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Paper Citation Record · LEDGER

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning

As of 8 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 2 inbound Pith citation observations for arXiv:2506.15701.

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

pith.paper-citation-record.v1
2506.15701 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:41:36.596353Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-29T07:53:06.859337Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T05:19:34.870032Z

Reference resolution

29 of 29 outbound references displayed

  • verified exact0
  • verified fuzzy20
  • unresolved8
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0cd8522b-6af2-47f7-8a46-b285936237ba · outbound

This paper cites Opentuner: An extensible framework for program autotuning.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Opentuner: An extensible framework for program autotuning

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:41:40.085658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:41:34.114293Z digest=sha256:cc06acc442170dd5a6f6551d37da245ad3e88dc413fb31312e9554cc7d9221cc

Observation de7abdad-276c-436e-a300-1f8532f95323 · outbound

This paper cites A survey on compiler autotuning using machine learning.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning A survey on compiler autotuning using machine learning

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:41:39.977414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:41:34.211944Z digest=sha256:d215fcd802e0c5e4d8c321575bb5fbcbcac3e989368d1057a2de045a93b0d446

Observation f1c84f35-6448-425e-a5f9-772b37f3cbaa · outbound

This paper cites The nas parallel benchmarks.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning The nas parallel benchmarks

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:41:39.869624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:41:34.311259Z digest=sha256:5fde330cb8bdc0efa8a009148e84a8a88f23bc10d1c12bfd99869ebc24145843

Observation 6c25d0cc-b418-4b7b-af37-f6d58af64b69 · outbound

This paper cites Algorithms for hyper- parameter optimization.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Algorithms for hyper- parameter optimization

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:41:39.745947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:41:34.414790Z digest=sha256:73ec6f815ccb94ce15c4879697b271af4c871294471bbe52e60c99632a34e8f3

Observation 1ec358d2-d752-41ab-b979-549e54e93845 · outbound

This paper cites Iterative compilation in a non-linear optimisation space.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Iterative compilation in a non-linear optimisation space

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:41:39.662112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:41:34.504066Z digest=sha256:868fed99abe8e40880ab0114bb758684b03ede976415e692a77bbfebed4bb9ca

Observation 2c2c3d8d-080f-43be-b6e2-9de4b7e83034 · outbound

This paper cites Efficient compiler autotuning via bayesian optimization.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Efficient compiler autotuning via bayesian optimization

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:41:39.506304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:41:34.581710Z digest=sha256:4da7276369e25fb07ebc0f4943665ae52c61c60e0c8187c999989b60410b8a72

Observation 7364dd2d-9838-4d27-a061-1298760daf0e · outbound

This paper cites Deconstructing iterative optimization.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Deconstructing iterative optimization

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:41:39.387835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:41:34.675289Z digest=sha256:79c8d1adfa4529820dbd65f12d9ed32bdc74086f79241d582f19d6a12adda9ed

Observation cc4edc8c-1716-47f2-926f-8ddd2b474072 · outbound

This paper cites Large Language Models for Compiler Optimization.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Large Language Models for Compiler Optimization

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T12:41:34.776620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:41:34.776620Z digest=sha256:ba34cb840cd04984a8e2e89ea24576c3a91246db3728cf531fbdd18bffafbbd5

Observation 4bb300e0-6c8d-4708-a215-05c4f387eecf · outbound

This paper cites Meta Large Language Model Compiler: Foundation Models of Compiler Optimization.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Meta Large Language Model Compiler: Foundation Models of Compiler Optimization

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T12:41:34.854994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:41:34.854994Z digest=sha256:bbd64685445714192557e1dc72f7f93afb54571fa88677bc499bf9f724799759

Observation feb94fa9-160c-4c5c-92b0-7d3314f15af1 · outbound

This paper cites Compilergym: Robust, performant compiler optimization environments for ai research.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Compilergym: Robust, performant compiler optimization environments for ai research

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:41:39.234185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:41:34.939324Z digest=sha256:528c385ad8fb6d800f0bd57300c0825c789b0f96c1fa0fb4c31a8c84367d01f3

Observation 6a6cfba2-2ca4-4178-8017-0f5f0fb4cf4b · outbound

This paper cites an unresolved cited work.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:41:39.062853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:41:35.027437Z digest=sha256:c402eba8c8cf5e8b18d3de9ce2f8006b367a0530c2f097149ab367fbba6101d6

Observation c8d4cf1c-da30-48da-b74b-3b025d82e106 · outbound

This paper cites Collective tuning initiative: automating and accelerating development and optimization of computing systems.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Collective tuning initiative: automating and accelerating development and optimization of computing systems

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:41:38.924004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:41:35.103827Z digest=sha256:06d034b9ccefaa658e6b9247161eed12d11932e51d7f93268ab4dc855a169d1c

Observation 7713b22b-0c10-44fc-92c6-f8ab9d83af68 · outbound

This paper cites Evolutionary optimization of compiler flag selection by learning and exploiting flags interactions.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Evolutionary optimization of compiler flag selection by learning and exploiting flags interactions

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:41:38.765038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:41:35.198489Z digest=sha256:0f4dd85dfb76f28ca61d0a7e02365fd4301ea72ad2da3ad12209107d0dcb5371

Observation da5b95d5-34a4-4339-8323-4282531705df · outbound

This paper cites Mibench: A free, commercially representative embedded benchmark suite.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Mibench: A free, commercially representative embedded benchmark suite

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:41:38.604984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:41:35.296051Z digest=sha256:317c91adbd656f0cd97900688dbfe1f2cb7ba3a419c33cc1c8ae9e23f9a87208

Observation 24bd8c4e-0db7-4271-95d1-235e91a514c9 · outbound

This paper cites Autophase: Juggling hls phase orderings in random forests with deep reinforcement learning.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Autophase: Juggling hls phase orderings in random forests with deep reinforcement learning

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:41:38.428384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:41:35.405692Z digest=sha256:71d17571cb9eed1833fcb93f1f259b8d774215f602c75f23ceb0159a8aa3ea37

Observation 42da08cc-9ea9-4ff6-9b05-360662d0963c · outbound

This paper cites Chstone: A benchmark program suite for practical c-based high-level synthesis.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Chstone: A benchmark program suite for practical c-based high-level synthesis

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:41:38.214286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:41:35.445394Z digest=sha256:db9bb1a10df9664ac832ba3b1473c6b58e2847ec6170382945fd30df85304866

Observation 4577dcfa-ee1c-4094-82a9-9d63e2b4e8da · outbound

This paper cites Finding Missed Code Size Optimizations in Compilers using LLMs.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Finding Missed Code Size Optimizations in Compilers using LLMs

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T12:41:35.577750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:41:35.577750Z digest=sha256:63c63ab2b327d888042bca494d2dccd34395a140561a2448d6d490e880c2a330

Observation 31dd1c54-86d1-4a90-acc5-aef3d62f2977 · outbound

This paper cites OpenAI o1 System Card.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning OpenAI o1 System Card

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T12:41:35.649905Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:41:35.649905Z digest=sha256:d049dd01b47a8d31d72525bcd1a9147c391227f97f0c15edfe6d1108be13a1bc

Observation 54afd1dd-26fe-4bf8-b48d-6447bc70bd4d · outbound

This paper cites Search-r1: Training llms to reason and leverage search engines with reinforcement learning, 2025.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Search-r1: Training llms to reason and leverage search engines with reinforcement learning, 2025

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:41:38.027842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:41:35.714245Z digest=sha256:084679f884cff26938e202c0f7b9c28d9f37cc9082d87dbdbc0367c5e59d71e5

Observation 7affb8e0-954d-4c8c-b037-11cbc4a80323 · outbound

This paper cites Llvm: A compilation framework for lifelong program analysis & transformation.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Llvm: A compilation framework for lifelong program analysis & transformation

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:41:37.843060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:41:35.787773Z digest=sha256:76a3f6d80bb5c64a80b1e41679f9f7f3dbfdb8ec24301c888d15403396c0f919

Observation be3390ce-9c0e-4648-8c58-7fb549bd8507 · outbound

This paper cites Learning compiler pass orders using coreset and normalized value prediction.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Learning compiler pass orders using coreset and normalized value prediction

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:41:37.620285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:41:35.844191Z digest=sha256:7102b95407af244b2d8006e4119eaee357912d8ffb2e2fb5d79af0c3d0a4c582

Observation 51dcb3e6-11a1-4d79-9efd-4b6ed88c1f99 · outbound

This paper cites Code-r1: Reproducing r1 for code with reliable rewards.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Code-r1: Reproducing r1 for code with reliable rewards

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T12:41:35.926532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:41:35.926532Z digest=sha256:eb8a2120af7ee3838be05ff9c24d1f3c0034031e389d3021ac70995ee418aeca

Observation 43dfefe7-d598-4db6-854c-4226bed8d4b6 · outbound

This paper cites Ui-r1: Enhancing action prediction of gui agents by reinforcement learning, 2025.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Ui-r1: Enhancing action prediction of gui agents by reinforcement learning, 2025

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:41:37.486512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:41:36.057404Z digest=sha256:721ac5bba19964917b7ee8bd69e80463c852e5335f9345b206ae43efa25ae293

Observation a7cf7e3c-db82-4164-8702-ad6e31c49377 · outbound

This paper cites Towards efficient compiler auto-tuning: Leveraging synergistic search spaces.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Towards efficient compiler auto-tuning: Leveraging synergistic search spaces

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:41:37.312616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:41:36.119919Z digest=sha256:064f3930cf5bf3dfc4943bd6650c702758164fd93f0927904b38bee5883315ba

Observation 95d4249c-ca3a-4132-b2a5-7bc887345952 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Proximal Policy Optimization Algorithms

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T12:41:36.244603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:41:36.244603Z digest=sha256:33c658dffcafbcc5345b3842d72f289dc7f0bde08a4f55297c20443310a6e797

Observation 60ab62f9-3648-4b84-8a36-dcac1a110f1f · outbound

This paper cites Deepseekmath: Pushing the limits of mathematical reasoning in open language models.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Deepseekmath: Pushing the limits of mathematical reasoning in open language models

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:41:37.178007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:41:36.323705Z digest=sha256:c4482b6944c3d32135319f50eb7c7dffc9800c16c96c7673be4509b9c9feb59e

Observation 88aefcd1-1146-43fc-930b-3d9ba7215352 · outbound

This paper cites Logic-rl: Unleashing llm reasoning with rule-based reinforcement learning, 2025.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Logic-rl: Unleashing llm reasoning with rule-based reinforcement learning, 2025

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T12:41:36.400958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:41:36.400958Z digest=sha256:e065f6758635911e2767a6f05e9d1003da24aab943fdb50a91e0bbd0cdce2599

Observation 6d677146-d8d2-47d6-be17-34d8ccc47908 · outbound

This paper cites Sample efficient reinforce- ment learning with reinforce.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning Sample efficient reinforce- ment learning with reinforce

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:41:37.011655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:41:36.487954Z digest=sha256:3e5a2e66a73d0fb269319b483c536d9a55df21c62cca4cbd4836bed7fae06576

Observation ec95a667-8a08-4528-9171-2c1ea938840d · outbound

This paper cites - - dse.

Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning - - dse

Reference 29

Resolution
malformed identifier
raw_fallback, observed 2026-08-07T12:41:36.791527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:41:36.596353Z digest=sha256:9bc1e3cfdd935ae3e9cd73aefd648bb55e6b70f3b35837fd6837873208eb8a84

Pith citing papers

Observation 996b4324-e646-4ad3-aab4-1c90c547ee1d · inbound

PassNet: Scaling Large Language Models for Graph Compiler Pass Generation cites this paper.

PassNet: Scaling Large Language Models for Graph Compiler Pass Generation Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-06-29T07:53:13.243708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-29T07:53:06.859337Z digest=sha256:d6c92934cccdf38e0ad2402ced9d7b55c12897da53f4854fd383ffc639653e7f

Observation ffb9150a-78c3-466d-9212-11a824840a14 · inbound

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning cites this paper.

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-07-04T05:19:34.871590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-26T16:10:14.144156Z digest=sha256:ef9c8cd0facdda680f8642883a2d05fa66f0e7e7a469ee6d29516ba99948f3fa