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Paper Citation Record · LEDGER

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning

As of 15 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 0 inbound Pith citation observations for arXiv:2506.01880.

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

pith.paper-citation-record.v1
2506.01880 v1

Coverage vector

measured 61 of 61 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:37:18.710415Z

measured 61 of 61 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

61 of 61 outbound references displayed

  • verified exact9
  • verified fuzzy9
  • unresolved40
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d9e0bcef-02d8-4d62-896b-cf77f205f09d · outbound

This paper cites an unresolved cited work.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 1

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Observation 148c244b-3260-431b-9627-81ab7e8b563b · outbound

This paper cites Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation

Reference 2

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Observation 52a21e26-4491-4c69-bfdf-6e914260ce9b · outbound

This paper cites an unresolved cited work.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 3

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Observation 9c3bd9bc-6907-4b6a-9cfb-ee14709e4cbf · outbound

This paper cites The Potential of Synergistic Static, Dynamic and Speculative Loop Nest Optimizations for Automatic Parallelization.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning The Potential of Synergistic Static, Dynamic and Speculative Loop Nest Optimizations for Automatic Parallelization

Reference 4

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Observation baf53c50-87f4-4a3f-8d2d-3b7abb1db5a6 · outbound

This paper cites an unresolved cited work.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 5

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Observation 325f30e6-f067-4a7d-be15-b02cc175af94 · outbound

This paper cites PENCIL: Towards a Platform-Neutral Compute Intermediate Language for DSLs.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning PENCIL: Towards a Platform-Neutral Compute Intermediate Language for DSLs

Reference 6

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Observation c3ec9938-1862-471c-92c4-2030cc6b1711 · outbound

This paper cites TIRAMISU: A Polyhedral Compiler for Dense and Sparse Deep Learning.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning TIRAMISU: A Polyhedral Compiler for Dense and Sparse Deep Learning

Reference 7

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Observation 8d771028-4873-453b-9ff8-25925c2a3ccd · outbound

This paper cites an unresolved cited work.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 8

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Observation 2340a3a1-f64b-4c0b-b82c-6ce0b8028725 · outbound

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Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 9

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Observation 4f0f6aeb-3549-4a67-8860-7544bf9682e8 · outbound

This paper cites Tiramisu: A Polyhedral Compiler for Expressing Fast and Portable Code.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Tiramisu: A Polyhedral Compiler for Expressing Fast and Portable Code

Reference 10

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Observation 1ca3ee93-e2d0-4317-9903-ed6bde177b3b · outbound

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Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 11

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Observation f22fae0d-0e6c-4466-8d05-7bf965eabbce · outbound

This paper cites an unresolved cited work.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 12

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Observation 29c48f63-10cc-47d1-a14f-4dae85210f96 · outbound

This paper cites Ramanujam, and P.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Ramanujam, and P

Reference 13

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Observation e755675e-c129-468f-9162-fb44d386a1cb · outbound

This paper cites A Reinforcement Learning Environment for Polyhedral Optimizations.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning A Reinforcement Learning Environment for Polyhedral Optimizations

Reference 14

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Observation d23d964d-0954-4a11-aa60-f76933c4d75d · outbound

This paper cites How Attentive are Graph Attention Networks?.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning How Attentive are Graph Attention Networks?

Reference 15

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Observation e9d2cc3c-4d23-4b4c-9301-fd1bdfc6c4c5 · outbound

This paper cites TVM: An Automated End-to-End Optimizing Compiler for Deep Learning.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning TVM: An Automated End-to-End Optimizing Compiler for Deep Learning

Reference 16

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Observation 611d3cad-8814-4f65-963a-a4bd9e578320 · outbound

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Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 17

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Observation 4abf6fa5-832d-418e-9dd7-0ab7d228daec · outbound

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Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 18

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Observation 257c224a-9e5e-4bee-8bfb-7f43f7fba2bd · outbound

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Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 19

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Observation ad3330d7-4a32-4f05-94fc-0db2e6495881 · outbound

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Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Feautrier

Reference 20

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Observation 0594b605-903f-4322-b341-46515b4e6b2d · outbound

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Pearl: Automatic Code Optimization Using Deep Reinforcement Learning 2011.Polyhedron Model

Reference 21

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Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 22

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Observation 6c0ee80d-cb00-4aaf-a1a5-337b211ab03b · outbound

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Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Sadayappan, and Sven Verdoolaege

Reference 23

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Observation 31fcf7ce-ef14-47ad-bd8a-697c86c0967c · outbound

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Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 24

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Observation ae3fcefc-d6f2-4582-a030-509d20fd1d67 · outbound

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Pearl: Automatic Code Optimization Using Deep Reinforcement Learning ProTuner: Tuning Programs with Monte Carlo Tree Search

Reference 25

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Observation 551344b0-a107-4642-a3c6-3b4ae9322ada · outbound

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Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 26

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Observation 363b4a71-5b76-4533-b609-81a2c79fb1b8 · outbound

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Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 27

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Observation d9228d05-c3d3-471c-89e8-f1ce3bdd49aa · outbound

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Pearl: Automatic Code Optimization Using Deep Reinforcement Learning X-RLflow: Graph Reinforcement Learning for Neural Network Subgraphs Transformation

Reference 28

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Observation 90a25505-0082-4ad9-873e-1126f77be879 · outbound

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Pearl: Automatic Code Optimization Using Deep Reinforcement Learning AutoPhase: Juggling HLS Phase Orderings in Random Forests with Deep Reinforcement Learning

Reference 29

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Observation 2d9b89af-9f1d-47b1-8fa2-95ecb47131cf · outbound

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Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 30

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Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Irigoin and R

Reference 31

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Observation 5fad93f1-e3ed-4ee1-9241-d8e2d3817ace · outbound

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Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Semi-Supervised Classification with Graph Convolutional Networks

Reference 32

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Observation f50c7060-dbaf-4995-986e-623f279b0260 · outbound

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Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 33

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Observation 9e988c15-4453-438d-a1d8-597e4b87e4e3 · outbound

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Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 34

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Observation 74b67ab4-d9d6-46e9-b043-8731464cf046 · outbound

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Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 35

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Observation b8d82523-13d6-4343-b454-fd8fbab2d714 · outbound

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Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 36

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Observation 20ad90e2-d706-43a6-be14-18dfcc4d44bd · outbound

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Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Deep Learning with Dynamic Computation Graphs

Reference 37

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Observation 97c238d8-6d4c-428c-b9a8-d8d2a9aa41b2 · outbound

This paper cites an unresolved cited work.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 38

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Observation 5e037cb0-93b1-489d-afef-eec19d12f32b · outbound

This paper cites 2020.A deep learning based cost model for automatic code optimization in tiramisu.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning 2020.A deep learning based cost model for automatic code optimization in tiramisu

Reference 39

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Observation 7c9ccd90-fb57-4386-8bfc-9c3a388e6df3 · outbound

This paper cites an unresolved cited work.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 40

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source=pdf_text observed=2026-08-07T11:37:17.050173Z digest=sha256:ff451605f57192392ec077a023970ba3ad184cf9df375328cd3e730e21649ec8

Observation 7d78d250-d363-4dca-8d1f-c75bf5abed51 · outbound

This paper cites an unresolved cited work.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 41

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Observation a5132241-1dd4-4056-ada6-adef4a10a551 · outbound

This paper cites Reinforced Genetic Algorithm Learning for Optimizing Computation Graphs.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Reinforced Genetic Algorithm Learning for Optimizing Computation Graphs

Reference 42

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source=pdf_text observed=2026-08-07T11:37:17.180734Z digest=sha256:5a60f1b33175e1403116fde166425d23c06dc72bc5e60a5eccfeb54fccd75234

Observation 6209845a-f116-4b86-ae50-b9247009bab0 · outbound

This paper cites an unresolved cited work.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 43

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Observation c6585340-6b05-4cb2-bb20-ce0c21821775 · outbound

This paper cites an unresolved cited work.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 44

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Observation 11ae586b-8789-4ff9-b8d2-5126730bebaa · outbound

This paper cites Ramanujam, P.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Ramanujam, P

Reference 45

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 3022a394-6df1-4c96-96d4-ea78a31c4501 · outbound

This paper cites Quilleré and S.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Quilleré and S

Reference 46

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T11:37:17.501340Z digest=sha256:434317cc031df15f4b746f0685c7e84a14f885d2a44b52b61246fdb550d11d97

Observation 6222457e-4d22-4cad-a94b-f24eb0ce668d · outbound

This paper cites an unresolved cited work.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 47

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source=pdf_text observed=2026-08-07T11:37:17.580652Z digest=sha256:dcc831379afa4b006469522b2043a7b2ad157cf4feb7984ef0cdeca48514eebd

Observation 15307476-c37e-4ef4-bf20-dce42251c195 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Proximal Policy Optimization Algorithms

Reference 48

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source=pdf_text observed=2026-08-07T11:37:17.677852Z digest=sha256:2116441273215dedc2652a6e29a49fd51fff0fb1b69a3163d5db7fba9c3aaadd

Observation 00f4166c-9ed2-4b92-94a5-f0608aa0660c · outbound

This paper cites Sutton and A.G.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Sutton and A.G

Reference 49

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source=pdf_text observed=2026-08-07T11:37:17.757033Z digest=sha256:a4bc09fc64c9b0409d980874c7539ab2b5499f9c4a4cef4a132a8fc78b721ea2

Observation 4ad406a4-efb9-4980-b75f-64deaae70c4c · outbound

This paper cites an unresolved cited work.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 50

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Observation 681a2f3a-e2f8-43a9-93de-f0e4dfea1a43 · outbound

This paper cites an unresolved cited work.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 51

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source=pdf_text observed=2026-08-07T11:37:17.868847Z digest=sha256:46bfe87c3941d8c6761b970c1cfb1762783caf7285bd00b76ee97fbede76c817

Observation ac849872-b2a8-4a42-8dc7-37e1161dd089 · outbound

This paper cites an unresolved cited work.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 52

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Observation 8ac21825-94ca-4d5c-b79b-053f379d124a · outbound

This paper cites Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions

Reference 54

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Observation 66282a02-1566-4cb7-a1a6-955daf68a080 · outbound

This paper cites an unresolved cited work.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 55

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source=pdf_text observed=2026-08-07T11:37:18.288372Z digest=sha256:48940acabebbd9536c5f57dd458ffd3fdb7580ec14bd4015cbfadf1c51bbe979

Observation 874fc4f4-60b1-48df-a0f6-4e3f0d3287a2 · outbound

This paper cites an unresolved cited work.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 56

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Observation 2dc017a4-87ca-463e-a2c8-a9f1ebdff207 · outbound

This paper cites an unresolved cited work.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Unresolved cited work

Reference 57

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Observation 61b60399-70d8-4395-9fd8-444d5b1eb3ab · outbound

This paper cites Ansor: Generating High-Performance Tensor Programs for Deep Learning.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Ansor: Generating High-Performance Tensor Programs for Deep Learning

Reference 58

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source=pdf_text observed=2026-08-07T11:37:18.587768Z digest=sha256:1ee493aee75bed4dc0b69cec2b86d54b2eb8ec06759d29baccc4a87a7434b102

Observation 4da71da3-82fd-4be6-8473-add67e484281 · outbound

This paper cites FusionStitching: Boosting Memory Intensive Computations for Deep Learning Workloads.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning FusionStitching: Boosting Memory Intensive Computations for Deep Learning Workloads

Reference 59

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source=pdf_text observed=2026-08-07T11:37:18.710415Z digest=sha256:fb24643874e152958091f912e67d0d72e30dd11acb9be157bea371381d0b10c2

Observation 2fa3edec-9ada-49f5-9954-0c95236ee886 · outbound

This paper cites In 38th ACM SIGACT-SIGPLAN Symposium on Principles of Programming Languages (POPL’11).

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning In 38th ACM SIGACT-SIGPLAN Symposium on Principles of Programming Languages (POPL’11)

Reference 2011

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raw_fallback, observed 2026-08-07T11:37:22.495010Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T11:37:17.444124Z digest=sha256:0057adb520a5c8b7530f60e85fc2cc0a82268eb5e15d16cf1a796f96e94edcb7

Observation cc5a5706-ae76-4f09-8d11-6786ad043efa · outbound

This paper cites Learning to Optimize Tensor Programs.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Learning to Optimize Tensor Programs

Reference 2019

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source=pdf_text observed=2026-08-07T11:37:15.849112Z digest=sha256:745b1b36f70ba4d9039b22024886b901340923b354d18c3406116d04a45366d1

Observation f66847b5-4ac7-428e-bac4-098f196c9d42 · outbound

This paper cites Proceedings of Machine Learning and Systems 3 (2021), 181–193.

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning Proceedings of Machine Learning and Systems 3 (2021), 181–193

Reference 2021

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raw_fallback, observed 2026-08-07T11:37:22.984033Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T11:37:15.195507Z digest=sha256:48fa22dc4a689d8905c8e357d0955df7f830365cdd970cd443c39de489c35da9

Pith citing papers

No inbound Pith citation observations are available.