Paper Citation Record · LEDGER

MLPerf Tiny Benchmark

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2106.07597.

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

pith.paper-citation-record.v1
2106.07597 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:09:32.933918Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T02:55:53.494035Z

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 ff09f248-ddb9-4699-887d-6d1adbe8f715 · inbound

Wake Vision: A Tailored Dataset and Benchmark Suite for TinyML Computer Vision Applications cites this paper.

Wake Vision: A Tailored Dataset and Benchmark Suite for TinyML Computer Vision Applications MLPerf Tiny Benchmark

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-24T01:08:41.928544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation b3b818d6-0b18-4bbb-9fa2-e790c5b42821 · inbound

Flexible Vector Integration in Embedded RISC-V SoCs for End to End CNN Inference Acceleration cites this paper.

Flexible Vector Integration in Embedded RISC-V SoCs for End to End CNN Inference Acceleration MLPerf Tiny Benchmark

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T16:09:32.933918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d4734d2-6541-4c7e-82c9-f425f9595bdc · inbound

Real-Time Performance Benchmarking of TinyML Models in Embedded Systems (PICO: Performance of Inference, CPU, and Operations) cites this paper.

Real-Time Performance Benchmarking of TinyML Models in Embedded Systems (PICO: Performance of Inference, CPU, and Operations) MLPerf Tiny Benchmark

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T05:59:51.067059Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2b5002d-42f3-4246-9fd4-2b028f198400 · inbound

Ariel-ML: Computing Parallelization with Embedded Rust for Neural Networks on Heterogeneous Multi-core Microcontrollers cites this paper.

Ariel-ML: Computing Parallelization with Embedded Rust for Neural Networks on Heterogeneous Multi-core Microcontrollers MLPerf Tiny Benchmark

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-03T17:24:26.197603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae6129ac-7bc0-4663-9604-3ef07bcfc7fb · inbound

Design Rules for Extreme-Edge Scientific Computing on AI Engines cites this paper.

Design Rules for Extreme-Edge Scientific Computing on AI Engines MLPerf Tiny Benchmark

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-11T13:06:05.521545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 686ac15f-a227-4666-99b7-0cf926a16c67 · inbound

Are Large Language Models Economically Viable for Industry Deployment? cites this paper.

Are Large Language Models Economically Viable for Industry Deployment? MLPerf Tiny Benchmark

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-11T13:01:20.353349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation fb75ef33-d277-4386-b014-85c06a7565cb · inbound

A Fully Tunable Ultra-Low Power Current-Mode Memory Cell in Standard CMOS Technology cites this paper.

A Fully Tunable Ultra-Low Power Current-Mode Memory Cell in Standard CMOS Technology MLPerf Tiny Benchmark

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-11T03:20:56.108853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 88cbba5b-de60-4451-acdd-89405e8338b7 · inbound

A Fully Tunable Ultra-Low Power Current-Mode Memory Cell in Standard CMOS Technology cites this paper.

A Fully Tunable Ultra-Low Power Current-Mode Memory Cell in Standard CMOS Technology MLPerf Tiny Benchmark

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-20T22:49:10.376572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 68b7077c-c1f3-4d8d-87d1-0a3c0484e447 · inbound

QuIDE: Mastering the Quantized Intelligence Trade-off via Active Optimization cites this paper.

QuIDE: Mastering the Quantized Intelligence Trade-off via Active Optimization MLPerf Tiny Benchmark

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-13T07:52:32.341381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 43fef4f5-0840-4577-9813-ea80c5f7ec15 · inbound

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations cites this paper.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations MLPerf Tiny Benchmark

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-20T22:09:07.264633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ff70bbb9-4f2d-4ba2-b20d-e173899b1c71 · inbound

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations cites this paper.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations MLPerf Tiny Benchmark

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:05:46.340205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation d512dca2-2df3-4f78-99be-17008ae256da · inbound

Perforated Neural Networks for Keyword Spotting cites this paper.

Perforated Neural Networks for Keyword Spotting MLPerf Tiny Benchmark

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-20T21:13:44.818066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 28373b91-2567-4615-ae97-d2e682ab8820 · inbound

OpenGlass: Ultra-Low-Power On-Device AI Eyewear with Event-based Vision cites this paper.

OpenGlass: Ultra-Low-Power On-Device AI Eyewear with Event-based Vision MLPerf Tiny Benchmark

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-07-02T17:27:15.080350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 2fa0aaf9-1cb5-45be-9346-41cfdfe39fde · inbound

Breaking TinyML: Why Quantized Neural Networks Need Domain-Specific Security Analysis cites this paper.

Breaking TinyML: Why Quantized Neural Networks Need Domain-Specific Security Analysis MLPerf Tiny Benchmark

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-12T14:06:47.857777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d03f2752-f7a4-47e6-86b2-c7d6c476e2aa · inbound

Efficient Network Inference via Hardware-Aware Architecture Search, Model Pruning & Quantization cites this paper.

Efficient Network Inference via Hardware-Aware Architecture Search, Model Pruning & Quantization MLPerf Tiny Benchmark

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-07-04T09:49:45.040981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 57eff531-f8b7-415f-a30f-9623b599e7f1 · inbound

AdvScan: Black-Box Adversarial Example Detection at Runtime through Power Analysis cites this paper.

AdvScan: Black-Box Adversarial Example Detection at Runtime through Power Analysis MLPerf Tiny Benchmark

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-07-01T16:55:50.973127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation c30300be-bc0c-489a-9b83-5af0a5ad5b2a · inbound

ECGLight: Compute-Light Framework For Paper ECG Digitization and Myocardial Infarction Screening cites this paper.

ECGLight: Compute-Light Framework For Paper ECG Digitization and Myocardial Infarction Screening MLPerf Tiny Benchmark

Reference 33

Resolution: metadata mismatch; local_arxiv, observed 2026-07-09T02:55:53.495667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.