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Paper Citation Record · LEDGER

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

As of 14 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 2026-08-14T06:32:32.682623+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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T12:41:34.114293Z digest=sha256:f7dd390eb32af8b1e23fc5867227d5c3bd3112d1cc60656f4b0f8d4ba9377dfd

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T12:41:34.211944Z digest=sha256:e51a7d22eda40c74e7200e40e0dd4ad90e14fa98832fb7ba5e8a8a150ee26640

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T12:41:34.311259Z digest=sha256:99d959f90684c434a69e94d993beb2813127a2122de505666d52cda5a145a2f7

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T12:41:34.414790Z digest=sha256:0a064ab5d9b7809d4868bf4f8f386e10ab7e43399e729b11cb53e6f2f238b322

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T12:41:34.504066Z digest=sha256:5054281af9c329578140fae00d1914ed33a8f18e5432a66e2af5ed4b8b15c1e0

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T12:41:34.581710Z digest=sha256:88ce98e4d8f4494dd31de54ff244d57e9e5bf5fb32625b539333147c4dc1100b

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T12:41:34.675289Z digest=sha256:dd04bb6ce75164935a6eb26f333fcd2d9cd58e13f978f19b836309c5c27df873

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=sha256:4cda64929a250313341029f64876a07bb61f9cb99955cd0011c60a9b160ea606

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=sha256:64e658408367d1ddce2f3b6b8e19efd0d20eebbe7b2aa7b69f4dc425c1da5fed

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T12:41:34.939324Z digest=sha256:7b5a4baeedc39f066499186302e7a15ec54823012de2331f4f08e2f96e309b85

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T12:41:35.027437Z digest=sha256:37f32351e509dc73857637709cf28a599069f71bec287f3976a46ec5d9cc009c

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T12:41:35.103827Z digest=sha256:51a768bd536b77c7e5a2b86cf6b6159a179316554a7f749f48733365d200b5b7

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T12:41:35.198489Z digest=sha256:203c1b787d0a85d9f631bb13a3850ee717b557e558c109124c6274cff719e309

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T12:41:35.296051Z digest=sha256:477e854efc0380424883c25cb0c5879a40993dd8a49a818d22e323dc0156140c

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T12:41:35.405692Z digest=sha256:e39f4e8e07e6a1eda781f00a8abcd87fd44435c58ea2bfad4fa7f7456d6de07f

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T12:41:35.445394Z digest=sha256:51bdfacb566fe7ea466922df29d0b4ed6bf20d5d8df9d8b8d71bafab40437d5a

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=sha256:3a66b4fbb5ca7d45b920ed609b955eb4d00c2ed7fc8a9282d09b1615be9791dc

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=sha256:55124cc582ff67beaf7e7a414403090232df1e21b3fbd0b603d454e073769a3a

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T12:41:35.714245Z digest=sha256:c2d57488c8a42cc8de49cf43ec819ae670d69e694f0a56ff0bbfbe512816174b

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T12:41:35.787773Z digest=sha256:058d1b96bf86c34a86c95fb661f74b81b3ca486a2a683f614aad6c91ff55a906

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T12:41:35.844191Z digest=sha256:3d32bfcdd29284a686a7db8613c2f3afacb7b8b8577d5cc172d9c0a7d7fde3ce

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=sha256:03b66b70d33e9cf380a8fda9308060dc44253c5d94a31bca4099941f9945d1c6

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T12:41:36.057404Z digest=sha256:aba14a277fb0894dd2ecd10ab1bd0e2994992f0f6eb4f52b8a444b31f21d93e4

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T12:41:36.119919Z digest=sha256:fca8f373ab5c06213faafd3ba3e9689c6e9cf5af0f0239c57fe9ab556be80329

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=sha256:481857ca746f6a4e673857887d1b9955d97eb72c4fd5ff22c98f1d934b820620

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T12:41:36.323705Z digest=sha256:55b76df8cbe2d8ef3a3eb3a52a771f7b2ce48cc0877a5d6d2902cfc8fe290171

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=sha256:47884c6ee16c8647d2f309c6eb3776992b0f485aa4af16e99cb849c73dc483a6

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T12:41:36.487954Z digest=sha256:63a9127d22d18bb1e5096931e96a233f83c51d89ffc624097d61ba4eb3753d75

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T12:41:36.596353Z digest=sha256:1c8576f7fe3f802b76851fd60809e6c0f53c2e4396398e159641244167b482b1

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-29T07:53:06.859337Z digest=sha256:024ba3857a5a7bc0ab6f706d9e8219b506f3a059c52d80928e4e61ad55d266f4

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-26T16:10:14.144156Z digest=sha256:930c436509d1f8be2183c59a0d19e47ad361a73800fa8d494f13f412d5e7a403