Paper Citation Record · LEDGER

The Problem of Dynamic Spatial Sampling and Geofence Surveillance

As of 20 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2603.28958.

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

pith.paper-citation-record.v1
2603.28958 v2

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-13T16:01:44.895474Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

20 of 20 outbound references displayed

verified exact0
verified fuzzy0
unresolved20
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ea356640-a653-472b-b502-459ae50500d4 · outbound

This paper cites Searching for optimal solutions with llms via bayesian optimization.

The Problem of Dynamic Spatial Sampling and Geofence Surveillance Searching for optimal solutions with llms via bayesian optimization

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-13T16:01:44.895474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf15286c-dbbb-4cd8-8a21-a466f8a48fae · outbound

This paper cites Fairpi- lot: An interactive system for fairness–accuracy model selection powered by apex.Information and Software Technology, page 107912, 2025.

The Problem of Dynamic Spatial Sampling and Geofence Surveillance Fairpi- lot: An interactive system for fairness–accuracy model selection powered by apex.Information and Software Technology, page 107912, 2025

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-13T16:01:44.895474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18af326b-5fd2-4f6a-8b00-523d9af2410d · outbound

This paper cites High-dimensional black-box optimization under uncer- tainty.Computers & Operations Research, 137:105444, 2022.

The Problem of Dynamic Spatial Sampling and Geofence Surveillance High-dimensional black-box optimization under uncer- tainty.Computers & Operations Research, 137:105444, 2022

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-13T16:01:44.895474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74b96691-2973-4362-af2c-684b05b42052 · outbound

This paper cites an unresolved cited work.

The Problem of Dynamic Spatial Sampling and Geofence Surveillance Unresolved cited work

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-13T16:01:44.895474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84a71fd8-0990-4e32-9b50-8fdd7a3bfa34 · outbound

This paper cites Langchain.��, 2023.

The Problem of Dynamic Spatial Sampling and Geofence Surveillance Langchain.��, 2023

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-13T16:01:44.895474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04ff17ab-08a9-4277-b0b3-9fec16b58b8e · outbound

This paper cites Exploring representativeness and informativeness for active learning.IEEE transactions on cybernetics, 47(1):14–26, 2015.

The Problem of Dynamic Spatial Sampling and Geofence Surveillance Exploring representativeness and informativeness for active learning.IEEE transactions on cybernetics, 47(1):14–26, 2015

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-13T16:01:44.895474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77b8575f-e2d2-49f1-9e2e-0c8bec8cd222 · outbound

This paper cites Bayesian optimization.Cambridge University Press, 2023.

The Problem of Dynamic Spatial Sampling and Geofence Surveillance Bayesian optimization.Cambridge University Press, 2023

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-13T16:01:44.895474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd53abb9-46bd-47c2-a283-d6efa07aa8e0 · outbound

This paper cites Diversity- driven exploration strategy for deep reinforcement learning.Advances in neural information processing systems, 31, 2018.

The Problem of Dynamic Spatial Sampling and Geofence Surveillance Diversity- driven exploration strategy for deep reinforcement learning.Advances in neural information processing systems, 31, 2018

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-13T16:01:44.895474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1de0f7c-2683-4aef-afa0-ba2252c3fabc · outbound

This paper cites Exploring the True Potential: Evaluating the Black-box Optimization Capability of Large Language Models.

The Problem of Dynamic Spatial Sampling and Geofence Surveillance Exploring the True Potential: Evaluating the Black-box Optimization Capability of Large Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-13T16:01:44.895474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59e07677-090c-411d-a92d-5dd6159c520e · outbound

This paper cites Active learning in brain tumor segmentation with uncertainty sampling and annotation redundancy restriction.Journal of Imaging Informatics in Medicine, 37(5):2099–2107, 2024.

The Problem of Dynamic Spatial Sampling and Geofence Surveillance Active learning in brain tumor segmentation with uncertainty sampling and annotation redundancy restriction.Journal of Imaging Informatics in Medicine, 37(5):2099–2107, 2024

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-13T16:01:44.895474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d7a5c72-7901-4ed4-bd6c-bf7844240554 · outbound

This paper cites Language models as black-box optimizers for vision-language models.

The Problem of Dynamic Spatial Sampling and Geofence Surveillance Language models as black-box optimizers for vision-language models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-13T16:01:44.895474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b74ba950-0162-4bc1-861a-4c5d793ef90a · outbound

This paper cites Large Language Models to Enhance Bayesian Optimization.

The Problem of Dynamic Spatial Sampling and Geofence Surveillance Large Language Models to Enhance Bayesian Optimization

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-13T16:01:44.895474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3de91a34-b3f5-48be-baa8-86c1517fd22e · outbound

This paper cites Hyperparameter adaptive search for surrogate optimization: A self- adjusting approach.

The Problem of Dynamic Spatial Sampling and Geofence Surveillance Hyperparameter adaptive search for surrogate optimization: A self- adjusting approach

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-13T16:01:44.895474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eaf6b5c2-2e17-490b-a633-f784d6fc1093 · outbound

This paper cites Enhancing batch diversity in surrogate optimization: A determinantal point processes approach.ACM Transactions on Evolutionary Learning, 5(3):1–30, 2025.

The Problem of Dynamic Spatial Sampling and Geofence Surveillance Enhancing batch diversity in surrogate optimization: A determinantal point processes approach.ACM Transactions on Evolutionary Learning, 5(3):1–30, 2025

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-13T16:01:44.895474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2aaedd27-b76a-4ed9-b7de-2b7797e6cfee · outbound

This paper cites Position: Leverage Foundational Models for Black-Box Optimization.

The Problem of Dynamic Spatial Sampling and Geofence Surveillance Position: Leverage Foundational Models for Black-Box Optimization

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-13T16:01:44.895474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cdfe4c81-f543-46ed-97b6-d621cc4f1e02 · outbound

This paper cites Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design.

The Problem of Dynamic Spatial Sampling and Geofence Surveillance Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-13T16:01:44.895474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 305807ca-e5b5-4243-893a-25ce45c601b5 · outbound

This paper cites Large language models as optimizers.

The Problem of Dynamic Spatial Sampling and Geofence Surveillance Large language models as optimizers

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-13T16:01:44.895474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b59817f-03ea-4a32-ae3c-8a96a83eef2e · outbound

This paper cites Large Scale Multi-Task Bayesian Optimization with Large Language Models.

The Problem of Dynamic Spatial Sampling and Geofence Surveillance Large Scale Multi-Task Bayesian Optimization with Large Language Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-13T16:01:44.895474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6ad5055-8cb8-40a9-a280-6dccc7a9172b · outbound

This paper cites Using Large Language Models for Hyperparameter Optimization.

The Problem of Dynamic Spatial Sampling and Geofence Surveillance Using Large Language Models for Hyperparameter Optimization

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-13T16:01:44.895474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b2341e4-881d-492c-b998-073fac824116 · outbound

This paper cites an unresolved cited work.

The Problem of Dynamic Spatial Sampling and Geofence Surveillance Unresolved cited work

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-13T16:01:44.895474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.