Pith. sign in

Paper Citation Record · LEDGER

Sequential Large Language Model-Based Hyper-parameter Optimization

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2410.20302.

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

pith.paper-citation-record.v1
2410.20302 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:34:30.165996Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 4fa99b72-46c4-40e6-9c45-cfd3468a4971 · inbound

Optimization Problem Solving Can Transition to Evolutionary Agentic Workflows cites this paper.

Optimization Problem Solving Can Transition to Evolutionary Agentic Workflows Sequential Large Language Model-Based Hyper-parameter Optimization

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-15T23:34:30.165996Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:34:30.165996Z digest=sha256:0869588a11e01ad62034d0e6b8a6f94c71abe65f87c60b0c6aff0a392581a0d3

Observation 2f65c991-430c-426b-aed0-870f9fa3f298 · inbound

Cooperative Design Optimization through Natural Language Interaction cites this paper.

Cooperative Design Optimization through Natural Language Interaction Sequential Large Language Model-Based Hyper-parameter Optimization

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-05T17:36:35.092079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:36:35.092079Z digest=sha256:c6c878c56a11a57a9f8371f3f9442ba4f984767ed2e38412441c046af2aa99bd

Observation 31c896e1-c2a7-4325-a955-85ca33f8eddd · inbound

Efficient and Principled Scientific Discovery through Bayesian Optimization: A Tutorial cites this paper.

Efficient and Principled Scientific Discovery through Bayesian Optimization: A Tutorial Sequential Large Language Model-Based Hyper-parameter Optimization

Reference 66

Resolution
verified exact
arxiv_id, observed 2026-05-13T22:08:20.197448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-13T22:06:48.152555Z digest=sha256:b7a61d38fc62c4a740dc0d890436cb4dff2e9f87634d2da0b5c0609a3803fb95

Observation 0dc78ba2-8ac4-4958-bcf8-4ab0ca74ada0 · inbound

AutoLLMResearch: Training Research Agents for Automating LLM Experiment Configuration - Learning from Cheap, Optimizing Expensive cites this paper.

AutoLLMResearch: Training Research Agents for Automating LLM Experiment Configuration - Learning from Cheap, Optimizing Expensive Sequential Large Language Model-Based Hyper-parameter Optimization

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-13T01:17:01.991583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-13T01:15:58.175350Z digest=sha256:5fd588160428ad269b0c43fdd402ef4b88ff26c728a859533109c8efd1ba6e84

Observation 008ac84d-c605-4055-b0dd-1e8f6a3357e0 · inbound

AutoLLMResearch: Training Research Agents for Automating LLM Experiment Configuration - Learning from Cheap, Optimizing Expensive cites this paper.

AutoLLMResearch: Training Research Agents for Automating LLM Experiment Configuration - Learning from Cheap, Optimizing Expensive Sequential Large Language Model-Based Hyper-parameter Optimization

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-20T22:39:10.193412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-20T22:36:56.061187Z digest=sha256:a58c48e31b831ac150dbcaf95af612e5b97f093a1d7b0dbe774e35a4aa331323

Observation d8e84807-990c-4d40-9bc2-9ec6e7c7889a · inbound

When Is an LLM Worth It for Hyperparameter Optimization? A Budget-Matched Study on Tabular Data Finds the Warm-Start Is a Default Configuration, Not the Model cites this paper.

When Is an LLM Worth It for Hyperparameter Optimization? A Budget-Matched Study on Tabular Data Finds the Warm-Start Is a Default Configuration, Not the Model Sequential Large Language Model-Based Hyper-parameter Optimization

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-07-04T06:19:37.918504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-06-26T14:38:52.451377Z digest=sha256:2425656fe6fa696b9ed9130d4304949ffa00002e648a3fd4e21e1ecae80e0cd3

Observation d01cb219-e2ec-4b7c-b9df-528eea700791 · inbound

When Is an LLM Worth It for Hyperparameter Optimization? A Budget-Matched Study on Tabular Data Finds the Warm-Start Is a Default Configuration, Not the Model cites this paper.

When Is an LLM Worth It for Hyperparameter Optimization? A Budget-Matched Study on Tabular Data Finds the Warm-Start Is a Default Configuration, Not the Model Sequential Large Language Model-Based Hyper-parameter Optimization

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-06-29T19:53:56.128532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-06-29T04:37:37.944091Z digest=sha256:0306ccedb75bca90817d7330b89af18fd0986e58449dbcaa0f29956f6ffe5eb1

Observation 508b6ae9-042c-4645-b19c-f2b233e792d3 · inbound

GRIMIP: A General Framework for Instance-Specific Configuration of MIP Solvers Using LLMs cites this paper.

GRIMIP: A General Framework for Instance-Specific Configuration of MIP Solvers Using LLMs Sequential Large Language Model-Based Hyper-parameter Optimization

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-07-04T10:09:45.035580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-26T09:05:56.687400Z digest=sha256:d39c4d6944e5ce5e919ef461635e860f240887e04dded4dcbab7e7aa4207e779

Observation df4c4bd4-f785-480b-a208-1bfca1f81279 · inbound

AI Training Manager: Bounded Closed-Loop Control of Adaptive Training Recipes cites this paper.

AI Training Manager: Bounded Closed-Loop Control of Adaptive Training Recipes Sequential Large Language Model-Based Hyper-parameter Optimization

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-06-30T06:54:21.217925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-30T06:35:10.832304Z digest=sha256:33853dc752b75a2c7065b5639448004e0a0828273ce71ca139c6fee552aed6cc

Observation fb384162-319e-46d5-ba5a-76e3deda0b21 · inbound

AgentHPOBench: A Benchmark For Evaluating LLM Agents as Sequential Hyperparameter Optimizers cites this paper.

AgentHPOBench: A Benchmark For Evaluating LLM Agents as Sequential Hyperparameter Optimizers Sequential Large Language Model-Based Hyper-parameter Optimization

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-03T03:15:14.213821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T03:15:14.213821Z digest=sha256:2e2ffe3a0844b3021766029985ea1efdbf6e572c4f9efb036be7c07623bfab6d

Observation 65b921b3-490d-41e0-8289-92840a3ecf9b · inbound

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

Agentic Bayesian Optimization through Surrogate-Augmented Autoresearch Sequential Large Language Model-Based Hyper-parameter Optimization

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-04T00:51:33.966984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T00:51:33.966984Z digest=sha256:b01c52d99ff2680077641cf08ff98d282ed3889688ae8b7b4d815f9ccde6cbfb