Pith. sign in

Paper Citation Record · LEDGER

Streaming Chain

As of 10 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2604.04995.

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

pith.paper-citation-record.v1
2604.04995 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-13T10:56:59.609600Z

measured 17 of 17 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

17 of 17 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved17
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cbdbbb7b-4a24-4db1-ad59-29e7851b043e · outbound

This paper cites Model compression and acceleration for deep neural networks: The principles, progress, and challenges,.

Streaming Chain Model compression and acceleration for deep neural networks: The principles, progress, and challenges,

Reference 1

Resolution
unresolved
no resolver link, observed 2026-07-13T10:56:59.609600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T10:56:59.609600Z digest=sha256:2f00d2e75c3a50099bf961dd5d32fd4cb074ed21db890c297e2c057c7a8276c4

Observation ddb9a29d-4d5c-4119-88cd-c08a121bd300 · outbound

This paper cites A comprehensive review of model compression techniques in machine learning,.

Streaming Chain A comprehensive review of model compression techniques in machine learning,

Reference 2

Resolution
unresolved
no resolver link, observed 2026-07-13T10:56:59.609600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T10:56:59.609600Z digest=sha256:a9a2a51fc264fb0b95fbe6dcc72c984d647bf3222d02abe1f36946babd3f6c53

Observation 21f2525a-1634-40ec-a0fd-9f0ce2a49a86 · outbound

This paper cites Deep neural networks compression: A comparative survey and choice recommenda- tions,.

Streaming Chain Deep neural networks compression: A comparative survey and choice recommenda- tions,

Reference 3

Resolution
unresolved
no resolver link, observed 2026-07-13T10:56:59.609600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T10:56:59.609600Z digest=sha256:a0710d5c5aefd6ff9b45cb29855a8163590266d085a8f23cc6bb6f3392165f76

Observation 30ed1c1e-2a45-41ea-8181-d18b7429e858 · outbound

This paper cites Deep neural network compression by in- parallel pruning-quantization,.

Streaming Chain Deep neural network compression by in- parallel pruning-quantization,

Reference 4

Resolution
unresolved
no resolver link, observed 2026-07-13T10:56:59.609600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T10:56:59.609600Z digest=sha256:2f3c38e36b8f8482a056e5e458772883eb856b5f16a28b299cc9103b7fdcab12

Observation 7643f1a3-9336-4574-a4ec-7617a12d44c4 · outbound

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

Streaming Chain A survey on deep neural network pruning: Taxonomy, comparison, analysis, and recommendations,

Reference 5

Resolution
unresolved
no resolver link, observed 2026-07-13T10:56:59.609600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T10:56:59.609600Z digest=sha256:11f512e59a8e30056fd719e3e8c0a17baa30a866edba9dfbe809d5c1290b1da8

Observation 0a166845-e118-4cd5-963c-2967f467cf5a · outbound

This paper cites Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights.

Streaming Chain Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights

Reference 6

Resolution
unresolved
no resolver link, observed 2026-07-13T10:56:59.609600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T10:56:59.609600Z digest=sha256:a9b63153e0ad57392597bcfc4a52dceab71b5b120002d823ee4e580ebb13f2ae

Observation 5a1a3cf1-fb1e-411e-91c5-9e77b5720469 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Streaming Chain Distilling the Knowledge in a Neural Network

Reference 7

Resolution
unresolved
no resolver link, observed 2026-07-13T10:56:59.609600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T10:56:59.609600Z digest=sha256:c14080a502adead8aaf93a3aca60d4c3e868602a8babbd571787ccbd68adb0c3

Observation bdd191b7-edf4-4850-992d-25172cb6d820 · outbound

This paper cites Boosting pruned networks with linear over-parameterization,.

Streaming Chain Boosting pruned networks with linear over-parameterization,

Reference 8

Resolution
unresolved
no resolver link, observed 2026-07-13T10:56:59.609600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T10:56:59.609600Z digest=sha256:fae8cbaea3eb2d578ae00a554e7b0f4a5ab5d6911b08c619c129a1c444802945

Observation 5f500b36-8405-4893-914c-56c73f4e53c5 · outbound

This paper cites PQK: Model Compression via Pruning, Quantization, and Knowledge Distillation.

Streaming Chain PQK: Model Compression via Pruning, Quantization, and Knowledge Distillation

Reference 9

Resolution
unresolved
no resolver link, observed 2026-07-13T10:56:59.609600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T10:56:59.609600Z digest=sha256:11ce5624851fb495bb602e7248334d5152858b30de6c2c8bbd18f875dc26b329

Observation b65c1dfb-7eee-4b1f-9d25-7788497d7902 · outbound

This paper cites Comp-diff: A unified pruning and distillation framework for compressing diffusion models,.

Streaming Chain Comp-diff: A unified pruning and distillation framework for compressing diffusion models,

Reference 10

Resolution
unresolved
no resolver link, observed 2026-07-13T10:56:59.609600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T10:56:59.609600Z digest=sha256:3fdd0bd2bc83f0d9924de65df5dc6de7456f088515471fe380f96cef76213ebb

Observation f6d7b251-3d7c-4ebf-a69c-b4e989cf02d4 · outbound

This paper cites Pruning and quantization for deep neural network acceleration: A survey,.

Streaming Chain Pruning and quantization for deep neural network acceleration: A survey,

Reference 11

Resolution
unresolved
no resolver link, observed 2026-07-13T10:56:59.609600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T10:56:59.609600Z digest=sha256:685ac6c37cc6113906a7a16c2dea0299a0cd908cdb6a4d4a09f1c34f773ab98f

Observation 149973d8-a86e-4c50-bdd3-8b209cd3daaf · outbound

This paper cites The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks.

Streaming Chain The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks

Reference 12

Resolution
unresolved
no resolver link, observed 2026-07-13T10:56:59.609600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T10:56:59.609600Z digest=sha256:320f97059bd5826e631c6f115abc76bf0e26a9e05b3dc41a0b79b028fbe90500

Observation 8bf82c70-95f5-425c-a304-d789b1280c85 · outbound

This paper cites SNIP: Single-shot Network Pruning based on Connection Sensitivity.

Streaming Chain SNIP: Single-shot Network Pruning based on Connection Sensitivity

Reference 13

Resolution
unresolved
no resolver link, observed 2026-07-13T10:56:59.609600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T10:56:59.609600Z digest=sha256:eb767cfd7d92c833d56ad46e910935fd09232c65b26829fb8513104db49430f2

Observation 28eee23a-a5ea-4a1d-a1ac-b8f3b9cc0c44 · outbound

This paper cites DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients.

Streaming Chain DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients

Reference 14

Resolution
unresolved
no resolver link, observed 2026-07-13T10:56:59.609600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T10:56:59.609600Z digest=sha256:354d8dbd01e6926c396f3c954c33129046e66d7de59a529ccdcaab7ad050989c

Observation c81116b7-85bc-4a43-a97a-565e43699293 · outbound

This paper cites Learned Step Size Quantization.

Streaming Chain Learned Step Size Quantization

Reference 15

Resolution
unresolved
no resolver link, observed 2026-07-13T10:56:59.609600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T10:56:59.609600Z digest=sha256:b32ee7bf81bda5fde1a0a3de28f5d6e98fa1651a19471d510f388bd738157e55

Observation f1490c89-7365-4207-a889-2a3e8aa0d2a6 · outbound

This paper cites Contrastive Representation Distillation.

Streaming Chain Contrastive Representation Distillation

Reference 16

Resolution
unresolved
no resolver link, observed 2026-07-13T10:56:59.609600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T10:56:59.609600Z digest=sha256:16492d91d1f95a9625a676165810cfbb572669023008f006c73a882c4411566a

Observation cd391fef-4f10-4d57-82b8-9eff3590b800 · outbound

This paper cites Once-for-All: Train One Network and Specialize it for Efficient Deployment.

Streaming Chain Once-for-All: Train One Network and Specialize it for Efficient Deployment

Reference 17

Resolution
unresolved
no resolver link, observed 2026-07-13T10:56:59.609600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T10:56:59.609600Z digest=sha256:9f78ae1301723f31ea1470a7157725d33097ce4c217387b873135d65613c9f6a

Pith citing papers

No inbound Pith citation observations are available.