Paper Citation Record · LEDGER

Adversarial Robustness in Distributed Quantum Machine Learning

As of 20 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 1 inbound Pith citation observation for arXiv:2508.11848.

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

pith.paper-citation-record.v1
2508.11848 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T19:46:25.271383Z

measured 22 of 22 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-13T06:23:02.975594Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T06:27:24.848118Z

Reference resolution

21 of 21 outbound references displayed

verified exact2
verified fuzzy10
unresolved8
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 947eef5a-8c28-43a5-bb6a-d2fc0dbdbf8d · outbound

This paper cites E., Danna, E., Gamrath, G., Gleixner, A.

Adversarial Robustness in Distributed Quantum Machine Learning E., Danna, E., Gamrath, G., Gleixner, A

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:46:28.666911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 762777b0-378e-4076-9f02-83ac1f574949 · outbound

This paper cites Evolution of heuristics: Towards efficient automatic algorithm design using large language model.

Adversarial Robustness in Distributed Quantum Machine Learning Evolution of heuristics: Towards efficient automatic algorithm design using large language model

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T19:46:24.007634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2eb37c6f-8f66-454e-99c0-97d43d7f6961 · outbound

This paper cites Mostajabdaveh, M., Yu, T.

Adversarial Robustness in Distributed Quantum Machine Learning Mostajabdaveh, M., Yu, T

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:46:28.653637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 10d76259-4bad-4ef2-8045-48dd09bf3ec8 · outbound

This paper cites Ostrowski, J., Anjos, M.

Adversarial Robustness in Distributed Quantum Machine Learning Ostrowski, J., Anjos, M

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:46:28.639842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 598296dc-b1c5-41a0-9cfb-9b09c3606901 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Adversarial Robustness in Distributed Quantum Machine Learning Gemini: A Family of Highly Capable Multimodal Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T19:46:24.489824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9578fbb-03de-496d-b4dc-d2ada13fd7dd · outbound

This paper cites ReEvo: Large language models as hyper- heuristics with reflective evolution.

Adversarial Robustness in Distributed Quantum Machine Learning ReEvo: Large language models as hyper- heuristics with reflective evolution

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:46:27.771302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4e1f6dd0-9a99-4ede-89a0-892440e101b1 · outbound

This paper cites EVOCUTPseudocode The full procedure is outlined in Algorithm 1, which presents the pseudocode for the proposed EVOCUTframework.

Adversarial Robustness in Distributed Quantum Machine Learning EVOCUTPseudocode The full procedure is outlined in Algorithm 1, which presents the pseudocode for the proposed EVOCUTframework

Reference 16

Resolution: malformed identifier; raw_fallback, observed 2026-08-05T19:46:27.482058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 48a94cd9-69ea-4a2a-94c2-06eb67bdd368 · outbound

This paper cites an unresolved cited work.

Adversarial Robustness in Distributed Quantum Machine Learning Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-05T19:46:27.142235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6970a5cc-fe75-451b-b2e0-70114fca5c9a · outbound

This paper cites an unresolved cited work.

Adversarial Robustness in Distributed Quantum Machine Learning Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-05T19:46:26.824617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9f74408c-81f4-49da-9261-74dc1d5f2fc9 · outbound

This paper cites Compact MILP formulation.

Adversarial Robustness in Distributed Quantum Machine Learning Compact MILP formulation

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:46:26.616031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1bd77b6a-bdf3-4cd6-a282-ea3a084a00d0 · outbound

This paper cites an unresolved cited work.

Adversarial Robustness in Distributed Quantum Machine Learning Unresolved cited work

Reference 1990

Resolution: unresolved; raw_fallback, observed 2026-08-05T19:46:26.960145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9656a358-03e3-4709-9acd-6cbc97d0a179 · outbound

This paper cites NL4Opt competition: Formulating optimization problems based on their natural language descriptions.

Adversarial Robustness in Distributed Quantum Machine Learning NL4Opt competition: Formulating optimization problems based on their natural language descriptions

Reference 1991

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:46:28.082135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e7389ce3-d30e-4101-8987-64c0a6c1806f · outbound

This paper cites For our experiments, we used instances from TSPLIB (Reinelt, 1991), a widely used benchmark, together with the Miller-Tucker-Zemlin (MTZ) formulation in Eq.

Adversarial Robustness in Distributed Quantum Machine Learning For our experiments, we used instances from TSPLIB (Reinelt, 1991), a widely used benchmark, together with the Miller-Tucker-Zemlin (MTZ) formulation in Eq

Reference 1992

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:46:27.357951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6c12d7f3-b924-4415-bf70-e9d8176fec01 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Adversarial Robustness in Distributed Quantum Machine Learning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 1999

Resolution: unresolved; no resolver link, observed 2026-08-05T19:46:23.582845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc2e3f90-9559-4e16-9985-07b685e6dea3 · outbound

This paper cites Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model.

Adversarial Robustness in Distributed Quantum Machine Learning Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model

Reference 2002

Resolution: unresolved; no resolver link, observed 2026-08-05T19:46:24.593329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56e9f1f8-8a78-4377-a953-c9820dda258b · outbound

This paper cites da Cunha, A.

Adversarial Robustness in Distributed Quantum Machine Learning da Cunha, A

Reference 2009

Resolution: verified exact; doi, observed 2026-08-05T19:46:25.503936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation bb9edeae-dcd0-418d-b9d1-b227f1939d3c · outbound

This paper cites Queyranne, M.

Adversarial Robustness in Distributed Quantum Machine Learning Queyranne, M

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:46:28.360978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7f61f57a-c0ef-4f0b-a1a2-2d0c4cf4dccb · outbound

This paper cites 2025 IMO problem- s/problem.

Adversarial Robustness in Distributed Quantum Machine Learning 2025 IMO problem- s/problem

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:46:28.706597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f23b2c74-0576-447b-bc15-72ccac86a171 · outbound

This paper cites Costa, A.

Adversarial Robustness in Distributed Quantum Machine Learning Costa, A

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:46:28.693750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ce073101-f394-47c1-8509-27100def1ad0 · outbound

This paper cites doi: https://doi.org/10.1016/j.swevo.2024.101663.

Adversarial Robustness in Distributed Quantum Machine Learning doi: https://doi.org/10.1016/j.swevo.2024.101663

Reference 2024

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-05T19:46:26.479731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a3df7502-818b-43bc-af42-00740e3018f0 · outbound

This paper cites an unresolved cited work.

Adversarial Robustness in Distributed Quantum Machine Learning Unresolved cited work

Reference 2025

Resolution: unresolved; raw_fallback, observed 2026-08-05T19:46:28.680443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

Observation c1b88d4e-a39b-476c-8aea-cbfa134bfb43 · inbound

Controlled Steering-Based State Preparation for Adversarial-Robust Quantum Machine Learning cites this paper.

Controlled Steering-Based State Preparation for Adversarial-Robust Quantum Machine Learning Adversarial Robustness in Distributed Quantum Machine Learning

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-13T06:27:24.849949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.