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Paper Citation Record · LEDGER

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization

As of 9 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 1 inbound Pith citation observation for arXiv:2505.17115.

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

pith.paper-citation-record.v1
2505.17115 v2

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:18:06.711688Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-12T01:06:18.691416Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

50 of 50 outbound references displayed

  • verified exact0
  • verified fuzzy24
  • unresolved25
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b4f07a92-7161-4598-9069-4bab8c1e327c · outbound

This paper cites an unresolved cited work.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Unresolved cited work

Reference 1

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unresolved
raw_fallback, observed 2026-08-07T15:18:12.587904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:17:59.306161Z digest=sha256:03e8b9ac2b9e7e93cea52e1ab87d3f23e02f1a0951facdfa530ca26f99765437

Observation 8442c69b-790e-4886-b551-f47c0c851abf · outbound

This paper cites Number 1.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Number 1

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:18:12.411262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:17:59.389139Z digest=sha256:4b20c744f26f6ff53de427c81ff9cfe9d10d1e1d55d587815ac53581ec58249c

Observation bf30b820-08f1-49e4-af47-ef24f6686378 · outbound

This paper cites Chateval: Towards better llm-based evaluators through multi-agent debate.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Chateval: Towards better llm-based evaluators through multi-agent debate

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-07T15:18:12.284242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:17:59.490588Z digest=sha256:e8fedb43cce3d612a477d93e65fbe68a78fcddf58809e1171c568bd1dba0964b

Observation 2b5a631c-c549-472e-a7d4-6acb9994fcca · outbound

This paper cites Comm: Collaborative multi-agent, multi-reasoning- path prompting for complex problem solving.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Comm: Collaborative multi-agent, multi-reasoning- path prompting for complex problem solving

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:18:12.166971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:17:59.618100Z digest=sha256:9eea6dfe484a9a6a63d07cf430ebde7269496325d20a8378fda60aa910cf033c

Observation e4e9f0f9-33ff-4edf-8d5d-94576a18b91d · outbound

This paper cites Agentverse: Facilitating multi-agent collaboration and exploring emergent behaviors.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Agentverse: Facilitating multi-agent collaboration and exploring emergent behaviors

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:18:12.012327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:17:59.740877Z digest=sha256:668a902ef502fe30fcf77712fe9a08095e7b52edc86665dd3fc697465cd35aca

Observation 29f9578b-b0fd-4226-b09d-77493b4efcda · outbound

This paper cites an unresolved cited work.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-07T15:18:11.882279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:17:59.849265Z digest=sha256:ce106f210c60050d625b8efec09f23dd00b29b7414e1bce5400d7f1230d1a347

Observation 682eb61b-ec2e-4ea0-b123-10e248f9fa1e · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Training Verifiers to Solve Math Word Problems

Reference 7

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no resolver link, observed 2026-08-07T15:17:59.944895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:17:59.944895Z digest=sha256:738744acc6a77fdac54d8989900319fa4200170765c0852443d8b3edc1620df1

Observation 2f77ed75-18c9-4f1d-94f1-fdd93b648823 · outbound

This paper cites an unresolved cited work.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-08-07T15:18:11.729135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:18:00.047366Z digest=sha256:e948bc4f58a8857f94b00af3c2b1eba1a7edbd79ea48afcdf3e23cc84a5e6cf0

Observation c2865953-f2ac-4e19-9560-e4062798fe12 · outbound

This paper cites Ant colony optimization.IEEE computa- tional intelligence magazine, 1(4):28–39, 2007.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Ant colony optimization.IEEE computa- tional intelligence magazine, 1(4):28–39, 2007

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:18:11.562227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:18:00.156671Z digest=sha256:aa49b68c706acdbe47c483a0ff9560d46aaacfbcd65d0c4ce67fa8a45b21b95c

Observation 3abe09ad-080b-40bc-bd64-529a74e8b348 · outbound

This paper cites Improv- ing factuality and reasoning in language models through multiagent debate.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Improv- ing factuality and reasoning in language models through multiagent debate

Reference 10

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no resolver link, observed 2026-08-07T15:18:00.232569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:18:00.232569Z digest=sha256:7074c1e22f1bafeddb5a153a183f3404b1e5d8ffd88e595441e0a0cec4d013b1

Observation 7f0b23f3-9202-452c-b2ea-8f9e4c9bb607 · outbound

This paper cites Large language model based multi-agents: a survey of progress and challenges.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Large language model based multi-agents: a survey of progress and challenges

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:18:11.456539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:18:00.316759Z digest=sha256:0bb1aa8586f5235840dcb014649702c69f1bf90c0e2ceebd81cc308c61ace664

Observation e703bc5d-3243-49fe-9dc1-d391added39d · outbound

This paper cites Improving LLM Reasoning with Multi-Agent Tree-of-Thought Validator Agent.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Improving LLM Reasoning with Multi-Agent Tree-of-Thought Validator Agent

Reference 12

Resolution
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no resolver link, observed 2026-08-07T15:18:00.421985Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:18:00.421985Z digest=sha256:bd5eefc999ec2defaabc9fe8100cf307316d1dbbdc337262c9c100f1d7104369

Observation 93ae4940-8bfa-4bb2-b9aa-ab0aff10ca26 · outbound

This paper cites LLM Multi-Agent Systems: Challenges and Open Problems.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization LLM Multi-Agent Systems: Challenges and Open Problems

Reference 13

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no resolver link, observed 2026-08-07T15:18:00.548391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:18:00.548391Z digest=sha256:74dfd325b35de43f891cf19a5b0f37fc7ee028885a88f6ab9e5747127ae4d1a5

Observation a0a2fa90-aaa4-4e04-ade0-e1686666d891 · outbound

This paper cites Measuring massive multitask language understanding.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Measuring massive multitask language understanding

Reference 14

Resolution
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no resolver link, observed 2026-08-07T15:18:00.654337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:18:00.654337Z digest=sha256:4816ecffc74414144f8219f974fbafee2d2af1c9ba2c9f3ddb1d7cc7bc520f31

Observation f0dbdb0e-fb3e-4919-bada-e4f05f31b69f · outbound

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

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Measuring Mathematical Problem Solving With the MATH Dataset

Reference 15

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no resolver link, observed 2026-08-07T15:18:00.772200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:18:00.772200Z digest=sha256:8282ced74b5070594ba85958192937432b486f62626ce18d52e26ed2430fa30e

Observation 14a22005-2ef2-4762-b578-16544ab04e10 · outbound

This paper cites Genetic algorithms.Scientific american, 267(1):66–73, 1992.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Genetic algorithms.Scientific american, 267(1):66–73, 1992

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:18:11.295143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:18:00.897715Z digest=sha256:2a8c18e9eb0e1e8b4f5f4b058fe5a2debaec1e4138c299bd7c2c99f510e8ddb0

Observation bd6df1f3-d2bb-4c1d-a353-9f11e5ce2c7f · outbound

This paper cites Metagpt: Meta programming for a multi-agent collaborative framework.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Metagpt: Meta programming for a multi-agent collaborative framework

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:18:11.158303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:18:01.038988Z digest=sha256:f4a77566fe17b468d0c7006848b53cd129ab3d901c4536af1ed5c1c4519581db

Observation 68322d42-1ff4-4d27-a4d0-68b9c5e73c1e · outbound

This paper cites Optimizing niche center for multimodal optimization problems.IEEE Transactions on Cybernetics, 53(4):2544–2557, 2023.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Optimizing niche center for multimodal optimization problems.IEEE Transactions on Cybernetics, 53(4):2544–2557, 2023

Reference 18

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verified fuzzy
raw_fallback, observed 2026-08-07T15:18:11.007115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:18:01.147796Z digest=sha256:9e840d8a1fc1b2ca277ae7834ec8d5a8a08d01bcf36748e0f6ce36487c739f8f

Observation 67f09b78-f449-4551-a861-d38cd1ba4012 · outbound

This paper cites Particle swarm optimization.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Particle swarm optimization

Reference 19

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no resolver link, observed 2026-08-07T15:18:01.271551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:18:01.271551Z digest=sha256:9e8f4943822e3e16a65c02456a31450c623817687c6cc4c1a0bae0638ee594c4

Observation 8b70e066-528f-4c58-9838-81465eab25cd · outbound

This paper cites Large language models are zero-shot reasoners.Advances in neural information processing systems, 35:22199–22213, 2022.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Large language models are zero-shot reasoners.Advances in neural information processing systems, 35:22199–22213, 2022

Reference 20

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no resolver link, observed 2026-08-07T15:18:01.368878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:18:01.368878Z digest=sha256:f4ea70620fbdab0540a42fee49022ce751d37bb99a9d735be37041792d4fc9b0

Observation c220b015-6c4b-44d3-9dc4-3cdba628a9fe · outbound

This paper cites Camel: Communicative agents for" mind" exploration of large language model society.Advances in Neural Information Processing Systems, 36:51991–52008, 2023.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Camel: Communicative agents for" mind" exploration of large language model society.Advances in Neural Information Processing Systems, 36:51991–52008, 2023

Reference 21

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no resolver link, observed 2026-08-07T15:18:01.485789Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:18:01.485789Z digest=sha256:b6f8d270811508cd225a5b22f5a4561b541236a82509016e0a48a74d7a43f995

Observation 60cf0203-62c7-4ebf-b474-a7567a99285f · outbound

This paper cites Encouraging divergent thinking in large language models through multi- agent debate.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Encouraging divergent thinking in large language models through multi- agent debate

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:18:10.867270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:18:01.566977Z digest=sha256:5267067553d71de0035d31d1c443765020a615406e1a01c4ea7efe252407cceb

Observation a0a31374-71dd-4db1-9bc8-6ca064a236bc · outbound

This paper cites Let’s verify step by step.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Let’s verify step by step

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T15:18:01.685130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:18:01.685130Z digest=sha256:0c327287e2bfc14bd31aa3972c7994a40c825cbb0ab846e4c0cfc1deadd61231

Observation d0bbd154-91c7-4785-889d-1b666c9c29ff · outbound

This paper cites Differential evolution for multimodal optimization with species by nearest-better clustering.IEEE Transactions on Cybernetics, 51(2):970–983, 2021.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Differential evolution for multimodal optimization with species by nearest-better clustering.IEEE Transactions on Cybernetics, 51(2):970–983, 2021

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-07T15:18:10.754480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:18:01.772518Z digest=sha256:b50e9de61a58f46a9e20df7668fe7201a9e6ff0ef86c87323e49c559cdb2f01c

Observation 544f46c5-e9b0-4b28-8113-2ef82bcb98f7 · outbound

This paper cites Are Your LLMs Capable of Stable Reasoning?.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Are Your LLMs Capable of Stable Reasoning?

Reference 25

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no resolver link, observed 2026-08-07T15:18:01.927634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:18:01.927634Z digest=sha256:d65ba32537befd00080a61d3d79671b1afe0a4afaf51cde257676c756158d050

Observation 80ec60b2-6aad-4242-bbf7-5ca7ecaff334 · outbound

This paper cites Hybridizing niching, particle swarm optimization, and evolution strategy for multimodal optimization.IEEE Transactions on Cybernetics, 52(7):6707–6720, 2022.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Hybridizing niching, particle swarm optimization, and evolution strategy for multimodal optimization.IEEE Transactions on Cybernetics, 52(7):6707–6720, 2022

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-07T15:18:10.545253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:18:02.045778Z digest=sha256:4d6990d330887127d2e200f9505293592e0ed531f2c6f4a2e513e86631936bb0

Observation 0bbf46f3-06e8-4c9b-9f44-c59f83b7a278 · outbound

This paper cites American invitational mathematics examination - aime.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization American invitational mathematics examination - aime

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-07T15:18:10.447065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:18:02.145037Z digest=sha256:28e3f91aa4daa13c16a47bceac8b57cbd4deefa4a6bed8d6ede749194abd3bfd

Observation 19665f8a-6383-4aa8-8749-7a44cbff3647 · outbound

This paper cites American invitational mathematics examination - aime.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization American invitational mathematics examination - aime

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:18:10.285426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:18:02.228615Z digest=sha256:e325eeb42a5cebe9b396afb7571e50e1a39f4c2ff617f1a8919d0e0b5062cfc1

Observation a419d02c-a5a5-4487-8330-78538cec07f2 · outbound

This paper cites an unresolved cited work.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Unresolved cited work

Reference 29

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unresolved
raw_fallback, observed 2026-08-07T15:18:10.169359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:18:02.323339Z digest=sha256:20d191bfc36190fbc567efade4078050ff69018c2c9417df4fc9f33775649fad

Observation 9dadb48c-cc27-48ac-b384-2cde689b1573 · outbound

This paper cites A clearing procedure as a niching method for genetic algorithms.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization A clearing procedure as a niching method for genetic algorithms

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:18:09.902066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:18:02.582979Z digest=sha256:ce02ecacc265d8390e0d3d1205ce2e3c7a3648ee9a7be95e38f517356930e01c

Observation a259cf7b-53bd-4e42-909a-b90d1a448751 · outbound

This paper cites Niching the CMA-ES via nearest-better clustering.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Niching the CMA-ES via nearest-better clustering

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-07T15:18:09.680415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:18:03.334784Z digest=sha256:383ec966a4bf0bb20334979a9eeb947d5614ff6825f658925c5121720938a75a

Observation d0232530-d323-463b-b2d3-d94c443b00f0 · outbound

This paper cites Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces.Journal of global optimization, 11:341–359, 1997.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces.Journal of global optimization, 11:341–359, 1997

Reference 32

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unresolved
no resolver link, observed 2026-08-07T15:18:04.029901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:18:04.029901Z digest=sha256:e60813e4f59db257dac29fecd214a8543292771b85009911e230a2bf860fd333

Observation b17528c5-8db0-48b7-8367-fe75a4fa1e7a · outbound

This paper cites Multi-Agent Collaboration Mechanisms: A Survey of LLMs.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Multi-Agent Collaboration Mechanisms: A Survey of LLMs

Reference 33

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unresolved
no resolver link, observed 2026-08-07T15:18:04.271715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:18:04.271715Z digest=sha256:cfd4989f6a72542e867efcf56a4657e1bdb53e85df6f1b8b9c5194ce2d86402e

Observation ff2f5898-19ae-42ae-907a-5e7bd4b431eb · outbound

This paper cites CRC press, 1994.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization CRC press, 1994

Reference 34

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:18:04.455487Z digest=sha256:970ee8a215a45254ab034b296a981ca9f27c44b251c1907f10ba562ea379313a

Observation d8dca236-7c63-45f3-bc22-2d0052b7dd93 · outbound

This paper cites Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models

Reference 35

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source=pdf_text observed=2026-08-07T15:18:04.535605Z digest=sha256:80c754ee51cbd17ddca62b492c7f20d243f57d8380dde9ffc886d40cad1bf74f

Observation 082b071f-022c-4bc0-b921-ac90b6f3c48f · outbound

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

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key?

Reference 36

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source=pdf_text observed=2026-08-07T15:18:04.654575Z digest=sha256:85ab7a37dea8a683272065157312537305c545202a31f6879547b69b30bdfaa3

Observation d258f7c7-24db-4c04-aa8d-66463f7f6d5b · outbound

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

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Self-consistency improves chain of thought reasoning in language models

Reference 37

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source=pdf_text observed=2026-08-07T15:18:04.815138Z digest=sha256:f650c918317883f03da4d0feecbeffb2b28547d6b668f1f96d0f098067ae5712

Observation ab26c75a-f382-4666-881a-4d1c5ff7826e · outbound

This paper cites Yen, and Wu Song.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Yen, and Wu Song

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-07T15:18:09.232444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:18:04.979802Z digest=sha256:2357e176c377d65ba66d17b9459a13369e652c6864f454a9d2bd8935fb649149

Observation 533ed3fb-8794-446f-ab0f-821ce39a4231 · outbound

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

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Chain-of-thought prompting elicits reasoning in large language models

Reference 39

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source=pdf_text observed=2026-08-07T15:18:05.093841Z digest=sha256:20f2fc1616dc8605f002061b60625ad53948ac27a1bca3064f9ebce460ac8d0f

Observation 0bed272a-763f-43d1-9706-f6d1bbfed3d7 · outbound

This paper cites A penalty-based differential evolution for multimodal optimization.IEEE Transactions on Cybernetics, 52(7):6024–6033, 2022.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization A penalty-based differential evolution for multimodal optimization.IEEE Transactions on Cybernetics, 52(7):6024–6033, 2022

Reference 40

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verified fuzzy
raw_fallback, observed 2026-08-07T15:18:08.970360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:18:05.199201Z digest=sha256:795d69bb0ddb6072298c296bd847ce741df621062e6e7f49a25e1de49ebb13c4

Observation 76c49cde-57d1-41d0-ad65-db676fbb7a56 · outbound

This paper cites Autogen: Enabling next-gen llm applications via multi-agent conversations.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Autogen: Enabling next-gen llm applications via multi-agent conversations

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:18:08.765830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:18:05.353936Z digest=sha256:cacdfc4795ec11920a228054b22b6906eb15347804b41becb1530c04d9c89b5c

Observation 28fd13ad-871f-403f-84a9-3fd152d95278 · outbound

This paper cites An alternative way of evolutionary multimodal optimization: density-based population initialization strategy.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization An alternative way of evolutionary multimodal optimization: density-based population initialization strategy

Reference 42

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verified fuzzy
raw_fallback, observed 2026-08-07T15:18:08.508127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:18:05.509057Z digest=sha256:7d42821b05ff3d048fa09bc02780beccaa0bbaeb9d5faaf28423bf8e034f8d58

Observation c109424c-64dc-4009-a955-e26644c620dc · outbound

This paper cites Tree of thoughts: Deliberate problem solving with large language models.Ad- vances in neural information processing systems, 36:11809–11822, 2023.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Tree of thoughts: Deliberate problem solving with large language models.Ad- vances in neural information processing systems, 36:11809–11822, 2023

Reference 43

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source=pdf_text observed=2026-08-07T15:18:05.637885Z digest=sha256:4d59fd849448498aae1db1ca3b90121a44b6d60b3effab3981e6d3b5969ab98d

Observation f5fbc9ec-b9c7-413b-a247-2e997f9062a0 · outbound

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

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Exchange-of-thought: Enhancing large language model capabilities through cross-model communication

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:18:08.238621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:18:05.723707Z digest=sha256:39e85a86b7280d50c764d2fd231722bb70ae37cf98c76444d04cb0721a4e066d

Observation c1c90507-3994-46eb-8568-002a362cdfe9 · outbound

This paper cites Stop Overvaluing Multi-Agent Debate -- We Must Rethink Evaluation and Embrace Model Heterogeneity.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Stop Overvaluing Multi-Agent Debate -- We Must Rethink Evaluation and Embrace Model Heterogeneity

Reference 45

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source=pdf_text observed=2026-08-07T15:18:05.812386Z digest=sha256:00f4c968ead2967a494967bf4d1528948aa79db0e09df565cfc80ea3feb95b7c

Observation bf36790b-6c1b-4b9a-bd8a-c92ca4b5957a · outbound

This paper cites The Lessons of Developing Process Reward Models in Mathematical Reasoning.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization The Lessons of Developing Process Reward Models in Mathematical Reasoning

Reference 46

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source=pdf_text observed=2026-08-07T15:18:05.961672Z digest=sha256:b5f7cdf62ed93906c48a97f7a26395af2c5573f3df59b60486e857dbe760a6d1

Observation e6403871-cf60-40f1-b7de-5d7f1a4efe76 · outbound

This paper cites Automatic chain of thought prompting in large language models.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Automatic chain of thought prompting in large language models

Reference 47

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verified fuzzy
raw_fallback, observed 2026-08-07T15:18:07.886264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:18:06.116954Z digest=sha256:44d491c612672d23fba1c84a18482f53d6257c91c6c47ae628405ecf0b2e2d1a

Observation 1554a998-6633-4282-a691-2d4b751cd501 · outbound

This paper cites Least-to-most prompting enables complex reasoning in large language models.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization Least-to-most prompting enables complex reasoning in large language models

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:18:07.546920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:18:06.281439Z digest=sha256:110aed6e91e2ada776943838ff8b4bb2f7921dde812830dc2fcc66be7ac1f718

Observation fa354434-7fa9-487d-b74c-d26c1db85583 · outbound

This paper cites ReSo: A Reward-driven Self-organizing LLM-based Multi-Agent System for Reasoning Tasks.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization ReSo: A Reward-driven Self-organizing LLM-based Multi-Agent System for Reasoning Tasks

Reference 49

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source=pdf_text observed=2026-08-07T15:18:06.516181Z digest=sha256:47891c7b841fcd1f241e24a63653b99c97be6a36a2218e81f6892618cd18b198

Observation e94b36d8-e447-4bcd-914b-a6be015a244c · outbound

This paper cites assistant agent.

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization assistant agent

Reference 50

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T15:18:06.711688Z digest=sha256:05650de3bca52d6383ad7382b9f74ed11517ee8951a8b14cfd63eb58fb889783

Pith citing papers

Observation b6b7719f-d3dc-421d-a774-eb9b072ff036 · inbound

Swarm-Driven Multi-Agent Reasoning for Smart City Security cites this paper.

Swarm-Driven Multi-Agent Reasoning for Smart City Security Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization

Reference 22

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source=pdf_text observed=2026-07-12T01:06:18.691416Z digest=sha256:e02c3aee066de0bb994238d78b57d95c7d3b7758be7e2ec571856f29bd7c019e