Methods › General › Cache Replacement Models › Parrot

Parrot

17 papers tagged archive 2025-07-28

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

Parrot is an imitation learning approach to automatically learn cache access patterns by leveraging Belady’s optimal policy. Belady’s optimal policy is an oracle policy that computes the theoretically optimal cache eviction decision based on knowledge of future cache accesses, which Parrot approximates with a policy that only conditions on the past accesses.

Source: An Imitation Learning Approach for Cache Replacement

Papers archive 2025-07-28

17 shown of 17, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

20 shown of 29 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Position2
4k1
Attribute1
Autonomous Driving1
Autonomous Navigation1
Classification1
Decision Making1
Drone navigation1
Ethics1
Image Classification1
Image Generation1
Image-to-Image Translation1
Imitation Learning1
In-Context Learning1
Instruction Following1
Memorization1
Mixture-of-Experts1
Model Predictive Control1
Navigate1
Object Detection1

Usage over time archive 2025-07-28

Papers per year tagged with Parrot: 2020 to 2025, peak 8 8 0 2020: 2 papers 2020 2021: 2 papers 2021 2022: 0 papers 2022 2023: 2 papers 2023 2024: 8 papers 2024 2025: 3 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (17 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Cache Replacement Models

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