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Paper Citation Record · LEDGER

Compiling ONNX Neural Network Models Using MLIR

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2008.08272.

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

pith.paper-citation-record.v1
2008.08272 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:52:19.045608Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T22:29:01.081748Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 867c6d68-25de-4b0d-9dcd-11f0f7f0c093 · inbound

FluidML: Fast and Memory Efficient Inference Optimization cites this paper.

FluidML: Fast and Memory Efficient Inference Optimization Compiling ONNX Neural Network Models Using MLIR

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-12T20:56:15.495894Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:56:15.495894Z digest=sha256:51b7224bfe9bbaaf3e0ee4528dd2f95474402082799782099f26e492418865bc

Observation 457d0097-0b57-4cd8-93b1-bf73d0cad007 · inbound

A Multi-level Compiler Backend for Accelerated Micro-kernels Targeting RISC-V ISA Extensions cites this paper.

A Multi-level Compiler Backend for Accelerated Micro-kernels Targeting RISC-V ISA Extensions Compiling ONNX Neural Network Models Using MLIR

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-08T23:48:51.610577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T23:48:51.610577Z digest=sha256:8bd0fe11ea0435e54e944aee2f08544858ef2ef6adc6ce615603832db6455938

Observation 5da1d094-c491-4ef3-896e-47a2bef3a989 · inbound

DejAIvu: Identifying and Explaining AI Art on the Web in Real-Time with Saliency Maps cites this paper.

DejAIvu: Identifying and Explaining AI Art on the Web in Real-Time with Saliency Maps Compiling ONNX Neural Network Models Using MLIR

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-07T23:37:01.351277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T23:37:01.351277Z digest=sha256:965cc4bb25111a7f65cd629c9675df139d20348cf05378e413c6d3f065f99ac8

Observation e898757b-3198-4b31-8a82-f111159ab967 · inbound

Rulebook: bringing co-routines to reinforcement learning environments cites this paper.

Rulebook: bringing co-routines to reinforcement learning environments Compiling ONNX Neural Network Models Using MLIR

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-16T05:52:19.045608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:52:19.045608Z digest=sha256:6a1710addca67e4325fcac8b54861b627c2adf9fd0b38459cadec5b087880db8

Observation 2fbd6698-31a0-4564-8fee-f31ad5e5b84b · inbound

WAMI: Compilation to WebAssembly through MLIR without Losing Abstraction cites this paper.

WAMI: Compilation to WebAssembly through MLIR without Losing Abstraction Compiling ONNX Neural Network Models Using MLIR

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-06T23:50:07.651147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:50:07.651147Z digest=sha256:07673e1cf7e71a0b52bbb4a1c8550a19299944994bed7c4726a382aeadcf172d

Observation 531f5d7d-7dcd-43b2-83df-f98de157ebff · inbound

Chat-Ghosting: A Comparative Study of Methods for Auto-Completion in Dialog Systems cites this paper.

Chat-Ghosting: A Comparative Study of Methods for Auto-Completion in Dialog Systems Compiling ONNX Neural Network Models Using MLIR

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-06T19:19:10.082227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:19:10.082227Z digest=sha256:793e288b13d7fe77b838cfeb5628fe2eab65dea72a8ef5eec232578217d281b5

Observation 10177488-b553-4498-9659-11bcd74c5eb4 · inbound

Mind Meets Space: Rethinking Agentic Spatial Intelligence from a Neuroscience-inspired Perspective cites this paper.

Mind Meets Space: Rethinking Agentic Spatial Intelligence from a Neuroscience-inspired Perspective Compiling ONNX Neural Network Models Using MLIR

Reference 94

Resolution
unresolved
no resolver link, observed 2026-08-04T19:39:05.493826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:39:05.493826Z digest=sha256:041371dab366b196e8740553283a07e59dbf06a725559d41322ed3a9544570ca

Observation be4090b4-7e5f-4d27-a9f8-56895a4efd83 · inbound

Tensor Algebraic Property Skeletons: Amplifying Property-Based Testing for AI Compilers cites this paper.

Tensor Algebraic Property Skeletons: Amplifying Property-Based Testing for AI Compilers Compiling ONNX Neural Network Models Using MLIR

Reference 11

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T15:17:07.566893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-28T00:00:07.129336Z digest=sha256:d8abf9d073cc19649eab9dbb5d229dddf52418ec07e0a61c50cf8619880bcd82

Observation da951a0c-1636-4f6a-a23f-cfd8cf1f30ff · inbound

Finding Compiler-Platform Interaction Bugs in Deep Learning Pipelines via Cross-Layer Constraints cites this paper.

Finding Compiler-Platform Interaction Bugs in Deep Learning Pipelines via Cross-Layer Constraints Compiling ONNX Neural Network Models Using MLIR

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-07-03T22:29:01.083094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-26T23:30:03.186368Z digest=sha256:9bb04033c095ef85bfdeeea9984e3af564f35d3a529b654f1b4347a99a1cf47b

Observation 3b471db9-e75b-4665-a872-d199f64de548 · inbound

MLIR for Quantum Beyond Gate Cancellation: Quantum Circuit Mapping Reimagined cites this paper.

MLIR for Quantum Beyond Gate Cancellation: Quantum Circuit Mapping Reimagined Compiling ONNX Neural Network Models Using MLIR

Reference 7

Resolution
unresolved
no resolver link, observed 2026-07-12T08:54:39.253884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T08:54:39.253884Z digest=sha256:0a90de8283998407fb1137b15d35b79494799937e3809babc2019d7ff2bd8a0a