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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=sha256:98434e5d90b9bba695ca147d4291a8661e4fa4331574c53456fbd0dcecaeea45

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=sha256:288fa6a5c4c8588c1f5ea19d01e006adcb733caa81ed267c05e47a907c36531a

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=sha256:7eca228021f3ac7b11156f9a415c77a88f7bf951668a304fa5223a16f31c6805

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

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=2026-05-14T22:17:13.431164Z digest=sha256:430b97c288083bfbb5d66fcd31daa5fe41f0a8e8f9b5e523b57409dbca3ce24a

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=sha256:891dd8082338809c524221039857903f04dac1e363005ca89c0b3bf3bdd1006c

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

Resolution
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:a464921da93958f3402af11fc18850c979f514a806d49defbf0e105aab88ec1b

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:d5a40b84520ab9482158f0748fcd2ef7970a0a06df053aa5abec0ef8de951d70

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

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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=2026-06-29T23:16:05.110912Z digest=sha256:ed08825e6f7c8406cdbf4e251d1d81615821c2afb58cd9bc6b93f6d584ffbfce

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=sha256:8ff6d0828e16108445ccacc7bdb3cef89a616cdb16288285639764a320c34014

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=sha256:805b1cb2888d8350ee736c63c4775b2ba4514f0587297950daaed535c2bdee98

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:d09fb5b3783c3f2093988ad645cbbac91df40bf675630cd35a0208d5cea1128d

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=sha256:749a5a283ea9633eaa2b579c9134625313031d283e48815741f5ac5a1be385f4

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=sha256:7b40e89ac38ba4f77e3bb632224e845b6fd85b1af066d59f3187fc03360b4781

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=sha256:6bf6d00c70e19ef11e60a2f5791d8aac9cf59a6a3fd99fb01af891abec7fe476

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:e2a2c6d2c030db660e71c3279cad2a76679e525b8106d7924772a3ddd88b45cf

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=sha256:4565146885b8803de715fe96ffaf7677284a39da9bbd1f2f83a6dc399e56a784

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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