Paper Citation Record · LEDGER

HattriQ: Designing Integrated Gradients for Feature Attribution in Quantum Machine Learning

As of 9 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2510.02497.

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

pith.paper-citation-record.v1
2510.02497 v2

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T12:48:34.326459Z

measured 19 of 19 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 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

19 of 19 outbound references displayed

verified exact1
verified fuzzy0
unresolved18
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 41cab699-2d66-4deb-b0f8-856ad422b48a · outbound

This paper cites Better than classical? The subtle art of benchmarking quantum machine learning models.

HattriQ: Designing Integrated Gradients for Feature Attribution in Quantum Machine Learning Better than classical? The subtle art of benchmarking quantum machine learning models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-04T12:48:32.231762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d66f526c-5bf0-4053-ba08-2757e2d08f65 · outbound

This paper cites Scalable and interpretable quantum natural language processing: an implementation on trapped ions.

HattriQ: Designing Integrated Gradients for Feature Attribution in Quantum Machine Learning Scalable and interpretable quantum natural language processing: an implementation on trapped ions

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T12:48:32.567007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6cacc3b7-ea28-4d01-b413-2fd849c39d78 · outbound

This paper cites EnQode: Fast Amplitude Embedding for Quantum Machine Learning Using Classical Data.

HattriQ: Designing Integrated Gradients for Feature Attribution in Quantum Machine Learning EnQode: Fast Amplitude Embedding for Quantum Machine Learning Using Classical Data

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T12:48:32.685898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c126e81-9d50-4112-bfe3-05195db27861 · outbound

This paper cites The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective.

HattriQ: Designing Integrated Gradients for Feature Attribution in Quantum Machine Learning The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T12:48:32.972806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa59a1b4-c032-4e8e-b70e-07eb48c47f70 · outbound

This paper cites Quantum embeddings for machine learning.

HattriQ: Designing Integrated Gradients for Feature Attribution in Quantum Machine Learning Quantum embeddings for machine learning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T12:48:33.107217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3902499f-7362-40b8-b3cd-4f92e314e44f · outbound

This paper cites doi: 10.18653/v1/P18-1176.

HattriQ: Designing Integrated Gradients for Feature Attribution in Quantum Machine Learning doi: 10.18653/v1/P18-1176

Reference 12

Resolution: verified exact; doi, observed 2026-08-04T12:53:32.377542Z

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.

Observation b2c3f580-22d7-476f-9d60-449a64279519 · outbound

This paper cites Maria Schuld and Nathan Killoran.

HattriQ: Designing Integrated Gradients for Feature Attribution in Quantum Machine Learning Maria Schuld and Nathan Killoran

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T12:48:33.528267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1631db32-d892-47d8-9574-c6e3c1af7502 · outbound

This paper cites Supervised learning with quantum computers.Quantum science and technology (Springer, 2018),.

HattriQ: Designing Integrated Gradients for Feature Attribution in Quantum Machine Learning Supervised learning with quantum computers.Quantum science and technology (Springer, 2018),

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T12:48:33.674248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1e6a47f-5851-40db-b12c-741079a87954 · outbound

This paper cites URL https://link.aps.org/doi/10.1103/PhysRevA.99.032331.

HattriQ: Designing Integrated Gradients for Feature Attribution in Quantum Machine Learning URL https://link.aps.org/doi/10.1103/PhysRevA.99.032331

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T12:48:33.846653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce3a4c8d-d954-4a92-848e-8927341908c3 · outbound

This paper cites Andrew G White, DFV James, William J Munro, and PG Kwiat.

HattriQ: Designing Integrated Gradients for Feature Attribution in Quantum Machine Learning Andrew G White, DFV James, William J Munro, and PG Kwiat

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T12:48:34.080579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe389068-9579-478d-9ec1-57154eb6a1c0 · outbound

This paper cites Yusen Wu, Bujiao Wu, Yanqi Song, Xiao Yuan, and Jingbo Wang.

HattriQ: Designing Integrated Gradients for Feature Attribution in Quantum Machine Learning Yusen Wu, Bujiao Wu, Yanqi Song, Xiao Yuan, and Jingbo Wang

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T12:48:34.197530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb666679-cc47-489c-a25e-b3ef7cf27984 · outbound

This paper cites an unresolved cited work.

HattriQ: Designing Integrated Gradients for Feature Attribution in Quantum Machine Learning Unresolved cited work

Reference 2013

Resolution: unresolved; no resolver link, observed 2026-08-04T12:48:33.284786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dccfdbf7-4fe8-4840-9b31-eb37bccc4374 · outbound

This paper cites A Survey of Quantum Property Testing.

HattriQ: Designing Integrated Gradients for Feature Attribution in Quantum Machine Learning A Survey of Quantum Property Testing

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-04T12:48:33.197485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 261fc1b8-a79c-4d6f-8a35-fd42cb99caf2 · outbound

This paper cites What is my quantum computer good for? Quantum capability learning with physics-aware neural networks.

HattriQ: Designing Integrated Gradients for Feature Attribution in Quantum Machine Learning What is my quantum computer good for? Quantum capability learning with physics-aware neural networks

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-04T12:48:32.854157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27b5e085-4261-4481-a781-d342ad67b576 · outbound

This paper cites URL https://link.aps.org/doi/10.1103/PhysRevA.101.032308.

HattriQ: Designing Integrated Gradients for Feature Attribution in Quantum Machine Learning URL https://link.aps.org/doi/10.1103/PhysRevA.101.032308

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-04T12:48:33.946551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a7053d6-f28e-4861-8237-bd95d800d172 · outbound

This paper cites PennyLane: Automatic differentiation of hybrid quantum-classical computations.

HattriQ: Designing Integrated Gradients for Feature Attribution in Quantum Machine Learning PennyLane: Automatic differentiation of hybrid quantum-classical computations

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-04T12:48:32.161249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ba84ada-4a9a-4fac-86d7-39a4943678b2 · outbound

This paper cites Multi-qubit rydberg gates between distant atoms.arXiv preprint arXiv:2507.16602,.

HattriQ: Designing Integrated Gradients for Feature Attribution in Quantum Machine Learning Multi-qubit rydberg gates between distant atoms.arXiv preprint arXiv:2507.16602,

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-04T12:48:32.297769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a8d52ea-60b7-4754-b044-68ce432e2d9b · outbound

This paper cites Efficiently manipulating Pauli strings with PauliArray.

HattriQ: Designing Integrated Gradients for Feature Attribution in Quantum Machine Learning Efficiently manipulating Pauli strings with PauliArray

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-04T12:48:32.420197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e55b1c0f-e084-4caa-b190-3ae46df0e7c7 · outbound

This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

HattriQ: Designing Integrated Gradients for Feature Attribution in Quantum Machine Learning Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-04T12:48:34.326459Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.