agent Large Language Model Conversations https://api.openai.com/v1

Reference 58

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:e6637cb53bcf168d0a3f01cb5b722244b291097c551a1e0f671760114e06e85c

Observation 4376b483-e6fc-4b06-a63f-c119c16c0a4f · outbound

This paper cites an unresolved cited work.

Decision Protocols in Multi-Agent Large Language Model Conversations Unresolved cited work

Reference 59

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:172f51aadb0f0dd817b13a5a00810d3b96d00b807db3669680a731082975205f

Observation 78c8f7fa-d7df-4b93-bfd3-498a6cb5ba90 · outbound

This paper cites an unresolved cited work.

Decision Protocols in Multi-Agent Large Language Model Conversations Unresolved cited work

Reference 60

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:afdb1db1ff96fd2b2b533e74c8a0b9c62a48c6e5910c8dfb1dad996d5aef77d0

Observation 66878b51-4945-4f94-be74-59abdd4930f7 · outbound

This paper cites an unresolved cited work.

Decision Protocols in Multi-Agent Large Language Model Conversations Unresolved cited work

Reference 61

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source=pdf_text observed=2026-07-11T10:52:59.410307Z digest=sha256:ee01f9a2434e25079839faab265b88f1427fa5a36e58421208e0df67e32c145f

Pith citing papers

No inbound Pith citation observations are available.