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Paper Citation Record · LEDGER

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization

As of 7 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 1 inbound Pith citation observation for arXiv:2505.19205.

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

pith.paper-citation-record.v1
2505.19205 v2

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:22:04.548148Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T00:51:33.810307Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

24 of 24 outbound references displayed

  • verified exact0
  • verified fuzzy20
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 65c26088-ed66-4d48-95ab-e23f3158d495 · outbound

This paper cites Random search for hyper-parameter optimization,.

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization Random search for hyper-parameter optimization,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:22:04.847621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:22:04.455227Z digest=sha256:6a05aac658e0a0804dbd333da3259f3913f75c1442fdf8aab304c778428249e8

Observation 80a6cad2-f076-45e7-b7c2-902250e395bf · outbound

This paper cites Practical Bayesian opti- mization of machine learning algorithms,.

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization Practical Bayesian opti- mization of machine learning algorithms,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:22:04.836025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:22:04.460043Z digest=sha256:2595d28f7ab0ba0b943fd97348b040164e8fff056625a95c9676f5230c49c99f

Observation c920b09b-2cd6-4145-8065-44bee41c4d39 · outbound

This paper cites Floreano and C.

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization Floreano and C

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:22:04.825286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:22:04.463786Z digest=sha256:e42bbcc4bcfdfbc8cdfee0b96784a8f4a6dafda03c3e1a7794c41f1a941c44fb

Observation 820e6265-bd39-4478-940d-7999b2862dd0 · outbound

This paper cites Taking the human out of the loop: A review of Bayesian optimiza- tion,.

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization Taking the human out of the loop: A review of Bayesian optimiza- tion,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:22:04.814619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:22:04.467312Z digest=sha256:14a58e74938df4490f274192c95ccccc7008ed0996bbf04ab8b453696c634500

Observation 5fa78c02-96ba-47f0-b211-511975e7571a · outbound

This paper cites GPyOpt: A Bayesian optimization frame- work in Python,.

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization GPyOpt: A Bayesian optimization frame- work in Python,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:22:04.802877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:22:04.471538Z digest=sha256:32d95a6d8816589f60368e717e6c7984a98034c82d61edf857aa9a93beba19bc

Observation 2cc170a4-3db3-495d-aae6-68e907c78e92 · outbound

This paper cites Scikit-Optimize: Sequential model- based optimization in Python,.

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization Scikit-Optimize: Sequential model- based optimization in Python,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:22:04.791429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:22:04.475372Z digest=sha256:b49220f58c70dce358e873d33db2c128f0c4d98c0ddd89f2be75a28af8205b24

Observation e8bac673-8bcb-4eb1-bd91-a63df243accc · outbound

This paper cites an unresolved cited work.

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization Unresolved cited work

Reference 7

Resolution
unresolved
raw_fallback, observed 2026-08-07T14:22:04.779227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:22:04.479310Z digest=sha256:279a3478fd3d301afa583da7742277195503b21b740294ee77d9a9f22fb7f260

Observation 21fe570d-3094-41c7-907c-aae897c0142c · outbound

This paper cites Particle swarm optimization,.

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization Particle swarm optimization,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:22:04.768418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:22:04.483433Z digest=sha256:9ecd4aa1613e9b7b8c65bdd9498f34bb98ff1c0677a765b7cc51528eda353ca1

Observation 740b5d92-cc31-43aa-8d19-521235dba5ef · outbound

This paper cites Algorithms for hyper-parameter optimization,.

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization Algorithms for hyper-parameter optimization,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:22:04.756887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:22:04.487796Z digest=sha256:aaf75d4a6df668c8191be442140a2bf2666396e5be402049391428f3320202b1

Observation bcb7746e-5bf9-4d4e-9736-2fd69df411a3 · outbound

This paper cites Optuna: A next-generation hyperparameter optimization framework,.

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization Optuna: A next-generation hyperparameter optimization framework,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:22:04.745370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:22:04.491659Z digest=sha256:e91ac0703ef89d9e17f0b923d0f5d9db79c73feb0806f660796079ba887fb829

Observation e5eba524-3bb3-48fd-a532-92fdf7e07cb1 · outbound

This paper cites Hyperband: A novel bandit-based approach to hyperparameter opti- mization,.

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization Hyperband: A novel bandit-based approach to hyperparameter opti- mization,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:22:04.733936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:22:04.495723Z digest=sha256:59c75b9c177b37e1b66bad84b0f4d66f187c8931fb16511e4d4ba5baf9ad7cd5

Observation b824e607-1b18-4198-9442-8528079beee6 · outbound

This paper cites Non-stochastic best arm identification and hyperparameter optimization,.

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization Non-stochastic best arm identification and hyperparameter optimization,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:22:04.722594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:22:04.499548Z digest=sha256:4e120148cfc0c8ea041ace03724aad886a3c96708f62da28e35ada9010343d71

Observation 81a63eeb-5548-41af-ae90-6a002fc31742 · outbound

This paper cites an unresolved cited work.

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-07T14:22:04.711604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:22:04.503298Z digest=sha256:a04eaf1688a7dbd9f1be577401987fcc90911dbe2eb64937b8ba24b97d49aac9

Observation a1bf5ba6-2040-4d46-bc18-781b9844d37f · outbound

This paper cites Ant system: Optimization by a colony of cooperating agents,.

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization Ant system: Optimization by a colony of cooperating agents,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:22:04.700327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:22:04.507143Z digest=sha256:949d59994f8cba8de4adad630a42a1e7a448185b327c3ab8659d8d934e8024b0

Observation fba3a755-0858-405b-ac19-a979a4b8aefd · outbound

This paper cites Current state of the art in distributed autonomous mobile robotics,.

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization Current state of the art in distributed autonomous mobile robotics,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:22:04.688317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:22:04.510800Z digest=sha256:1ec65ec5105cae95c4a52cd9202ada16d4e76d0e5ad9d57cf2d2d7c2e10a9433

Observation 135b6182-2ff9-4d95-8092-9eb8ab960d9d · outbound

This paper cites Gemini: A family of multimodal models,.

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization Gemini: A family of multimodal models,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:22:04.677309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:22:04.514596Z digest=sha256:0007170b70a9149291135d444eb40319779da5ff92f9669959f8d140c4880117

Observation b610ec20-f0b6-4d7f-a5b5-efd1c45507c7 · outbound

This paper cites Voyager: An Open-Ended Embodied Agent with Large Language Models.

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T14:22:04.518654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:22:04.518654Z digest=sha256:9251f9007576cf2be9a1aa8eaa9efcccef5597039482d80e5736a7cae8c3a5ac

Observation 8e99014c-d858-4cf5-a338-58a1f7397e43 · outbound

This paper cites Building with agents: A new paradigm for AI applica- tions,.

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization Building with agents: A new paradigm for AI applica- tions,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:22:04.666083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:22:04.523333Z digest=sha256:afd08c873bc72d9671ff62d55d934feee20e13173c5aeed35a6c8f203dd64cd3

Observation 789ddf95-7739-47b1-be81-3d0ba71b9263 · outbound

This paper cites Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA,.

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:22:04.653515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:22:04.527010Z digest=sha256:d63df8c444c9683c9a350466ad512a936916751b49cf8246637558a9bfe3b488

Observation f0e4a058-af31-419a-a14b-6e4ed6af70ec · outbound

This paper cites OpenML: Networked science in machine learning,.

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization OpenML: Networked science in machine learning,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:22:04.641156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:22:04.531154Z digest=sha256:0f6337b8cfe6874cfd4f6faacbe758906e006448c410d9810090e7f1e97db81f

Observation f3558b2e-9d49-4ab5-9f01-f4f9466b45a0 · outbound

This paper cites Practical automated machine learning for the AutoML challenge 2018,.

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization Practical automated machine learning for the AutoML challenge 2018,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:22:04.628922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:22:04.535598Z digest=sha256:16b028194d197b1dab3ebb09f089883704ed6af37f3100022da5ad48a7c0b846

Observation ee227af1-05d0-4ed7-9d6b-333726a0c2a0 · outbound

This paper cites XGBoost: A scalable tree boosting system,.

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization XGBoost: A scalable tree boosting system,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:22:04.617037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:22:04.539250Z digest=sha256:5b858adb2b4e208a3e66ea3d3783b177ddde5bbd3d2b0e825ff780998a8e3bba

Observation 9b9d0956-025f-4e3b-b7be-4396cb1e8f1e · outbound

This paper cites Large Language Model Agent for Hyper-Parameter Optimization.

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization Large Language Model Agent for Hyper-Parameter Optimization

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T14:22:04.543607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:22:04.543607Z digest=sha256:f28ec4baf5fedf915b471f3eac315efd941ad8d61ec5d9b44e8a0a95a280e4b3

Observation 42919f57-36a0-4fbc-8c5c-6c2956b4d556 · outbound

This paper cites LightGBM: A highly efficient gradient boosting decision tree,.

OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization LightGBM: A highly efficient gradient boosting decision tree,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:22:04.603618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:22:04.548148Z digest=sha256:ebfb8244155abac0a951c4756904d6954d49938719ce4e2217cf08f1cb57a6f7

Pith citing papers

Observation 838ce62c-b154-44a8-9c5e-5fc7fac5dd6f · inbound

Agentic Bayesian Optimization through Surrogate-Augmented Autoresearch cites this paper.

Agentic Bayesian Optimization through Surrogate-Augmented Autoresearch OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-04T00:51:33.810307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T00:51:33.810307Z digest=sha256:adfd7c54e60110a9d592348c0d4a8ad2b707a2a518f8e6859caf5061f37fe31c