Paper Citation Record · LEDGER

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies

As of 18 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2608.01041.

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

pith.paper-citation-record.v1
2608.01041 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:17:28.195873Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

31 of 31 outbound references displayed

verified exact5
verified fuzzy16
unresolved10
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fe2a2259-ca8c-40ba-bc44-b542039ffeee · outbound

This paper cites Characterizing machine learning-based runtime prefetcher selection,.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Characterizing machine learning-based runtime prefetcher selection,

Reference 1

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Observation b70e7cdf-d491-4aee-8e5b-7191ae7e0f67 · outbound

This paper cites Gaze into the pattern: characterizing spatial patterns with internal temporal correlations for hardware prefetching,.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Gaze into the pattern: characterizing spatial patterns with internal temporal correlations for hardware prefetching,

Reference 2

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Source-reported events for the cited work

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Observation 5c01cca0-7dd0-4b89-84df-55d8db63f6c2 · outbound

This paper cites Simtrace: Capturing over time program phase behavior,.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Simtrace: Capturing over time program phase behavior,

Reference 3

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Source-reported events for the cited work

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Observation efbfabde-bd12-443f-b64e-00754632ed93 · outbound

This paper cites The Championship Simulator: Architectural Simulation for Education and Competition.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies The Championship Simulator: Architectural Simulation for Education and Competition

Reference 4

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Source-reported events for the cited work

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Observation 21695a6d-cd66-475b-8917-95034af9d0de · outbound

This paper cites Barca: Branch agnostic region searching algorithm,.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Barca: Branch agnostic region searching algorithm,

Reference 5

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Source-reported events for the cited work

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Observation 0a1ccefe-d145-4bb4-84c6-6bd9d2a5f7e8 · outbound

This paper cites Using machine learning to guide architecture simulation.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Using machine learning to guide architecture simulation

Reference 6

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Source-reported events for the cited work

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Observation 7e944155-cadf-456c-b854-7bce552234dc · outbound

This paper cites Efficiently exploring architectural design spaces via predictive mod- eling,.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Efficiently exploring architectural design spaces via predictive mod- eling,

Reference 7

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Source-reported events for the cited work

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Observation 38bf0ea0-f88e-4d87-8417-1c498a64846b · outbound

This paper cites Construction and use of linear regression models for processor performance analysis,.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Construction and use of linear regression models for processor performance analysis,

Reference 8

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Observation 584222d1-da1b-4490-82ce-ac4c5fac837d · outbound

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On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies A predictive per- formance model for superscalar processors,

Reference 9

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Source-reported events for the cited work

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Observation 673530ea-bd18-4a51-a3ac-e0d3a565024e · outbound

This paper cites Machine learning-based microarchitecture- level power modeling of cpus,.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Machine learning-based microarchitecture- level power modeling of cpus,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:17:28.644535Z

Source-reported events for the cited work

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Observation b7230d2c-24c0-4bc3-b57f-691cbf5ccafe · outbound

This paper cites Learning-based cpu power model- ing,.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Learning-based cpu power model- ing,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:17:28.635236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 28ba18b6-63dd-450b-897a-7576bd7f977b · outbound

This paper cites Accurate and efficient regression mod- eling for microarchitectural performance and power prediction,.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Accurate and efficient regression mod- eling for microarchitectural performance and power prediction,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:17:28.624741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation df381d9d-ad5b-4503-bacc-daddf670d474 · outbound

This paper cites Illustrative design space studies with microarchitectural regression models,.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Illustrative design space studies with microarchitectural regression models,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:17:28.614356Z

Source-reported events for the cited work

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Observation 9e39d020-8083-41be-a9f9-47a4d25f285d · outbound

This paper cites Machine learning based online performance prediction for runtime parallelization and task scheduling,.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Machine learning based online performance prediction for runtime parallelization and task scheduling,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:17:28.601838Z

Source-reported events for the cited work

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Observation ef1e5965-7fd5-4cbe-9eba-5b2bcc7c1c62 · outbound

This paper cites Learning generalizable program and architecture representations for performance modeling,.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Learning generalizable program and architecture representations for performance modeling,

Reference 15

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Source-reported events for the cited work

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Observation fa73d188-aaf1-482c-b6fb-00ec3357f8ac · outbound

This paper cites Simnet: Accurate and high-performance computer architecture simulation using deep learning,.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Simnet: Accurate and high-performance computer architecture simulation using deep learning,

Reference 16

Resolution: verified exact; doi, observed 2026-08-15T15:17:28.253489Z

Source-reported events for the cited work

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Observation 52b31b54-7795-41ab-a9a3-0aebbff8cd91 · outbound

This paper cites Ithemal: Accurate, portable and fast basic block throughput estimation using deep neural networks,.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Ithemal: Accurate, portable and fast basic block throughput estimation using deep neural networks,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:17:28.581847Z

Source-reported events for the cited work

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Observation 74404e0d-e7a2-48a6-ac7e-47c2e1500503 · outbound

This paper cites Light-weight cache replacement for instruction heavy workloads,.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Light-weight cache replacement for instruction heavy workloads,

Reference 18

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Observation 9f83bd1b-f0e1-4688-8e07-07b73c8f7bbd · outbound

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On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Concorde: Fast and accurate cpu performance modeling with compositional analytical-ml fusion,

Reference 19

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Observation 9411337a-c38c-45c6-883d-69517b1a0350 · outbound

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On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Berti: an accurate local-delta data prefetcher,

Reference 20

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Observation 69a90a1a-9066-4864-91e0-9fc294c52d60 · outbound

This paper cites Scalable deep learning-based microarchitecture simulation on gpus,.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Scalable deep learning-based microarchitecture simulation on gpus,

Reference 21

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Observation 87c3e780-fffd-4574-b057-95477f6f51da · outbound

This paper cites Tao: Re-thinking dl-based microarchitecture simulation,.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Tao: Re-thinking dl-based microarchitecture simulation,

Reference 22

Resolution: verified exact; doi, observed 2026-08-15T15:17:28.242646Z

Source-reported events for the cited work

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Observation a485e897-f059-49fe-b495-4faf35a48619 · outbound

This paper cites Onedse: A unified microprocessor metric prediction and design space exploration framework,.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Onedse: A unified microprocessor metric prediction and design space exploration framework,

Reference 23

Resolution: verified exact; raw_fallback, observed 2026-08-15T15:17:28.439409Z

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Observation fede5e64-5017-4b34-a8e2-93bddc69c0c8 · outbound

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On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies A cost-effective entangling prefetcher for instructions,

Reference 24

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Observation cfddb531-c94a-46cf-95df-2d84c0318556 · outbound

This paper cites Effective mimicry of belady’s min policy,.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Effective mimicry of belady’s min policy,

Reference 25

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Observation a147e312-316e-41d2-b776-dc93522dfa99 · outbound

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On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Granite: A graph neural network model for basic block throughput estimation,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:17:28.534887Z

Source-reported events for the cited work

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Observation 23216d23-25d5-41dc-918f-7af3d7a1051b · outbound

This paper cites Neuroscalar: A deep learning framework for fast, accurate, and in-the-wild cycle-level performance prediction,.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Neuroscalar: A deep learning framework for fast, accurate, and in-the-wild cycle-level performance prediction,

Reference 27

Resolution: verified exact; raw_fallback, observed 2026-08-15T15:17:28.370608Z

Source-reported events for the cited work

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Observation b7839159-2326-43f5-bfa4-409d2ed04c3f · outbound

This paper cites A survey of machine learning for computer architecture and systems,.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies A survey of machine learning for computer architecture and systems,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:17:28.525469Z

Source-reported events for the cited work

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Observation f3d81eae-0fd8-455f-be15-67a2b6fd9b94 · outbound

This paper cites Rank-dse: Neural pareto comparator of microarchitecture design space exploration,.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Rank-dse: Neural pareto comparator of microarchitecture design space exploration,

Reference 29

Resolution: verified exact; doi, observed 2026-08-15T15:17:28.225316Z

Source-reported events for the cited work

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Observation f11158a5-d095-426f-b11d-0f74d5f955d3 · outbound

This paper cites Accurate phase-level cross- platform power and performance estimation,.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Accurate phase-level cross- platform power and performance estimation,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:17:28.516003Z

Source-reported events for the cited work

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Observation 06c0f7a2-30a2-48c7-8157-6fb91695e3a9 · outbound

This paper cites Available: https://doi.org/10.1145/3494523.

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies Available: https://doi.org/10.1145/3494523

Reference 2022

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Source-reported events for the cited work

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Pith citing papers

No inbound Pith citation observations are available.