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Paper Citation Record · LEDGER

A Near-Linear-Time Solver for Graph $p$-Laplacian Semi-Supervised Learning via Continuation in $p$

As of 15 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2607.03503.

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

pith.paper-citation-record.v1
2607.03503 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-12T02:02:31.229058Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

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External citation measurements

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Outbound references

Observation f5be5cfd-6324-4158-8405-1de58ccfc1d2 · outbound

This paper cites NLF: A Resistor-Network Framework and Linear-Time Solver for Convex Network-Flow Equilibria.

A Near-Linear-Time Solver for Graph $p$-Laplacian Semi-Supervised Learning via Continuation in $p$ NLF: A Resistor-Network Framework and Linear-Time Solver for Convex Network-Flow Equilibria

Reference 1

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source=pdf_text observed=2026-07-12T02:02:31.229058Z digest=sha256:d93a0a7467e4b03d91c538d3fc8df6ef86bdd190a182c5c3f0675dacbf1b8135

Observation 98dc7acd-9954-4e89-a1cd-85f4ff1412c2 · outbound

This paper cites Nadler, N.

A Near-Linear-Time Solver for Graph $p$-Laplacian Semi-Supervised Learning via Continuation in $p$ Nadler, N

Reference 2

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source=pdf_text observed=2026-07-12T02:02:31.229058Z digest=sha256:898db432ffa15f405e2c24c2678ae31fc130a1bce66fb7c0320e43420379290e

Observation 3c2ef10b-989f-4911-9ca9-01680104ba85 · outbound

This paper cites Slepˇ cev and M.

A Near-Linear-Time Solver for Graph $p$-Laplacian Semi-Supervised Learning via Continuation in $p$ Slepˇ cev and M

Reference 3

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source=pdf_text observed=2026-07-12T02:02:31.229058Z digest=sha256:58391465c207af3a225fff5123cd9aa3b4dd61826fdb7e65647a0b9059068edb

Observation b5cf19a9-e592-4368-bf7d-f923d6b61360 · outbound

This paper cites El Alaoui, X.

A Near-Linear-Time Solver for Graph $p$-Laplacian Semi-Supervised Learning via Continuation in $p$ El Alaoui, X

Reference 4

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source=pdf_text observed=2026-07-12T02:02:31.229058Z digest=sha256:07655091f6bc81c3d18c5d4328b33cd15e1b6d1ae86acfc5e147fb049d338bb4

Observation 29db2f77-b948-4f7f-97cd-72b79aad2148 · outbound

This paper cites Calder,The game theoreticp-Laplacian and semi-supervised learning with few labels, Non- linearity, 32 (2019), pp.

A Near-Linear-Time Solver for Graph $p$-Laplacian Semi-Supervised Learning via Continuation in $p$ Calder,The game theoreticp-Laplacian and semi-supervised learning with few labels, Non- linearity, 32 (2019), pp

Reference 5

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source=pdf_text observed=2026-07-12T02:02:31.229058Z digest=sha256:e5d3ac8c091fd6b27eaed8922ebcdb052133da2942e2147ea810db6298386329

Observation 13286f5a-cac7-4cda-aa3d-176389378b56 · outbound

This paper cites Calder, B.

A Near-Linear-Time Solver for Graph $p$-Laplacian Semi-Supervised Learning via Continuation in $p$ Calder, B

Reference 6

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Observation c73fec47-8734-411f-be5e-cd89bba9e905 · outbound

This paper cites Flores, J.

A Near-Linear-Time Solver for Graph $p$-Laplacian Semi-Supervised Learning via Continuation in $p$ Flores, J

Reference 7

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source=pdf_text observed=2026-07-12T02:02:31.229058Z digest=sha256:0cab7b696e16f412dfc88d25cee76129d433df11165ea8e44faee844d3bcd64b

Observation deb96915-456b-49ee-99a2-d658936bbece · outbound

This paper cites Storn,The dual IRLS scheme for (hyper-)graphp-Laplacians andℓ p regression with large exponents, arXiv:2603.26061, 2026.

A Near-Linear-Time Solver for Graph $p$-Laplacian Semi-Supervised Learning via Continuation in $p$ Storn,The dual IRLS scheme for (hyper-)graphp-Laplacians andℓ p regression with large exponents, arXiv:2603.26061, 2026

Reference 8

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source=pdf_text observed=2026-07-12T02:02:31.229058Z digest=sha256:a287f2f2543740c9d4b079df8c2e7bde59c5dcf94b46b5af2517b8be4d84b7ef

Observation fb88f87b-0aa3-4804-b4ce-2393303d7b4c · outbound

This paper cites an unresolved cited work.

A Near-Linear-Time Solver for Graph $p$-Laplacian Semi-Supervised Learning via Continuation in $p$ Unresolved cited work

Reference 9

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source=pdf_text observed=2026-07-12T02:02:31.229058Z digest=sha256:f5aed9f46e044ea1ab019e2e602372bbebf0b44cb6438cb108d36fac363fc53e

Observation 44beb2e1-6536-47a3-a237-d499ad1c4261 · outbound

This paper cites an unresolved cited work.

A Near-Linear-Time Solver for Graph $p$-Laplacian Semi-Supervised Learning via Continuation in $p$ Unresolved cited work

Reference 10

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source=pdf_text observed=2026-07-12T02:02:31.229058Z digest=sha256:afdf15a4021b3b0947cbea609c04487c5841c70a05aa99afe8cd8bd18782c6f8

Observation e40029b4-ad60-4070-a9ef-fdadc78f053f · outbound

This paper cites Hein and J.-Y.

A Near-Linear-Time Solver for Graph $p$-Laplacian Semi-Supervised Learning via Continuation in $p$ Hein and J.-Y

Reference 11

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source=pdf_text observed=2026-07-12T02:02:31.229058Z digest=sha256:ee163b438f7dbf0f700c8c545e1f6f6e2dd2daa66dc049d1c5ffa46de4c84fb2

Observation 78712db7-39a8-4cad-9467-42bea1e9e03d · outbound

This paper cites an unresolved cited work.

A Near-Linear-Time Solver for Graph $p$-Laplacian Semi-Supervised Learning via Continuation in $p$ Unresolved cited work

Reference 12

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source=pdf_text observed=2026-07-12T02:02:31.229058Z digest=sha256:7500d141d234c8dbab43accfce536b2419606da25448cec2fbcb3847c63ee3db

Observation fd74be45-112c-46fd-aed5-4d21b3107d33 · outbound

This paper cites Kyng and S.

A Near-Linear-Time Solver for Graph $p$-Laplacian Semi-Supervised Learning via Continuation in $p$ Kyng and S

Reference 13

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source=pdf_text observed=2026-07-12T02:02:31.229058Z digest=sha256:ed84aa1e86d594b505176bfa72b5e09e8d68e1457ea994723a82d97facb26abe

Observation 499c32f6-067d-46fe-928e-38f52a4b02ed · outbound

This paper cites an unresolved cited work.

A Near-Linear-Time Solver for Graph $p$-Laplacian Semi-Supervised Learning via Continuation in $p$ Unresolved cited work

Reference 14

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source=pdf_text observed=2026-07-12T02:02:31.229058Z digest=sha256:19233e2283e3e7e3c3fec5c59ef46a356d62aa863fdfc097c664cce521956383

Observation 5f8345d2-ce6e-4abe-acf7-0d9365201dfc · outbound

This paper cites Nocedal and S.

A Near-Linear-Time Solver for Graph $p$-Laplacian Semi-Supervised Learning via Continuation in $p$ Nocedal and S

Reference 15

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source=pdf_text observed=2026-07-12T02:02:31.229058Z digest=sha256:0e26e83e6bec5453f357b20f5b2669cc5b7400ba3a5a95e76ee69680530afe73

Observation b7ccf9a1-6a1d-4c74-8e87-ddbb0a89ee8c · outbound

This paper cites an unresolved cited work.

A Near-Linear-Time Solver for Graph $p$-Laplacian Semi-Supervised Learning via Continuation in $p$ Unresolved cited work

Reference 16

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source=pdf_text observed=2026-07-12T02:02:31.229058Z digest=sha256:98e606a3de46cdc2e5d1b32a795fbf7055d993d674a4597d274c2a9465faa7e7

Observation 2e6e9858-88dd-4c6a-8c43-3f97cccc9fec · outbound

This paper cites LAMG+: A Robust Lean Algebraic Multigrid Solver for Graph Laplacians.

A Near-Linear-Time Solver for Graph $p$-Laplacian Semi-Supervised Learning via Continuation in $p$ LAMG+: A Robust Lean Algebraic Multigrid Solver for Graph Laplacians

Reference 17

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source=pdf_text observed=2026-07-12T02:02:31.229058Z digest=sha256:4b54c233559f89107798096668b26858d9012bfbc74651d5c69739b87b5cbb1e

Observation 51cbb44d-b0ce-4630-bf84-8a21186e82a5 · outbound

This paper cites Huang, H.

A Near-Linear-Time Solver for Graph $p$-Laplacian Semi-Supervised Learning via Continuation in $p$ Huang, H

Reference 18

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source=pdf_text observed=2026-07-12T02:02:31.229058Z digest=sha256:df0059b48762689f1a5708896d72fed8158c6163c5b43a4a8b00efa46dfe5e38

Observation 63684015-0727-44aa-bd1c-4003626b058a · outbound

This paper cites Resurrecting Label Propagation for Graphs with Heterophily and Label Noise.

A Near-Linear-Time Solver for Graph $p$-Laplacian Semi-Supervised Learning via Continuation in $p$ Resurrecting Label Propagation for Graphs with Heterophily and Label Noise

Reference 19

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source=pdf_text observed=2026-07-12T02:02:31.229058Z digest=sha256:3f2dadb584958863544c652dc2a68450cf76cdcd02803f7f9cb383d17897083a

Observation 91979ecf-6c66-41dc-8938-89fd6b02ab04 · outbound

This paper cites an unresolved cited work.

A Near-Linear-Time Solver for Graph $p$-Laplacian Semi-Supervised Learning via Continuation in $p$ Unresolved cited work

Reference 20

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source=pdf_text observed=2026-07-12T02:02:31.229058Z digest=sha256:0922132117bf33b40fe832e68a48a8205d3b8b4e53c0d628b91965de7d0a19b2

Pith citing papers

No inbound Pith citation observations are available.