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Paper Citation Record · LEDGER

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network

As of 21 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 7 inbound Pith citation observations for arXiv:2505.05103.

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

pith.paper-citation-record.v1
2505.05103 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:19:24.762509Z

measured 59 of 59 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:16:14.678900Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T20:27:22.739239Z

Reference resolution

52 of 52 outbound references displayed

  • verified exact1
  • verified fuzzy34
  • unresolved17
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 228a0df5-6988-467f-a202-3cf8c07ced99 · outbound

This paper cites Federated large language model: Solutions, challenges and future directions,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Federated large language model: Solutions, challenges and future directions,

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-15T23:19:25.397376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 54a5adf7-7c49-470b-a2eb-c5bec9912155 · outbound

This paper cites A survey on evaluation of large language models,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network A survey on evaluation of large language models,

Reference 2

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no resolver link, observed 2026-08-15T23:19:24.538047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:19:24.538047Z digest=sha256:7234944ea836a9e54fa36d71457c54bacf023612e9f9be1b8eb4b599b320259b

Observation 993aebaa-0e53-4954-baff-48906caf1ac6 · outbound

This paper cites Chatgpt: A comprehensive review on background, applica- tions, key challenges, bias, ethics, limitations and future scope,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Chatgpt: A comprehensive review on background, applica- tions, key challenges, bias, ethics, limitations and future scope,

Reference 3

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source=pdf_text observed=2026-08-15T23:19:24.542046Z digest=sha256:f7bb0827a9ee9672ea244dfe3627acaee8ee1f6218e50ac73a56a708d80969da

Observation c36fef61-2e20-4ade-898f-9128c10ddce7 · outbound

This paper cites Large ai model empowered multimodal semantic communications,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Large ai model empowered multimodal semantic communications,

Reference 4

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source=pdf_text observed=2026-08-15T23:19:24.546120Z digest=sha256:076244ab9db6a179665ee010f26b9fa4caaaeb7d5cda12d2a874c8dd2aaaf155

Observation fd8a0fe6-82d4-415d-967a-6b10258797b1 · outbound

This paper cites Generative AI Enabled Robust Data Augmentation for Wireless Sensing in ISAC Networks.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Generative AI Enabled Robust Data Augmentation for Wireless Sensing in ISAC Networks

Reference 5

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source=pdf_text observed=2026-08-15T23:19:24.549944Z digest=sha256:5ab793dcedf42250e74f0aab54e154a6469eeed258692d03404cd629bc55cbbd

Observation 95f79a36-544c-4f24-86ef-f40f6793d605 · outbound

This paper cites Larger and more instructable language models become less reliable,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Larger and more instructable language models become less reliable,

Reference 6

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:19:24.554130Z digest=sha256:286f09615de50c2755c86c301ffaa26f581f907528babd56aa2a2f87ba5ad45d

Observation 2e9f85aa-8e50-44a0-a81a-c9edec72b5ce · outbound

This paper cites What are the best ai tools for research? nature’s guide,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network What are the best ai tools for research? nature’s guide,

Reference 7

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raw_fallback, observed 2026-08-15T23:19:25.357259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.558600Z digest=sha256:8f427009e81c8c3a4da1993a4d826257b2cabe4991759e412414589e271c8ea3

Observation 80b02171-abab-4602-85a4-490a55052de2 · outbound

This paper cites Easy2hard- bench: Standardized difficulty labels for profiling llm performance and generalization,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Easy2hard- bench: Standardized difficulty labels for profiling llm performance and generalization,

Reference 8

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raw_fallback, observed 2026-08-15T23:19:25.344231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.562447Z digest=sha256:a3be771102d988489f2b3ceac0e2875cc80ed993849425c97ef8e9d328d73e4c

Observation 11af04dc-77a0-41c9-993a-7f4c1cba9fc8 · outbound

This paper cites Merge, Ensemble, and Cooperate! A Survey on Collaborative Strategies in the Era of Large Language Models.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Merge, Ensemble, and Cooperate! A Survey on Collaborative Strategies in the Era of Large Language Models

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:19:24.566711Z digest=sha256:d19bbe9d4842ae6d237c3614accc37197767f9404acef94fa831c215a696c3d2

Observation d7fbf59c-2358-438d-9f9e-b49c67b0c347 · outbound

This paper cites A Multi-LLM Debiasing Framework.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network A Multi-LLM Debiasing Framework

Reference 10

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source=pdf_text observed=2026-08-15T23:19:24.571102Z digest=sha256:1d8c248e22665ac9117612ea5eda5a9f42f8bd4ca3b3c8334284738329463fc8

Observation f7d80ea2-bcda-46df-8b2d-e335ec5ae6ca · outbound

This paper cites Don't Hallucinate, Abstain: Identifying LLM Knowledge Gaps via Multi-LLM Collaboration.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Don't Hallucinate, Abstain: Identifying LLM Knowledge Gaps via Multi-LLM Collaboration

Reference 11

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:19:24.576708Z digest=sha256:bf7c78dd723eeb948eef1f80d6631623983203ccc2121eaa67691709554f4a3e

Observation 2213369e-bfa4-4cac-a586-05b108baa19c · outbound

This paper cites Wireless Hallucination in Generative AI-enabled Communications: Concepts, Issues, and Solutions.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Wireless Hallucination in Generative AI-enabled Communications: Concepts, Issues, and Solutions

Reference 12

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:19:24.581926Z digest=sha256:ad718e5ac966e2dfcb072f6a9a2f6c649df11741cbcb5a014bf01853561491fe

Observation 18a4ae04-a0cc-4ddc-83a4-0bbfe35eed79 · outbound

This paper cites Performance analysis on the applications of large language models: A case for elderly care,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Performance analysis on the applications of large language models: A case for elderly care,

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.586055Z digest=sha256:f0f08e72a1fecfb35fb93c6376d618c6339e57c3d764b32c0660cfa03fa4e085

Observation f624b972-bd99-4bb6-97a2-0174f24e4a5a · outbound

This paper cites A Scalable Communication Protocol for Networks of Large Language Models.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network A Scalable Communication Protocol for Networks of Large Language Models

Reference 14

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no resolver link, observed 2026-08-15T23:19:24.590095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:19:24.590095Z digest=sha256:9c6a018f08a69d525e6cd3285ea82ff73ab7935a120371192adf50568564ca6a

Observation a71d1d20-1a04-4c0d-9569-7420473797f7 · outbound

This paper cites Escm: An efficient and secure communication mechanism for uav networks,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Escm: An efficient and secure communication mechanism for uav networks,

Reference 15

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raw_fallback, observed 2026-08-15T23:19:25.318552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation c5cabe9d-d3fd-4503-bfa1-43c00b885be8 · outbound

This paper cites WormGPT: A large language model chatbot for criminals,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network WormGPT: A large language model chatbot for criminals,

Reference 16

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raw_fallback, observed 2026-08-15T23:19:25.304806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.598591Z digest=sha256:ce036848e9b60e60ef1c5568d1cff61502e69bf2fe54b7e3921b5d59b4c5bb87

Observation 6ca0e6f5-d7ca-4276-8c2c-2c37cb672ece · outbound

This paper cites Convergence of sym- biotic communications and blockchain for sustainable and trustworthy 6g wireless networks,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Convergence of sym- biotic communications and blockchain for sustainable and trustworthy 6g wireless networks,

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.602559Z digest=sha256:8bfd31b6d83cca49dba19f678151051c2d4fa355b92d7a9d8aad31020182dfb2

Observation 69c83703-e7c9-46b9-bdc0-0d63cfd90c97 · outbound

This paper cites Wireless blockchain meets 6g: The future trustworthy and ubiquitous connectivity,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Wireless blockchain meets 6g: The future trustworthy and ubiquitous connectivity,

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.606584Z digest=sha256:75d7d008f9accbab908a3fa0351972daf88daacd20dc1eec9594e7e0f765907c

Observation 001f2b49-bbae-4a8d-a1e6-d2a43342c5de · outbound

This paper cites BC4LLM: A perspective of trusted artificial intelligence when blockchain meets large language models,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network BC4LLM: A perspective of trusted artificial intelligence when blockchain meets large language models,

Reference 19

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raw_fallback, observed 2026-08-15T23:19:25.263728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.611082Z digest=sha256:cfe5e6ba71fce6326d41e3652a670f8f9b70599a02bb290799099cc52af68058

Observation 8a42e1a3-7166-437c-9072-ca448337156a · outbound

This paper cites Large Language Model Federated Learning with Blockchain and Unlearning for Cross-Organizational Collaboration.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Large Language Model Federated Learning with Blockchain and Unlearning for Cross-Organizational Collaboration

Reference 20

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local_arxiv, observed 2026-08-15T23:19:24.845743Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 1f9424a3-4875-4a02-9573-1bf251b504c8 · outbound

This paper cites Blockchain for large language model security and safety: A holistic survey,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Blockchain for large language model security and safety: A holistic survey,

Reference 21

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 7174d357-fa00-40cd-8543-d5d8a89ae247 · outbound

This paper cites Practical byzantine fault tolerance,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Practical byzantine fault tolerance,

Reference 22

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Observation 60f9d245-3f4d-4dbb-ae33-914cffe4f6b7 · outbound

This paper cites Hot- stuff: Bft consensus with linearity and responsiveness,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Hot- stuff: Bft consensus with linearity and responsiveness,

Reference 23

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source=pdf_text observed=2026-08-15T23:19:24.628770Z digest=sha256:f184514b3d288bf43e05f8c90e5651deaceb4fa4b142ae336ca23f775715e19f

Observation 55185b43-6c9a-4a57-a809-eade4e126940 · outbound

This paper cites When One LLM Drools, Multi-LLM Collaboration Rules.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network When One LLM Drools, Multi-LLM Collaboration Rules

Reference 24

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source=pdf_text observed=2026-08-15T23:19:24.633184Z digest=sha256:2e86692ac1ab4f1b77defe0a20dfe6e49f380649befcecc38337b687aba9e29b

Observation 3085f77a-ae7b-4fa2-9f36-406b18a0d8fb · outbound

This paper cites Learning to Decode Collaboratively with Multiple Language Models.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Learning to Decode Collaboratively with Multiple Language Models

Reference 25

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:19:24.639194Z digest=sha256:fe6b5821f61ca97b9e137f228571d5adad359fe08bbc52c96d386214d9a1f75e

Observation 705e7086-559e-47f5-a414-f018adec30e2 · outbound

This paper cites Knowledge Fusion of Large Language Models.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Knowledge Fusion of Large Language Models

Reference 26

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:19:24.644936Z digest=sha256:cce4b1b8f38accfc853a638787c6a96f58db065ef127720e60f26ab9475f61fd

Observation 7910a17b-628f-4c42-bf14-1b56befde252 · outbound

This paper cites Federated TrustChain: Blockchain-Enhanced LLM Training and Unlearning.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Federated TrustChain: Blockchain-Enhanced LLM Training and Unlearning

Reference 27

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:19:24.650217Z digest=sha256:5da2fb7cf6227fb7d2131fa3359ace4bbcbea89062912450168943cf320dff6f

Observation 3639e5d8-d47e-40ac-9e97-15141785a059 · outbound

This paper cites Blockagents: Towards byzantine-robust llm-based multi-agent coordination via blockchain,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Blockagents: Towards byzantine-robust llm-based multi-agent coordination via blockchain,

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-15T23:19:25.225304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.654995Z digest=sha256:f0df616b9fbcb39f4fc8aa15426ae730dbefecbcc49f127e87750fba491d20e6

Observation da713451-8ccd-4bb9-85c0-9bcee1ae5f5b · outbound

This paper cites Blockchain-empowered lifecycle management for AI- generated content products in edge networks,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Blockchain-empowered lifecycle management for AI- generated content products in edge networks,

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-15T23:19:25.213281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.659391Z digest=sha256:dc0e9e45144147586b133ef847fbfca2556525d5c7a9441607d9eed197039ca3

Observation 89a0bdc4-8c47-4bf5-86bb-0f911f83c858 · outbound

This paper cites Llmchain: Blockchain-based reputation system for sharing and evaluating large language models,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Llmchain: Blockchain-based reputation system for sharing and evaluating large language models,

Reference 30

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raw_fallback, observed 2026-08-15T23:19:25.200151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.663588Z digest=sha256:e4be6e64b77ef2efe51aea82be0948a5c0f980e10219a80e203e93eb7f13fadc

Observation da7e9d2f-e634-4a7d-ad29-f04c5150b122 · outbound

This paper cites Blockchain-based efficient and trustworthy aigc services in metaverse,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Blockchain-based efficient and trustworthy aigc services in metaverse,

Reference 31

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raw_fallback, observed 2026-08-15T23:19:25.188243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.668176Z digest=sha256:f5111e3eab865934905a1d4d307c31c6fda7458a46b3f3b9a71edbda60db54a9

Observation b109d3cb-a317-41c1-bcfa-a763b2d4f1da · outbound

This paper cites Collaborative annealing power k-means++ cluster- ing,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Collaborative annealing power k-means++ cluster- ing,

Reference 32

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raw_fallback, observed 2026-08-15T23:19:25.175844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.672331Z digest=sha256:529145b6df6d1d37684438bab472efe2442dd2370d1fae14e0281c66cfb7a750

Observation d3aea797-c633-466c-923e-438591b68324 · outbound

This paper cites Determine the number of unknown targets in open world based on elbow method,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Determine the number of unknown targets in open world based on elbow method,

Reference 33

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raw_fallback, observed 2026-08-15T23:19:25.164607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.676401Z digest=sha256:568f528b617c9a21ab6d2cd6961105b31503bdd12b2af7a964135d6270da95f7

Observation 48b9901c-1106-4e89-873d-f51ca3a492fe · outbound

This paper cites Tierflow: A pipelined layered bft consensus protocol for large-scale blockchain,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Tierflow: A pipelined layered bft consensus protocol for large-scale blockchain,

Reference 34

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raw_fallback, observed 2026-08-15T23:19:25.150837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.681095Z digest=sha256:d248c5b4f41a8b3ca0226a8c707988453e16e4add2fb91cc3be372e9a934f645

Observation 3f1c66f9-b199-4611-8884-8dfc9791e2f8 · outbound

This paper cites Blockchain-based cross- domain authentication with dynamic domain participation in iot,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Blockchain-based cross- domain authentication with dynamic domain participation in iot,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:19:25.138520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.685311Z digest=sha256:7d5aa3de4fd85e997299d83d0bcd3c2a5232e1acdcc5043f4ea85c9417ad6576

Observation 0168a5d4-ed08-4e53-ac3e-4d959a46b996 · outbound

This paper cites Esia: An efficient and stable identity authentication for internet of vehicles,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Esia: An efficient and stable identity authentication for internet of vehicles,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:19:25.126882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.689891Z digest=sha256:77c70c558487675bca9aff4ffb49a2788029865fbcfd4462d7bbbb281ea8def4

Observation dd68306e-c402-4c5d-b26d-2c65c9922c8d · outbound

This paper cites A scalable multi-layer pbft consensus for blockchain,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network A scalable multi-layer pbft consensus for blockchain,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:19:25.114190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.694311Z digest=sha256:0e5043a6aa52dfcc63dea87abc259aabe8dd20683b9ba2e6ed6b69c4e6f65601

Observation d1d52e03-3d3f-4867-ba5b-4258acbfc80d · outbound

This paper cites R ´ev´esz, The laws of large numbers.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network R ´ev´esz, The laws of large numbers

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:19:25.101722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.698504Z digest=sha256:d78c6dff2bfff4905ebf7b5fa15ac590261bc1dbcb8b47fd07e0cb739b94d64f

Observation 6ab66207-6cac-4521-a291-6f0730f95e8a · outbound

This paper cites an unresolved cited work.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Unresolved cited work

Reference 39

Resolution
unresolved
raw_fallback, observed 2026-08-15T23:19:25.091480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.702721Z digest=sha256:7acfe03a0a1764230132bc10b2ef5b6cfbd2b9d1b2d19e2ced5df8fd3fa004fc

Observation 629b3786-f142-40a0-9319-15c783097c4e · outbound

This paper cites Optimizing resource allocation in urllc for real-time wireless control systems,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Optimizing resource allocation in urllc for real-time wireless control systems,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:19:25.079519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.708291Z digest=sha256:c99423b6a303f12fa2d311dab63ddafba1807a4375eaeceee53c659b98fd14b4

Observation 6aecab22-ddb5-46e2-b64a-0e521987299b · outbound

This paper cites Low reliable and low latency communications for mission critical distributed industrial internet of things,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Low reliable and low latency communications for mission critical distributed industrial internet of things,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:19:25.068539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.714066Z digest=sha256:3d33a29581040250ba9e92778e297f51ae8ab343355cba1304f6fa8ebe9a6aa1

Observation 0619bdf6-8352-47e1-9f85-a6f9166f4a2c · outbound

This paper cites Symbiotic pbft consensus: Cognitive backscatter communications-enabled wireless pbft consensus,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Symbiotic pbft consensus: Cognitive backscatter communications-enabled wireless pbft consensus,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:19:25.056776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.718389Z digest=sha256:b7b8e2f55b5a183ece2e372d643f6b385f3dcae4df1e8773e7882a88fcddf5af

Observation 154eb06f-4228-46fe-8040-a365ea6959c6 · outbound

This paper cites A v2v empowered consensus framework for cooperative autonomous driving,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network A v2v empowered consensus framework for cooperative autonomous driving,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:19:25.044527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.722509Z digest=sha256:6fa0c97f2bb2399319a907b2de0af3e0c7814df6cca9ea405766cf8d7fbea3e3

Observation c43e4570-4244-4f4f-9650-1ded7ee0f095 · outbound

This paper cites An energy-efficient wireless blockchain sharding scheme for pbft consensus,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network An energy-efficient wireless blockchain sharding scheme for pbft consensus,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:19:25.031379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.727361Z digest=sha256:2f3339983943ba85c1c4518541539fe425963fe474f53df5bfb50188e9c8fe90

Observation b362c5d4-575b-4462-b85d-9dd55b68f6e8 · outbound

This paper cites Symbiotic blockchain consensus: Cognitive backscatter communications-enabled wireless blockchain consensus,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Symbiotic blockchain consensus: Cognitive backscatter communications-enabled wireless blockchain consensus,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:19:25.017553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.731756Z digest=sha256:5d6790888969e82e7822fc633d463754fc061f2c05f11c210622b8ca07fed418

Observation a5dc5053-d835-424f-9237-b65e64efa0cc · outbound

This paper cites Performance analysis and comparison of nonideal wireless pbft and raft consensus networks in 6g communications,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Performance analysis and comparison of nonideal wireless pbft and raft consensus networks in 6g communications,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:19:25.004675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.735939Z digest=sha256:da829f25944b40f7162e9135842ba0203e7967b41d7bdae403aeb1c22f084186

Observation 6cc0340b-7480-4fcb-911e-692aadaaa706 · outbound

This paper cites A multi- chain consensus for power big data transaction in generation-grid-load- storage integrated networks,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network A multi- chain consensus for power big data transaction in generation-grid-load- storage integrated networks,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:19:24.992312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.739712Z digest=sha256:77d5ae459febc4d1213792cbc912ba0bebf509385e90515b4fc12530eabccb2d

Observation 20b2eb1c-c84b-4bc8-9390-899aac14af67 · outbound

This paper cites V otes-as-a-Proof (VaaP): Permissioned blockchain consensus protocol made simple,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network V otes-as-a-Proof (VaaP): Permissioned blockchain consensus protocol made simple,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:19:24.978116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.744603Z digest=sha256:7cf41878bdda4f0baa14915d821a28d2018ab3e25411a1cc4841534c5eeb915a

Observation c04b81c8-656c-4ce0-8294-eba968c09198 · outbound

This paper cites An efficient consensus algorithm for blockchain-based cross-domain authentication in bandwidth-constrained wide area iot networks,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network An efficient consensus algorithm for blockchain-based cross-domain authentication in bandwidth-constrained wide area iot networks,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:19:24.965664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.748621Z digest=sha256:f8c48b12c15f635e50734a55edf092272a60f192b0102845f163745fe9481501

Observation 5cb5d241-4b04-4702-9dec-d99cd6b5c6ed · outbound

This paper cites Trusted and efficient task offloading in vehicular edge computing networks,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Trusted and efficient task offloading in vehicular edge computing networks,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:19:24.952264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.752365Z digest=sha256:a11aebcd090d9ec6d04c19db843d7a78c0a9c58d04aaea5a67d33a918ca6dbf4

Observation a9805d87-9529-489a-a58d-e6be1015fba3 · outbound

This paper cites Graph attention network-based block propagation with optimal AOB and reputation in Web 3.0,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Graph attention network-based block propagation with optimal AOB and reputation in Web 3.0,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:19:24.939573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.756848Z digest=sha256:7e279d242ae47a3871c70784f73c81fe53f972c54b15c5d765ace24e42823101

Observation 42c401ac-dbc2-4300-996e-2edf450a313e · outbound

This paper cites Abc-gspbft: Pbft with grouping score mechanism and optimized consensus process for flight operation data-sharing,.

A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network Abc-gspbft: Pbft with grouping score mechanism and optimized consensus process for flight operation data-sharing,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:19:24.926202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T23:19:24.762509Z digest=sha256:bdb2967466be6528ecd28daa12a3280829029c67de0cb35ddb01579fc11a3b9c

Pith citing papers

Observation b5bc9217-449d-49b0-bc5a-4946428c57e2 · inbound

Toward Edge General Intelligence with Multiple-Large Language Model (Multi-LLM): Architecture, Trust, and Orchestration cites this paper.

Toward Edge General Intelligence with Multiple-Large Language Model (Multi-LLM): Architecture, Trust, and Orchestration A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T21:16:14.678900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:16:14.678900Z digest=sha256:3b6733c6d0cfcca6fc32e27919a92a0d31f1485ad263c7dd6ebb4cd4d2c7b8da

Observation 52465fd6-1aa3-40bd-b50e-a748ad61f802 · inbound

Byzantine-Robust Decentralized Coordination of LLM Agents cites this paper.

Byzantine-Robust Decentralized Coordination of LLM Agents A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-06T15:50:02.733381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:50:02.733381Z digest=sha256:368ce640e9772f61d685ac421c1964535f38330ea35535084c84de2506a71349

Observation 5a0a18e5-8dc7-4f65-87ff-46ee3e5c15e5 · inbound

Toward Edge General Intelligence with Agentic AI and Agentification: Concepts, Technologies, and Future Directions cites this paper.

Toward Edge General Intelligence with Agentic AI and Agentification: Concepts, Technologies, and Future Directions A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-05T16:20:59.096939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T16:20:59.096939Z digest=sha256:5d246a154fcb5d01133d5491ee6187f253ec045ae089b89de50038f4c508e478

Observation 6cddf0e1-c2d9-4e95-88f1-bf318a6f7da7 · inbound

AI Reasoning for Wireless Communications and Networking: A Survey and Perspectives cites this paper.

AI Reasoning for Wireless Communications and Networking: A Survey and Perspectives A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-04T19:34:25.744550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:34:25.744550Z digest=sha256:2ae39386f909b4eab5e21366a483e51293ecb23577aad1534ed66c9ed0714c65

Observation 877c5b03-5b34-475e-b380-e969c96804b9 · inbound

Free-MAD: Consensus-Free Multi-Agent Debate cites this paper.

Free-MAD: Consensus-Free Multi-Agent Debate A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-04T17:15:01.873567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:15:01.873567Z digest=sha256:9acb3a8dd6f2127660c4c457e8f6d83f1a84323331ea4e3111c15fb9159de2b9

Observation de40db82-5ad3-4e5f-9a3e-c0e37e6404f7 · inbound

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures cites this paper.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network

Reference 129

Resolution
verified exact
arxiv_id, observed 2026-05-11T11:51:04.054943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-10T04:31:28.242097Z digest=sha256:a7b60c213135d168e26bb851966d76fc2061ae89660b9f3937d7eea4ccd18e0c

Observation c43486e3-95b3-4664-98fc-f05bdb55be6f · inbound

Certifiable Semantic Agreement Among LLM Agents: What the Admissibility Instrument Decides cites this paper.

Certifiable Semantic Agreement Among LLM Agents: What the Admissibility Instrument Decides A Weighted Byzantine Fault Tolerance Consensus Driven Trusted Multiple Large Language Models Network

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-07-02T20:27:22.740618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T20:21:28.237644Z digest=sha256:4b2dc362a8eb1a7b972fbe34c5c8ab9fe8c2f32a0459e1c5b4d71797a27f52c6