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Paper Citation Record · LEDGER

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference

As of 8 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2506.00518.

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

pith.paper-citation-record.v1
2506.00518 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:08:17.621396Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

30 of 30 outbound references displayed

  • verified exact0
  • verified fuzzy29
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 376b7e2f-97e8-43d9-acee-b2579f0a3eda · outbound

This paper cites Protocols for secure computations (extended abstract),.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference Protocols for secure computations (extended abstract),

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation c4ba81a9-38dd-45d0-b664-e9335a5abf65 · outbound

This paper cites How to play any mental game or A completeness theorem for protocols with honest majority,.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference How to play any mental game or A completeness theorem for protocols with honest majority,

Reference 2

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation f6da39cb-116f-46e5-8548-560a0f76fcac · outbound

This paper cites Completeness theorems for non-cryptographic fault-tolerant distributed computation (extended abstract),.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference Completeness theorems for non-cryptographic fault-tolerant distributed computation (extended abstract),

Reference 3

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 6bae5dfc-47a3-4845-85d7-277481839e18 · outbound

This paper cites Multiparty unconditionally secure protocols (abstract),.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference Multiparty unconditionally secure protocols (abstract),

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 561ecbf0-4ff5-45d7-b5bf-cdb44e8bf985 · outbound

This paper cites Multiparty computation from somewhat homomorphic encryption,.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference Multiparty computation from somewhat homomorphic encryption,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation a938171e-3f21-44fd-b5ad-caf780a5dbde · outbound

This paper cites Catching MPC cheaters: Identification and openability,.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference Catching MPC cheaters: Identification and openability,

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation ef81deb5-f411-4847-a4b4-f421a8aab7a1 · outbound

This paper cites Publicly account- able robust multi-party computation,.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference Publicly account- able robust multi-party computation,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 0feb0331-a800-43b8-87b7-e73ba5428b21 · outbound

This paper cites Secureml: A system for scalable privacy- preserving machine learning,.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference Secureml: A system for scalable privacy- preserving machine learning,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 82adf0dc-a3d6-42fb-984e-3af44a30963b · outbound

This paper cites MP-SPDZ: A versatile framework for multi-party compu- tation,.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference MP-SPDZ: A versatile framework for multi-party compu- tation,

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:08:15.638603Z digest=sha256:73c577c4246c6d30253f12ab4fcd64289fef1b10621d6f74ed0ce3dcf533a046

Observation a705fb71-889c-4489-ab40-a491dc71cb5e · outbound

This paper cites Homomorphic evaluation of the AES circuit,.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference Homomorphic evaluation of the AES circuit,

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:08:15.738768Z digest=sha256:338468da5b1325b1fffa2cfdcec981e2c4c3012fbdab2856a5c9048cb9c708ca

Observation 951d55cf-bf13-4dfc-bfa2-ceca04a51948 · outbound

This paper cites Overdrive: Making SPDZ great again,.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference Overdrive: Making SPDZ great again,

Reference 11

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:08:15.828795Z digest=sha256:8eaf9eee4af282d22644eed52dae70a2e153e0cd6e0a902021c9b8893449f3ad

Observation 70fddc99-aa0f-4bc9-a814-714521af33c9 · outbound

This paper cites MASCOT: faster malicious arith- metic secure computation with oblivious transfer,.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference MASCOT: faster malicious arith- metic secure computation with oblivious transfer,

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation aa73c9e2-416e-4851-9fb8-36442e32c336 · outbound

This paper cites Multiparty computation with covert security and public verifiability,.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference Multiparty computation with covert security and public verifiability,

Reference 13

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 1141f878-0555-409b-8731-cf732a5da7de · outbound

This paper cites How to generate and exchange secrets (extended abstract),.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference How to generate and exchange secrets (extended abstract),

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 7f77cdfd-09df-444f-9a20-97eab05afd4a · outbound

This paper cites Verifiable secret sharing and multiparty protocols with honest majority,.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference Verifiable secret sharing and multiparty protocols with honest majority,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 2bd8d68e-535b-4653-a665-8294b4348859 · outbound

This paper cites Efficient multiparty computations secure against an adaptive adversary,.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference Efficient multiparty computations secure against an adaptive adversary,

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 350dff88-52f2-465c-961c-fbdb6bc3b629 · outbound

This paper cites Katz and Y.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference Katz and Y

Reference 17

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:08:16.365340Z digest=sha256:e117a4876cf01aa24eeb1d6129e7d3b7ff5fad17ee8280b0dabc1ed8e45755f4

Observation c408cdcd-3da3-4681-8258-1a42957203f2 · outbound

This paper cites Proofs of partial knowl- edge and simplified design of witness hiding protocols,.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference Proofs of partial knowl- edge and simplified design of witness hiding protocols,

Reference 18

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 20c760e2-18bd-46b4-b406-72cd5f07e855 · outbound

This paper cites Fiat-shamir with aborts: Applications to lattice and factoring-based signatures,.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference Fiat-shamir with aborts: Applications to lattice and factoring-based signatures,

Reference 19

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:08:16.586956Z digest=sha256:46fdb9e39316dcee0bdcfa0a1fef7b27f3e1b08764f951de2cc847578dedc163

Observation 2afef642-90cd-4747-a2db-a728a3619921 · outbound

This paper cites Lattice signatures without trapdoors,.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference Lattice signatures without trapdoors,

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation b746f8fc-df1c-4567-866f-ca0bcc923943 · outbound

This paper cites (leveled) fully ho- momorphic encryption without bootstrapping,.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference (leveled) fully ho- momorphic encryption without bootstrapping,

Reference 21

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 5000bce0-fca7-4aa7-bd3e-8d0e431584d0 · outbound

This paper cites Universally composable security: A new paradigm for cryptographic protocols,.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference Universally composable security: A new paradigm for cryptographic protocols,

Reference 22

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation c95827fe-8801-4049-96df-2d9db510aba4 · outbound

This paper cites On ideal lattices and learning with errors over rings,.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference On ideal lattices and learning with errors over rings,

Reference 23

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:08:16.951958Z digest=sha256:4db648b96a6927d98e4dc64cb7df421dfebefbde6fea9e0438e0eb75fb2faf45

Observation e57828d1-15e6-4a8e-9e53-fccd6c51a08d · outbound

This paper cites On the concrete hardness of learning with errors,.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference On the concrete hardness of learning with errors,

Reference 24

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raw_fallback, observed 2026-08-07T12:08:18.541296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:08:17.036285Z digest=sha256:b95fac80852914240fa30618eb969f730ed126960e420a6b6a7bf95a7a3816e8

Observation 6caf0005-401e-4259-9a31-ac12a94b03c7 · outbound

This paper cites Mascot: Faster malicious arithmetic secure computation with oblivious transfer,.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference Mascot: Faster malicious arithmetic secure computation with oblivious transfer,

Reference 25

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raw_fallback, observed 2026-08-07T12:08:18.378910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:08:17.151929Z digest=sha256:bd53c46f609bf739e5ce2d217bb86ed7faa9d0214fad94882a680fa0b219a23e

Observation f8ce7742-d362-45d2-8bb1-0232e313f093 · outbound

This paper cites Spdz2k: Efficient mpc mod 2k for dishonest majority,.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference Spdz2k: Efficient mpc mod 2k for dishonest majority,

Reference 26

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raw_fallback, observed 2026-08-07T12:08:18.217932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:08:17.280042Z digest=sha256:a6e7f9a5eead5bec6fbfc527cae05a227ca73b97fdec6f3e20eb03b6815a1b24

Observation f1e7fc94-c57e-4344-bfba-d4e2e88a7bda · outbound

This paper cites Overdrive: Making spdz great again,.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference Overdrive: Making spdz great again,

Reference 27

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raw_fallback, observed 2026-08-07T12:08:18.087008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:08:17.370246Z digest=sha256:b6603b1e7baff36a8d01c3a62e68b46615be4f33e7e75eedf8a1d49d560b9043

Observation 3f5f1eef-2921-40d1-af44-b5b1f64e9877 · outbound

This paper cites Breast Cancer Wisconsin (Diagnostic).

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference Breast Cancer Wisconsin (Diagnostic)

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:08:17.449476Z digest=sha256:a1f7a7160745d487f0138af8c0357266c44d434deb5fddb0f91926e5474cb19e

Observation c4e0c50a-2786-4607-b844-c6d31eca226a · outbound

This paper cites The use of multiple measurements in taxonomic prob- lems,.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference The use of multiple measurements in taxonomic prob- lems,

Reference 29

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raw_fallback, observed 2026-08-07T12:08:17.843212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:08:17.621396Z digest=sha256:4c6b6d89190dad321a54f5fc5535dd7e18016ce24e8ae403bb86401243d75a3b

Observation 95ef2f89-24ff-460d-8336-7bcb34aea693 · outbound

This paper cites an unresolved cited work.

Robust and Verifiable MPC with Applications to Linear Machine Learning Inference Unresolved cited work

Reference 1995

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no resolver link, observed 2026-08-07T12:08:17.505752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:08:17.505752Z digest=sha256:222aa0cdd0a10bb53dd5133ad38f2ed2b9fa84ece8319d02ec84807af5ea57b3

Pith citing papers

No inbound Pith citation observations are available.