Paper Citation Record · LEDGER

Pruning Everything, Everywhere, All at Once

As of 9 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2506.04513.

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

pith.paper-citation-record.v1
2506.04513 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:45:29.376262Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

44 of 44 outbound references displayed

verified exact0
verified fuzzy43
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c8c11ee5-cb2f-4b4b-a849-61d5912ad6cc · outbound

This paper cites Meta-learning adaptable foundation models,.

Pruning Everything, Everywhere, All at Once Meta-learning adaptable foundation models,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.832296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 863c5a3f-7e2c-469a-8ce8-9f69d23b8318 · outbound

This paper cites The llama 3 herd of models,.

Pruning Everything, Everywhere, All at Once The llama 3 herd of models,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.823244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2d4f0f6f-f685-4431-8294-ecb7dd581c18 · outbound

This paper cites LLMCarbon: Modeling the end-to-end carbon footprint of large language models,.

Pruning Everything, Everywhere, All at Once LLMCarbon: Modeling the end-to-end carbon footprint of large language models,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.813557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5e6c4fdb-72b3-4081-a16b-e112178df18f · outbound

This paper cites A survey on deep neural net- work pruning: Taxonomy, comparison, analysis, and recommendations,.

Pruning Everything, Everywhere, All at Once A survey on deep neural net- work pruning: Taxonomy, comparison, analysis, and recommendations,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.803795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 05294e40-18d1-40bd-93ff-5ff0c9373c2a · outbound

This paper cites Structured pruning for deep convolutional neural networks: A survey,.

Pruning Everything, Everywhere, All at Once Structured pruning for deep convolutional neural networks: A survey,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.794701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5eff8eab-3d1b-4ea9-8bec-416063b91b3b · outbound

This paper cites Effective layer pruning through similarity metric perspective,.

Pruning Everything, Everywhere, All at Once Effective layer pruning through similarity metric perspective,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.785337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 11c69f83-3f4b-4de7-9a0f-3c3fe622a218 · outbound

This paper cites Layermerge: Neural network depth compression through layer pruning and merging,.

Pruning Everything, Everywhere, All at Once Layermerge: Neural network depth compression through layer pruning and merging,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.775855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7eff0f70-3131-4964-a969-608d835e3137 · outbound

This paper cites What makes a good prune? maximal unstructured pruning for maximal cosine similarity,.

Pruning Everything, Everywhere, All at Once What makes a good prune? maximal unstructured pruning for maximal cosine similarity,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.766511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 008c1ede-4799-4454-a108-25c9c0c695c0 · outbound

This paper cites Similarity of neural network representations revisited,.

Pruning Everything, Everywhere, All at Once Similarity of neural network representations revisited,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.757142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 89f949bd-fe28-41c1-947a-9ac8fdaf1ba5 · outbound

This paper cites Compact language models via pruning and knowledge distillation,.

Pruning Everything, Everywhere, All at Once Compact language models via pruning and knowledge distillation,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.748481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5c34e9a5-bde4-42d3-beae-3edff3363865 · outbound

This paper cites Structural pruning via latency-saliency knapsack,.

Pruning Everything, Everywhere, All at Once Structural pruning via latency-saliency knapsack,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.738169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e1f47548-97ec-4e45-91e3-a7d27220f547 · outbound

This paper cites Jointly training and pruning cnns via learnable agent guidance and alignment,.

Pruning Everything, Everywhere, All at Once Jointly training and pruning cnns via learnable agent guidance and alignment,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.727854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0c5e4dde-bbaf-449e-9b43-fb0f9f133eeb · outbound

This paper cites Quantifying the carbon emissions of machine learning,.

Pruning Everything, Everywhere, All at Once Quantifying the carbon emissions of machine learning,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.717527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9e123eca-151a-4bf0-a5d4-cec1fcc05289 · outbound

This paper cites Holistically evaluating the environmental impact of creating language models,.

Pruning Everything, Everywhere, All at Once Holistically evaluating the environmental impact of creating language models,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.707098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2e2364da-3d81-4513-a82e-c67073360c92 · outbound

This paper cites Bilevelpruning: Unified dynamic and static channel pruning for convolutional neural networks,.

Pruning Everything, Everywhere, All at Once Bilevelpruning: Unified dynamic and static channel pruning for convolutional neural networks,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.697826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 72878c8e-1ea9-47b8-9f23-567d657acb41 · outbound

This paper cites Auto-train-once: Controller network guided automatic network pruning from scratch,.

Pruning Everything, Everywhere, All at Once Auto-train-once: Controller network guided automatic network pruning from scratch,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.688130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation cf7339bd-c4cb-482e-b0b5-82f70e3f3b8e · outbound

This paper cites Laco: Large language model pruning via layer collapse,.

Pruning Everything, Everywhere, All at Once Laco: Large language model pruning via layer collapse,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.678783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8d9b8c2f-d88e-416a-825c-01402c55a0fc · outbound

This paper cites The unreasonable ineffectiveness of the deeper layers,.

Pruning Everything, Everywhere, All at Once The unreasonable ineffectiveness of the deeper layers,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.669199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0057769d-de8a-4c57-9ef6-0b49d12273fd · outbound

This paper cites Shortened LLaMA: A simple depth pruning for large language models,.

Pruning Everything, Everywhere, All at Once Shortened LLaMA: A simple depth pruning for large language models,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.658140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fa2fa2ab-e9e4-4006-9139-4e0c2d1c593b · outbound

This paper cites Revisiting random channel pruning for neural network compression,.

Pruning Everything, Everywhere, All at Once Revisiting random channel pruning for neural network compression,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.647343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d836676d-5c7d-4382-ac04-418365aad719 · outbound

This paper cites Measuring statistical dependence with hilbert-schmidt norms,.

Pruning Everything, Everywhere, All at Once Measuring statistical dependence with hilbert-schmidt norms,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.637428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5bd9397d-96ba-47b8-ae53-9b6047a19d23 · outbound

This paper cites When layers play the lottery, all tickets win at initialization,.

Pruning Everything, Everywhere, All at Once When layers play the lottery, all tickets win at initialization,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.626683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9f66c185-db54-4dfb-9775-e5d7afebbcc1 · outbound

This paper cites Neural network pruning with residual-connections and limited-data,.

Pruning Everything, Everywhere, All at Once Neural network pruning with residual-connections and limited-data,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.616993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1ba053f7-1bf2-43e1-9e96-3e3ce7775a9f · outbound

This paper cites Deep residual learning for image recognition,.

Pruning Everything, Everywhere, All at Once Deep residual learning for image recognition,

Reference 24

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Source-reported events for the cited work

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Observation 2f17f4f5-3e72-4b8f-9784-1406f7a98a1b · outbound

This paper cites A simple and effective pruning approach for large language models,.

Pruning Everything, Everywhere, All at Once A simple and effective pruning approach for large language models,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.600422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3e22393d-3443-4d80-b804-c734d6ded89b · outbound

This paper cites Shallowing deep networks: Layer-wise pruning based on feature representations,.

Pruning Everything, Everywhere, All at Once Shallowing deep networks: Layer-wise pruning based on feature representations,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.591512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c342afe3-db8f-41d1-9d0f-2ec18340e894 · outbound

This paper cites Evolutionary shallowing deep neural networks at block levels,.

Pruning Everything, Everywhere, All at Once Evolutionary shallowing deep neural networks at block levels,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.582095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5273fe54-af5f-493a-b9a8-7508b4ce1414 · outbound

This paper cites DECORE: deep compression with reinforcement learning,.

Pruning Everything, Everywhere, All at Once DECORE: deep compression with reinforcement learning,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.572870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ce55b556-4e44-4a62-91ef-5e7f79a102dd · outbound

This paper cites SOKS: automatic searching of the optimal kernel shapes for stripe-wise network pruning,.

Pruning Everything, Everywhere, All at Once SOKS: automatic searching of the optimal kernel shapes for stripe-wise network pruning,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.562929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f7b43201-a00c-4c31-94b7-c928cf9741b6 · outbound

This paper cites Revisit kernel pruning with lottery regulated grouped convolutions,.

Pruning Everything, Everywhere, All at Once Revisit kernel pruning with lottery regulated grouped convolutions,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.553650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3141c9f6-134c-471a-a498-248847781cfe · outbound

This paper cites On the channel pruning using graph convolution network for convolutional neural network acceleration,.

Pruning Everything, Everywhere, All at Once On the channel pruning using graph convolution network for convolutional neural network acceleration,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.544256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d303e2c8-6bf1-45f5-b960-95a7c0c6b37f · outbound

This paper cites Pruning neural networks via coresets and convex geometry: Towards no assumptions,.

Pruning Everything, Everywhere, All at Once Pruning neural networks via coresets and convex geometry: Towards no assumptions,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.533621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 475fcf2e-892d-496b-9138-7062db909e8a · outbound

This paper cites Topology-aware network pruning using multi-stage graph embedding and reinforcement learning,.

Pruning Everything, Everywhere, All at Once Topology-aware network pruning using multi-stage graph embedding and reinforcement learning,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.519123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ba81b484-5306-4b03-a2c5-8fffefe28401 · outbound

This paper cites Carrying out CNN channel pruning in a white box,.

Pruning Everything, Everywhere, All at Once Carrying out CNN channel pruning in a white box,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.509305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 762796b8-161a-41fa-a266-5cc6b066574b · outbound

This paper cites Pruning networks with cross-layer ranking & k-reciprocal nearest filters,.

Pruning Everything, Everywhere, All at Once Pruning networks with cross-layer ranking & k-reciprocal nearest filters,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.499324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 32fc9cf2-9c02-4c93-aa75-2d4ca292cec8 · outbound

This paper cites DAIS: automatic channel pruning via differentiable annealing indicator search,.

Pruning Everything, Everywhere, All at Once DAIS: automatic channel pruning via differentiable annealing indicator search,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.489881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation aef684ab-449f-4949-b041-9c04a02b077b · outbound

This paper cites SOSP: efficiently capturing global correlations by second- order structured pruning,.

Pruning Everything, Everywhere, All at Once SOSP: efficiently capturing global correlations by second- order structured pruning,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.479246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d3050307-8ffe-4cfa-ad0e-3db00f5ba3e3 · outbound

This paper cites Generalized shape metrics on neural representations,.

Pruning Everything, Everywhere, All at Once Generalized shape metrics on neural representations,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.468712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 92eec26f-95dd-4307-aec9-b397a37224ba · outbound

This paper cites Representational dissimilarity metric spaces for stochastic neural networks,.

Pruning Everything, Everywhere, All at Once Representational dissimilarity metric spaces for stochastic neural networks,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.457475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f2d4915a-4de9-46bf-82bb-3ed112a07e15 · outbound

This paper cites Adversarial attack robust dataset pruning,.

Pruning Everything, Everywhere, All at Once Adversarial attack robust dataset pruning,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.446379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0b26e3dc-a0a7-4300-9a50-b9cde4b6f2fb · outbound

This paper cites Adaptive sharpness-aware pruning for robust sparse networks,.

Pruning Everything, Everywhere, All at Once Adaptive sharpness-aware pruning for robust sparse networks,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.436675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ceee8315-4859-408e-8bc5-febe6fa0b489 · outbound

This paper cites Benchmarking neural network robustness to common corruptions and perturbations,.

Pruning Everything, Everywhere, All at Once Benchmarking neural network robustness to common corruptions and perturbations,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.426760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 996a6c11-8487-419f-a2a1-437d062648c5 · outbound

This paper cites Harder or different? a closer look at distribution shift in dataset reproduction,.

Pruning Everything, Everywhere, All at Once Harder or different? a closer look at distribution shift in dataset reproduction,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.416811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 87f4f246-eb6f-4cff-9c17-a7f29f5be030 · outbound

This paper cites Human activity recognition based on smartphone and wearable sensors using multiscale dcnn ensemble,.

Pruning Everything, Everywhere, All at Once Human activity recognition based on smartphone and wearable sensors using multiscale dcnn ensemble,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:45:29.406141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

No inbound Pith citation observations are available.