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Paper Citation Record · LEDGER

CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2507.14111.

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

pith.paper-citation-record.v1
2507.14111 v12

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 17 of 17 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 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:14:38.778592Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T22:29:00.423017Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a0cb7206-acca-42ef-b0a2-f6d817d05307 · inbound

A Systematic Survey on Large Language Models for Evolutionary Optimization: From Modeling to Solving cites this paper.

A Systematic Survey on Large Language Models for Evolutionary Optimization: From Modeling to Solving CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning

Reference 200

Resolution
unresolved
no resolver link, observed 2026-08-04T20:55:41.851979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T20:55:41.851979Z digest=sha256:6cee95478e31e1dbf161952a437b9bee7a5d7303d0482266cff4fa616894acbb

Observation ffab84f0-c8fc-46e0-a13b-c0da42c3a9da · inbound

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning cites this paper.

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning

Reference 7

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unresolved
no resolver link, observed 2026-08-03T19:04:27.711731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T19:04:27.711731Z digest=sha256:c17f245ef8e8134be70992b99cac5a0ce2d1f0f59ea0f80d35903cce04a596f7

Observation f0eac67c-39fc-4253-929c-82acc619deca · inbound

AscendOptimizer: Episodic Agent for Ascend NPU Operator Optimization cites this paper.

AscendOptimizer: Episodic Agent for Ascend NPU Operator Optimization CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning

Reference 17

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verified exact
arxiv_id, observed 2026-07-14T02:20:17.802860Z

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=2026-05-21T10:16:15.305706Z digest=sha256:a9f3a768bc1c164c7ebb9bf70170be595e5a656a0bf3ec93384747a2f18fe316

Observation 95e1063d-6f95-4dfb-b8dd-e0e186bab4d2 · inbound

Kernel-Smith: A Unified Recipe for Evolutionary Kernel Optimization cites this paper.

Kernel-Smith: A Unified Recipe for Evolutionary Kernel Optimization CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning

Reference 12

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verified exact
arxiv_id, observed 2026-07-14T02:20:17.802860Z

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=2026-05-14T22:17:13.431164Z digest=sha256:35e2f0658d9c96180227e4b8d8e669332e3ec14a3c3f77033f4385f1f4c974d1

Observation b119731d-c6f2-49f3-8b0e-78f00dc081de · inbound

GrandCode: Achieving Grandmaster Level in Competitive Programming via Agentic Reinforcement Learning cites this paper.

GrandCode: Achieving Grandmaster Level in Competitive Programming via Agentic Reinforcement Learning CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-07-14T02:20:17.802860Z

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=2026-05-13T20:30:17.791973Z digest=sha256:3bd20f668607b647a017202316171ddf004e277362ac93d3ace4a025496d7f9e

Observation 7130d8a5-bf5b-43f3-9dc3-83e73e3f1620 · inbound

AdaExplore: Failure-Driven Adaptation and Diversity-Preserving Search for Efficient Kernel Generation cites this paper.

AdaExplore: Failure-Driven Adaptation and Diversity-Preserving Search for Efficient Kernel Generation CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning

Reference 9

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metadata mismatch
arxiv_id, observed 2026-07-14T02:20:17.802860Z

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=2026-05-10T08:27:56.130579Z digest=sha256:aae862b7aa9d6a5981a57d2b9064fe8021a2c4a6d8c5a5accfb36a8e1cf3c976

Observation e61e2802-eb81-4e63-8b4f-d60440f2bbda · inbound

FastKernels: Benchmarking GPU Kernel Generation in Production cites this paper.

FastKernels: Benchmarking GPU Kernel Generation in Production CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning

Reference 11

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verified exact
arxiv_id, observed 2026-07-14T02:20:17.802860Z

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=2026-05-25T05:20:08.724490Z digest=sha256:607f9a51d04f77359d5708a3b3cada633ac974946d28d89da191d83a986dc6cb

Observation 628c1d86-0765-4a0b-beb0-d82db254543a · inbound

Step-TP: A Grounded, Step-Level Dataset with Chain-of-Thought Reasoning for LLM-Guided Tensor Program Optimization cites this paper.

Step-TP: A Grounded, Step-Level Dataset with Chain-of-Thought Reasoning for LLM-Guided Tensor Program Optimization CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-07-14T02:20:17.802860Z

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=2026-06-29T23:16:05.110912Z digest=sha256:73b128b78375fec0f5455d6154f9419691a795126e11205b2abfa6a048cc41b9

Observation a9b9664a-4073-4f32-83eb-dee6f5722f54 · inbound

Learning When to Optimize: Verified Optimization Skills from Expert GPU-Kernel Lineages cites this paper.

Learning When to Optimize: Verified Optimization Skills from Expert GPU-Kernel Lineages CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning

Reference 16

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verified exact
arxiv_id, observed 2026-07-14T02:20:17.802860Z

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=arxiv_source observed=2026-06-29T12:26:23.359699Z digest=sha256:5991fee28d109afb7fa351cfb0b0b008a4954e4e469acaf03ff492c25716498c

Observation 9b33ce55-68b9-4f93-b0fd-4e47c69c8439 · inbound

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

PassNet: Scaling Large Language Models for Graph Compiler Pass Generation CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-07-14T02:20:17.802860Z

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:babf83a269b95801e1b719845214e9e833908951dcc3ad7d0de756fcd292ba44

Observation e759449b-a952-4fe3-8967-83fa58e4e852 · inbound

Kernel Foundry: A Diagnosis-driven Evolutionary Kernel Optimizer with Multi-Experts cites this paper.

Kernel Foundry: A Diagnosis-driven Evolutionary Kernel Optimizer with Multi-Experts CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-07-14T02:20:17.802860Z

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=2026-06-30T23:33:47.477482Z digest=sha256:b72c8984f5440b83ec4f3c2024b0487c73acf810724016bc55cbc708196837a3

Observation dd96a8be-c7ad-494e-a112-224251c1021a · inbound

Kernel Foundry: A Diagnosis-driven Evolutionary Kernel Optimizer with Multi-Experts cites this paper.

Kernel Foundry: A Diagnosis-driven Evolutionary Kernel Optimizer with Multi-Experts CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-04T05:17:04.985935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T05:17:04.985935Z digest=sha256:c1835211af28362b43e77d11842dbb5df9b6cc6bcbbb9321a847d7f7c48aad26

Observation 49c67a07-7e43-414a-8557-31a1c6b03299 · inbound

SpecGen: Accelerating Agentic Kernel Optimization with Speculative Generation cites this paper.

SpecGen: Accelerating Agentic Kernel Optimization with Speculative Generation CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-07-14T02:20:17.802860Z

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=2026-06-26T23:35:32.175768Z digest=sha256:da9f07dd979bcca3fafc1f7fb131ead834245a00263ec8924c9537b6e9ce4168

Observation 83f2e016-62f5-4f54-9ea2-8b8d346ed990 · inbound

Hawk: Harnessing Hardware-Aware Knowledge for High-Performance NPU Kernel Generation cites this paper.

Hawk: Harnessing Hardware-Aware Knowledge for High-Performance NPU Kernel Generation CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-07-14T02:20:17.802860Z

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=2026-07-03T15:01:18.911340Z digest=sha256:f7e550ef7ba62bcc04f5694481129f4fce137e98f831e833e06d002316b686a6

Observation cd76fa3f-1b6a-494e-8013-a04d7c868fed · inbound

Compiler-Grounded Hierarchical Diagnosis for LLM-Based Triton Kernel Optimization cites this paper.

Compiler-Grounded Hierarchical Diagnosis for LLM-Based Triton Kernel Optimization CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-01T03:42:32.077668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T03:42:32.077668Z digest=sha256:2375be50097b870c23d4d023086a20566ff9d9772c04a7171d1bf9539222b3b3

Observation d62ac326-57e1-4974-9c40-44d477d16e37 · inbound

RLPF: Reinforcement Learning from Performance Feedback for Code Generation cites this paper.

RLPF: Reinforcement Learning from Performance Feedback for Code Generation CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-01T10:53:08.903173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T10:53:08.903173Z digest=sha256:09405a835ec6647d6957c5a3efe89a6f499d9ab8f111aa90e7ff0b73dc623016

Observation 39c2a086-d479-403e-9c5a-37aa61e6dba7 · inbound

LEAP: Lean Environment-Feedback via Adaptive Pruning for Code RL in GPU Kernel Generation cites this paper.

LEAP: Lean Environment-Feedback via Adaptive Pruning for Code RL in GPU Kernel Generation CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T00:14:38.778592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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