Paper Citation Record · LEDGER

Learning Personalized Utility Functions for Drivers in Ride-hailing Systems Using Ensemble Hypernetworks

As of 23 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2506.17672.

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

pith.paper-citation-record.v1
2506.17672 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:08:25.158143Z

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

12 of 12 outbound references displayed

verified exact0
verified fuzzy6
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3d5142e9-6e37-4b73-9404-75f39e04d9f4 · outbound

This paper cites Conditional logit analysis of qualitative choice behavior,.

Learning Personalized Utility Functions for Drivers in Ride-hailing Systems Using Ensemble Hypernetworks Conditional logit analysis of qualitative choice behavior,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T19:08:24.784197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e9fce61-6911-4ceb-9039-3d98fbd5eeec · outbound

This paper cites Ride acceptance behaviour of ride- sourcing drivers,.

Learning Personalized Utility Functions for Drivers in Ride-hailing Systems Using Ensemble Hypernetworks Ride acceptance behaviour of ride- sourcing drivers,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:08:25.600558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0c7b39d1-184b-4603-9cdc-e12bcf074f42 · outbound

This paper cites A pricing mechanism for ride-hailing systems in the presence of driver acceptance uncertainty,.

Learning Personalized Utility Functions for Drivers in Ride-hailing Systems Using Ensemble Hypernetworks A pricing mechanism for ride-hailing systems in the presence of driver acceptance uncertainty,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:08:25.586637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation dd0e08ca-c5dc-4aa1-a24d-eba74caff072 · outbound

This paper cites Comparing hundreds of machine learning classifiers and discrete choice models in predicting travel behavior: an empirical benchmark.

Learning Personalized Utility Functions for Drivers in Ride-hailing Systems Using Ensemble Hypernetworks Comparing hundreds of machine learning classifiers and discrete choice models in predicting travel behavior: an empirical benchmark

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T19:08:24.974093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d454f73a-4015-4c56-8214-87d4c568fc53 · outbound

This paper cites Hypernetworks,.

Learning Personalized Utility Functions for Drivers in Ride-hailing Systems Using Ensemble Hypernetworks Hypernetworks,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:08:25.559491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 08408f6c-ca7c-4a0b-a77f-54837213afac · outbound

This paper cites A Brief Review of Hypernetworks in Deep Learning.

Learning Personalized Utility Functions for Drivers in Ride-hailing Systems Using Ensemble Hypernetworks A Brief Review of Hypernetworks in Deep Learning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T19:08:25.044660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d40cef3-e6af-475d-904b-a79cc4e424cb · outbound

This paper cites Interpretable Mesomorphic Networks for Tabular Data.

Learning Personalized Utility Functions for Drivers in Ride-hailing Systems Using Ensemble Hypernetworks Interpretable Mesomorphic Networks for Tabular Data

Reference 7

Resolution: metadata mismatch; local_arxiv, observed 2026-08-15T19:08:25.224157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4b1d733f-f041-4641-a75f-8aac9ff8b9dc · outbound

This paper cites Sim- ple and scalable predictive uncertainty estimation using deep ensembles,.

Learning Personalized Utility Functions for Drivers in Ride-hailing Systems Using Ensemble Hypernetworks Sim- ple and scalable predictive uncertainty estimation using deep ensembles,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T19:08:25.055699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c45e11e9-9e09-492d-877e-cd1ea881016c · outbound

This paper cites Training independent subnetworks for robust prediction,.

Learning Personalized Utility Functions for Drivers in Ride-hailing Systems Using Ensemble Hypernetworks Training independent subnetworks for robust prediction,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:08:25.456686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2a4beb69-9c0e-419a-bed8-bf7b7bdbade7 · outbound

This paper cites Dropout as a bayesian approximation: Representing model uncertainty in deep learning,.

Learning Personalized Utility Functions for Drivers in Ride-hailing Systems Using Ensemble Hypernetworks Dropout as a bayesian approximation: Representing model uncertainty in deep learning,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T19:08:25.064719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43d71451-139f-49c2-b108-bf4354f1bf3b · outbound

This paper cites Strictly proper scoring rules, prediction, and estimation,.

Learning Personalized Utility Functions for Drivers in Ride-hailing Systems Using Ensemble Hypernetworks Strictly proper scoring rules, prediction, and estimation,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:08:25.420401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 90eb534f-3cf8-4f2b-bcb3-54c0373aa4b9 · outbound

This paper cites Well-tuned simple nets excel on tabular datasets,.

Learning Personalized Utility Functions for Drivers in Ride-hailing Systems Using Ensemble Hypernetworks Well-tuned simple nets excel on tabular datasets,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:08:25.361459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

No inbound Pith citation observations are available.