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Paper Citation Record · LEDGER

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement

As of 8 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2507.21271.

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

pith.paper-citation-record.v1
2507.21271 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T12:59:48.229723Z

measured 38 of 38 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

38 of 38 outbound references displayed

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  • verified fuzzy20
  • unresolved16
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9b0bbf4d-2f52-4c0e-a154-ea56c1581803 · outbound

This paper cites Pan-cancer computational histopathology reveals mutations, tumor composition and prognosis,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Pan-cancer computational histopathology reveals mutations, tumor composition and prognosis,

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 5d031dd4-ce53-407b-96fd-5f2d53fb310e · outbound

This paper cites Apolloauto,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Apolloauto,

Reference 2

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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 760f72c4-f235-42f8-9f80-d6d18c398b0c · outbound

This paper cites Meshcnn: a network with an edge,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Meshcnn: a network with an edge,

Reference 3

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Source-reported events for the cited work

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Observation 945914e8-cead-4e23-9b2e-eb2ce7581888 · outbound

This paper cites Testing of autonomous driving systems: where are we and where should we go?.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Testing of autonomous driving systems: where are we and where should we go?

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 0f0b7fbc-a2e4-407a-b027-8779c7f3ae56 · outbound

This paper cites An open- source machine-learning application for predicting pixel-to-pixel ndvi regression from rgb calibrated images,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement An open- source machine-learning application for predicting pixel-to-pixel ndvi regression from rgb calibrated images,

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 a2734cf3-c748-4e21-b31a-34f3074dd24d · outbound

This paper cites Omniseg3d: Omniversal 3d segmentation via hierarchical contrastive learning,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Omniseg3d: Omniversal 3d segmentation via hierarchical contrastive learning,

Reference 6

Resolution
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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 927cc975-2d0e-4041-992f-ee057142634e · outbound

This paper cites American fuzzy lop.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement American fuzzy lop

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 b125d03d-8624-45f0-9d1a-4faf22e0ae05 · outbound

This paper cites Saffron: Adaptive grammar-based fuzzing for worst-case analysis,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Saffron: Adaptive grammar-based fuzzing for worst-case analysis,

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 da84fcb0-d9b6-4913-8a0e-c0af14126b50 · outbound

This paper cites Open3D: A Modern Library for 3D Data Processing.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Open3D: A Modern Library for 3D Data Processing

Reference 9

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Unavailable: canonical work link unavailable.

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Observation 7cf06097-1ff4-4531-bf0a-006573c0aff2 · outbound

This paper cites [Online].

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement [Online]

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.

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Observation a1437e9b-357d-46c4-8065-dd8b9d048d92 · outbound

This paper cites Deepsdf: Learning continuous signed distance functions for shape rep- resentation,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Deepsdf: Learning continuous signed distance functions for shape rep- resentation,

Reference 11

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Unavailable: canonical work link unavailable.

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Observation a7a1578b-ece5-4f7d-af4d-43eabde1ed93 · outbound

This paper cites Cfd vision 2030 study: A path to revolutionary computational aerosciences,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Cfd vision 2030 study: A path to revolutionary computational aerosciences,

Reference 12

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verified fuzzy
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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 43476fed-c04e-475c-be4a-7cd7f482e3dc · outbound

This paper cites 3d adversarial attacks beyond point cloud,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement 3d adversarial attacks beyond point cloud,

Reference 13

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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 a9848b51-480a-4154-a846-68880eeae20d · outbound

This paper cites Black box fairness testing of machine learning models,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Black box fairness testing of machine learning models,

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 47b93af7-0937-4148-938c-56ff3f62e4e9 · outbound

This paper cites Input invariants,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Input invariants,

Reference 16

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Unavailable: canonical work link unavailable.

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Observation d24efa80-690b-4f47-afdf-cb7b6564e6b5 · outbound

This paper cites FAUST: Dataset and evaluation for 3D mesh registration,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement FAUST: Dataset and evaluation for 3D mesh registration,

Reference 17

Resolution
verified fuzzy
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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 f5b821ca-ebd6-466c-a36f-39373af74a4b · outbound

This paper cites ShapeNet: An Information-Rich 3D Model Repository.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement ShapeNet: An Information-Rich 3D Model Repository

Reference 18

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Observation 71718c2c-7aa3-4625-b501-0d77419be69b · outbound

This paper cites Hodgenet: Learning spectral geometry on triangle meshes,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Hodgenet: Learning spectral geometry on triangle meshes,

Reference 19

Resolution
verified fuzzy
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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 1b85c041-ac08-48a2-92ff-5e8bee63b1cc · outbound

This paper cites 3D ShapeNets: A Deep Representation for Volumetric Shapes.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement 3D ShapeNets: A Deep Representation for Volumetric Shapes

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 24752259-fe72-4001-8751-2c4455489a35 · outbound

This paper cites Meshsdf: Differentiable iso-surface extraction,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Meshsdf: Differentiable iso-surface extraction,

Reference 21

Resolution
verified fuzzy
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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 e4a9dfe2-2b21-4b01-a6ea-269c2a5051f2 · outbound

This paper cites Point2mesh: a self-prior for deformable meshes,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Point2mesh: a self-prior for deformable meshes,

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation fbff4bf3-c961-4cf4-8e9b-ed9b90a4a7d9 · outbound

This paper cites Active co-analysis of a set of shapes,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Active co-analysis of a set of shapes,

Reference 23

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Unavailable: canonical work link unavailable.

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Observation 7ff2ab07-7900-4bed-ab66-6954b262cd31 · outbound

This paper cites Meshwalker: Deep mesh understanding by random walks,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Meshwalker: Deep mesh understanding by random walks,

Reference 24

Resolution
verified fuzzy
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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 7d2dd841-1eef-4e84-96d5-366a7017f90e · outbound

This paper cites 3D menagerie: Modeling the 3D shape and pose of animals,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement 3D menagerie: Modeling the 3D shape and pose of animals,

Reference 25

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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 792144a5-07d8-4188-a73e-1e5e2a44cdf8 · outbound

This paper cites DeepGCNs: Can GCNs Go as Deep as CNNs?.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement DeepGCNs: Can GCNs Go as Deep as CNNs?

Reference 26

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Unavailable: canonical work link unavailable.

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Observation 0f9a7121-412f-4558-b110-9377a24750d4 · outbound

This paper cites Boundary-aware geometric encoding for semantic segmentation of point clouds,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Boundary-aware geometric encoding for semantic segmentation of point clouds,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:59:50.429439Z

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 7759bfc9-fc51-4a98-bbe7-5115ba61cfcf · outbound

This paper cites Human3.6m: Large scale datasets and predictive methods for 3d human sensing in natural environments,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Human3.6m: Large scale datasets and predictive methods for 3d human sensing in natural environments,

Reference 28

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verified fuzzy
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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 145abbcd-7b9b-4c72-868d-1c7cc8da362c · outbound

This paper cites SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters

Reference 29

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Unavailable: canonical work link unavailable.

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Observation a46dd9be-0a60-446c-83bc-6ddf0e6718f8 · outbound

This paper cites Evaluating fuzz testing,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Evaluating fuzz testing,

Reference 30

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:59:47.364393Z digest=sha256:99ef8a3830726835095fc597f009b9321984f165f13c7df828449b43ac535643

Observation 9ea799d7-f4e0-4874-b320-241feb184870 · outbound

This paper cites Token-Level fuzzing,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Token-Level fuzzing,

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-06T12:59:50.105677Z

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 49d5059e-1841-4480-ae2a-cb9a1014b1c2 · outbound

This paper cites Skyfire: Data-driven seed generation for fuzzing,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Skyfire: Data-driven seed generation for fuzzing,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:59:49.930818Z

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 2d8d7e16-fe76-425f-b98f-4ff683db6f0e · outbound

This paper cites Superion: grammar-aware greybox fuzzing,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Superion: grammar-aware greybox fuzzing,

Reference 33

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e4cc783c-b360-4f2c-8c0d-8e17df5c5a90 · outbound

This paper cites Graphfuzz: Library api fuzzing with lifetime-aware dataflow graphs,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Graphfuzz: Library api fuzzing with lifetime-aware dataflow graphs,

Reference 34

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:59:47.775397Z digest=sha256:08bfff7b6d00aa988845274aeb3cfc8d29e5336aa09cddf52e136be4a0d92cce

Observation a73b6d3b-9372-46fd-b668-f1f69fbb45f2 · outbound

This paper cites Nnsmith: Generating diverse and valid test cases for deep learning compilers,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Nnsmith: Generating diverse and valid test cases for deep learning compilers,

Reference 35

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Unavailable: canonical work link unavailable.

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Observation 34fbe163-5b72-4611-be53-cff5a7434469 · outbound

This paper cites Neuri: Diversifying dnn generation via inductive rule inference,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Neuri: Diversifying dnn generation via inductive rule inference,

Reference 36

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Unavailable: canonical work link unavailable.

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Observation a71f62cb-a893-48bd-8936-8dde55eea52b · outbound

This paper cites Adversarial testing with rein- forcement learning: A case study on autonomous driving,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Adversarial testing with rein- forcement learning: A case study on autonomous driving,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:59:49.729965Z

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=2026-08-06T12:59:48.119017Z digest=sha256:7e6e094e817cbe13ba9e75ea6504094b139127019ce620caa6c96fd7efb45349

Observation e462fd53-125e-4462-af53-4ece1dee4308 · outbound

This paper cites Towards understanding the effectiveness of large language models on directed test input generation,.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement Towards understanding the effectiveness of large language models on directed test input generation,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:59:49.553997Z

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=2026-08-06T12:59:48.229723Z digest=sha256:9628c6b52a719299a1d883748e1b2b8731e77464598156901adaa43c6982f6fd

Observation 9adec5ac-1ffe-46a0-9038-e11d9998a7f7 · outbound

This paper cites MeshSDF: Differentiable Iso-Surface Extraction.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement MeshSDF: Differentiable Iso-Surface Extraction

Reference 2020

Resolution
metadata mismatch
local_arxiv, observed 2026-08-06T12:59:48.966625Z

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=2026-08-06T12:59:46.455001Z digest=sha256:3b7400585cf63573e047ec702e12b5933e93ac25bc51ef0b67e82c6266e92dc6

Pith citing papers

No inbound Pith citation observations are available.