Paper Citation Record · LEDGER

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning

As of 19 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2509.10526.

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

pith.paper-citation-record.v1
2509.10526 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T10:19:22.913816Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

45 of 45 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4c2006b6-49db-454a-b51e-33dcc4b76326 · outbound

This paper cites Automated machine learning: past, present and future,.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Automated machine learning: past, present and future,

Reference 1

Resolution: verified exact; doi, observed 2026-08-05T10:19:23.012600Z

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Observation d74a26cb-45c5-46d8-953b-5582ea5ce7cf · outbound

This paper cites NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-05T10:19:23.754372Z

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Observation 3087283d-85af-4163-9d0e-dc74dda71ad0 · outbound

This paper cites EagleEye: Fast Sub-net Evaluation for Efficient Neural Network Pruning.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning EagleEye: Fast Sub-net Evaluation for Efficient Neural Network Pruning

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-05T10:19:23.732522Z

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Observation 0e576042-00eb-4ff5-b243-f4caccb91e08 · outbound

This paper cites MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-05T10:19:23.709851Z

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Observation 007764d2-cb82-4742-9a2d-9fc8fd889044 · outbound

This paper cites AutoPruner: An End-to-End Trainable Filter Pruning Method for Efficient Deep Model Inference.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning AutoPruner: An End-to-End Trainable Filter Pruning Method for Efficient Deep Model Inference

Reference 5

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Observation 1b139362-da4a-465b-9dad-d5e456e255b3 · outbound

This paper cites AutoSlim: Towards One-Shot Architecture Search for Channel Numbers.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning AutoSlim: Towards One-Shot Architecture Search for Channel Numbers

Reference 6

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Observation 19ddd4e5-7018-4c7d-96ed-74156a8874aa · outbound

This paper cites AutoCompress: An automatic DNN structured pruning framework for ultra-high compression rates,.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning AutoCompress: An automatic DNN structured pruning framework for ultra-high compression rates,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:19:23.887219Z

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Observation 0df77f40-43b0-4fb7-b697-b5b01e5558b1 · outbound

This paper cites AMC: AutoML for model compression and acceleration on mobile devices,.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning AMC: AutoML for model compression and acceleration on mobile devices,

Reference 8

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Observation 1cfbd5cd-a638-4129-9bc5-aa041c6487b6 · outbound

This paper cites A novel filter-level deep convolutional neural network pruning method based on deep reinforcement learning,.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning A novel filter-level deep convolutional neural network pruning method based on deep reinforcement learning,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:19:23.869925Z

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Observation aafb3925-29ec-41c2-b90a-8e4b3127fd80 · outbound

This paper cites Neural Network Pruning Through Constrained Reinforcement Learning.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Neural Network Pruning Through Constrained Reinforcement Learning

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-05T10:19:23.659230Z

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Observation 4ef78c72-59d0-4f4f-be40-8fc9efd37869 · outbound

This paper cites Runtime neural pruning,.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Runtime neural pruning,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:19:23.853058Z

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Observation da4ddf64-830d-40b8-9ea3-2a7982ab6804 · outbound

This paper cites Learning to Prune Filters in Convolutional Neural Networks.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Learning to Prune Filters in Convolutional Neural Networks

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-05T10:19:23.638404Z

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Observation 4b051dd0-afd9-4b77-bcd8-69f6a91532fd · outbound

This paper cites Deterministic policy gradient algorithms,.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Deterministic policy gradient algorithms,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:19:23.836872Z

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Observation 18ad122d-10f6-45bb-a311-2bffa087ae39 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Proximal Policy Optimization Algorithms

Reference 14

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Observation 2190698f-9c0d-4c38-9ba1-f770885b26db · outbound

This paper cites MuZero with Self-competition for Rate Control in VP9 Video Compression.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning MuZero with Self-competition for Rate Control in VP9 Video Compression

Reference 15

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Observation 51a6f90f-1e5e-4f42-8416-4c411987fe83 · outbound

This paper cites Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learning.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learning

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-05T10:19:23.588532Z

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Observation f71b15a0-a6b7-4313-901c-931d10b9a88e · outbound

This paper cites Graph Attention Networks.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Graph Attention Networks

Reference 17

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Observation 854f3b38-7d93-4e18-a8ee-086f0201e303 · outbound

This paper cites How Attentive are Graph Attention Networks?.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning How Attentive are Graph Attention Networks?

Reference 18

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Observation d708d731-6486-4bdc-a59b-1ca8cff42a93 · outbound

This paper cites Altman, Constrained Markov decision processes: Stochastic modeling.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Altman, Constrained Markov decision processes: Stochastic modeling

Reference 19

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Observation 2e1adf20-7326-4de6-b12a-29f8e702a0ea · outbound

This paper cites Simon, Evolutionary optimization algorithms.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Simon, Evolutionary optimization algorithms

Reference 20

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Observation 9963b6c0-228d-4bda-89d3-b4cd87e29780 · outbound

This paper cites Graph Matching Networks for Learning the Similarity of Graph Structured Objects.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Graph Matching Networks for Learning the Similarity of Graph Structured Objects

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-05T10:19:23.538205Z

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Observation b496196c-ef90-4272-8090-9002156acd03 · outbound

This paper cites Exact solutions to the nonlinear dynamics of learning in deep linear neural networks.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Exact solutions to the nonlinear dynamics of learning in deep linear neural networks

Reference 22

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Observation 5588617b-2096-4e8a-a773-f75533968b8f · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Semi-Supervised Classification with Graph Convolutional Networks

Reference 23

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Observation c6f0a5f1-b2c4-4f33-9805-0690b3a68624 · outbound

This paper cites Probabilistic interpretation of feedforward classification network outputs, with relationships to statistical pattern recognition,.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Probabilistic interpretation of feedforward classification network outputs, with relationships to statistical pattern recognition,

Reference 24

Resolution: verified exact; doi, observed 2026-08-05T10:19:22.986946Z

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Observation e73d6c8c-c101-44f6-86f1-f34daba40454 · outbound

This paper cites Learning representations by back-propagating errors,.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Learning representations by back-propagating errors,

Reference 25

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Observation eade41dd-b17d-4255-ada1-a44b3b79b8f6 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Adam: A Method for Stochastic Optimization

Reference 26

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Observation 5f3855af-555e-4ea5-8853-b7b7facc66e5 · outbound

This paper cites Very deep convolutional networks for large-scale image recognition,.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Very deep convolutional networks for large-scale image recognition,

Reference 27

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Observation 61db67a0-7ab4-41ec-8b41-aa0d3e2507ef · outbound

This paper cites Learning multiple layers of features from tiny images,.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Learning multiple layers of features from tiny images,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:19:23.773019Z

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Observation 60eab875-6f4b-4024-a379-13322fafaec3 · outbound

This paper cites Resource-aware neural network pruning using constrained reinforcement learning and self-competition,.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Resource-aware neural network pruning using constrained reinforcement learning and self-competition,

Reference 29

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Observation a3b3f8f1-3132-4ab3-89c4-e239c158bba4 · outbound

This paper cites Numerical optimization of computer models,.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Numerical optimization of computer models,

Reference 30

Resolution: verified exact; doi, observed 2026-08-05T10:19:22.961177Z

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Observation cf0ce441-dc58-49ec-afe5-d0f22cb8a99a · outbound

This paper cites Completely derandomized self-adaptation in evolution strategies,.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Completely derandomized self-adaptation in evolution strategies,

Reference 31

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Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning The CMA Evolution Strategy: A Tutorial

Reference 32

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Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning ImageNet: A large-scale hierarchical image database,

Reference 33

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This paper cites Structured Probabilistic Pruning for Convolutional Neural Network Acceleration.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Structured Probabilistic Pruning for Convolutional Neural Network Acceleration

Reference 34

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Observation b698bb1a-20a5-4f2a-82a4-5717338ac7b3 · outbound

This paper cites Pruning Filters for Efficient ConvNets.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Pruning Filters for Efficient ConvNets

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This paper cites Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks

Reference 36

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Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration

Reference 37

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This paper cites DSA: More Efficient Budgeted Pruning via Differentiable Sparsity Allocation.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning DSA: More Efficient Budgeted Pruning via Differentiable Sparsity Allocation

Reference 38

Resolution: verified exact; local_arxiv, observed 2026-08-05T10:19:23.220572Z

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Observation 70f7796d-d989-4d84-9728-b1589c5c7f62 · outbound

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Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Provable Filter Pruning for Efficient Neural Networks

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-08-05T10:19:23.199542Z

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Observation 01d5ece9-3a1d-49ff-9604-402260610fef · outbound

This paper cites Automatic group-based structured pruning for deep convolutional networks,.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Automatic group-based structured pruning for deep convolutional networks,

Reference 40

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Observation 16540730-b9db-434b-a67c-da3f7c1228d2 · outbound

This paper cites To prune, or not to prune: exploring the efficacy of pruning for model compression.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning To prune, or not to prune: exploring the efficacy of pruning for model compression

Reference 41

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This paper cites Learning Efficient Convolutional Networks through Network Slimming.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Learning Efficient Convolutional Networks through Network Slimming

Reference 42

Resolution: verified exact; local_arxiv, observed 2026-08-05T10:19:23.067036Z

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Observation 5b6be164-08f5-4407-923d-b9f545590efb · outbound

This paper cites A Comprehensive Overview of Large Language Models.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning A Comprehensive Overview of Large Language Models

Reference 43

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This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 44

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Observation c63dcf18-3b41-42da-b354-19132a3ec0ba · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 2014

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Pith citing papers

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