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Paper Citation Record · LEDGER

Structured Pruning and Quantization for Learned Image Compression

As of 13 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 1 inbound Pith citation observation for arXiv:2506.01229.

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

pith.paper-citation-record.v1
2506.01229 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:51:38.152066Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:51:36.667838Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T11:51:38.234828Z

Reference resolution

44 of 44 outbound references displayed

  • verified exact0
  • verified fuzzy34
  • unresolved7
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f9c1a19e-bfc6-446c-a9d0-8bea142433ac · outbound

This paper cites Structured Pruning and Quantization for Learned Image Compression.

Structured Pruning and Quantization for Learned Image Compression Structured Pruning and Quantization for Learned Image Compression

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation a75316cd-e82b-4a46-a27a-5e0bb796962f · outbound

This paper cites Learned Image Compression Learned Image Compression is a form of image source coding that operates in the transform coding paradigm.

Structured Pruning and Quantization for Learned Image Compression Learned Image Compression Learned Image Compression is a form of image source coding that operates in the transform coding paradigm

Reference 2

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Observation ee56e81e-e1b1-432e-b986-0aa5f8f1d355 · outbound

This paper cites Next, we demon- strate our proposed NAS procedure for determining the layer- wise pruning ratio of the pruned model.

Structured Pruning and Quantization for Learned Image Compression Next, we demon- strate our proposed NAS procedure for determining the layer- wise pruning ratio of the pruned model

Reference 3

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Source-reported events for the cited work

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Observation 88043b20-de7d-48b9-a56c-c135de7c8916 · outbound

This paper cites Next, we show the coding performance of our proposed pruning methods across dif- ferent model sizes.

Structured Pruning and Quantization for Learned Image Compression Next, we show the coding performance of our proposed pruning methods across dif- ferent model sizes

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation fff91e65-998c-4c87-8228-a7780f1b849c · outbound

This paper cites We perform experiments to show that simultane- ously pruning filters and filter channels can produce better Fig.

Structured Pruning and Quantization for Learned Image Compression We perform experiments to show that simultane- ously pruning filters and filter channels can produce better Fig

Reference 5

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 525434bb-5442-461c-9629-501ba319ed0e · outbound

This paper cites Variational image compression with a scale hyperprior.

Structured Pruning and Quantization for Learned Image Compression Variational image compression with a scale hyperprior

Reference 6

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Source-reported events for the cited work

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Observation aa44e2d4-779f-4709-a129-3fdb3e4ecf63 · outbound

This paper cites Joint autore- gressive and hierarchical priors for learned image compression,.

Structured Pruning and Quantization for Learned Image Compression Joint autore- gressive and hierarchical priors for learned image compression,

Reference 7

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 239362bd-06ba-449e-a99c-7cd020089a83 · outbound

This paper cites Lossy im- age compression with quantized hierarchical vaes,.

Structured Pruning and Quantization for Learned Image Compression Lossy im- age compression with quantized hierarchical vaes,

Reference 8

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation b4cda817-8f94-43bb-8833-50d6ad45cdeb · outbound

This paper cites Qarv: Quantization-aware resnet vae for lossy image compression,.

Structured Pruning and Quantization for Learned Image Compression Qarv: Quantization-aware resnet vae for lossy image compression,

Reference 9

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Observation 450da2d5-129a-479a-b49f-97035e302d4e · outbound

This paper cites Mlic: Multi-reference entropy model for learned image compression,.

Structured Pruning and Quantization for Learned Image Compression Mlic: Multi-reference entropy model for learned image compression,

Reference 10

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Observation 6efd806f-e7ba-4a45-9fc4-0844a7f6a4f5 · outbound

This paper cites The jpeg still picture compression standard,.

Structured Pruning and Quantization for Learned Image Compression The jpeg still picture compression standard,

Reference 11

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Observation 153b90b5-f5ae-4396-9bc6-d81d9f89ff89 · outbound

This paper cites Overview of the versatile video cod- ing (vvc) standard and its applications,.

Structured Pruning and Quantization for Learned Image Compression Overview of the versatile video cod- ing (vvc) standard and its applications,

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 3485225b-7c7b-4573-ab82-76779bea13af · outbound

This paper cites Effi- cient neural image decoding via fixed-point inference,.

Structured Pruning and Quantization for Learned Image Compression Effi- cient neural image decoding via fixed-point inference,

Reference 13

Resolution
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Source-reported events for the cited work

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Observation 4dfaf016-c9d1-4f67-83ed-84efe7be0af2 · outbound

This paper cites End-to-end learned image compression with fixed point weight quan- tization,.

Structured Pruning and Quantization for Learned Image Compression End-to-end learned image compression with fixed point weight quan- tization,

Reference 14

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 541b34be-cf6d-4539-83af-ad248af1e36c · outbound

This paper cites Learned image compression with fixed-point arithmetic,.

Structured Pruning and Quantization for Learned Image Compression Learned image compression with fixed-point arithmetic,

Reference 15

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 8512d92e-621d-42d2-a500-4e0aeb867568 · outbound

This paper cites Rate-distortion optimized post- training quantization for learned image compression,.

Structured Pruning and Quantization for Learned Image Compression Rate-distortion optimized post- training quantization for learned image compression,

Reference 16

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation f98e5c5e-9dd1-452a-aa75-38de10b163c9 · outbound

This paper cites Integer quantized learned image compression,.

Structured Pruning and Quantization for Learned Image Compression Integer quantized learned image compression,

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation eb064f4e-f132-461f-8b17-be48b55aecc6 · outbound

This paper cites Memory-efficient learned image compression with pruned hyperprior module,.

Structured Pruning and Quantization for Learned Image Compression Memory-efficient learned image compression with pruned hyperprior module,

Reference 18

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation e0e43df4-73f5-4ada-b069-778c4f6a65fd · outbound

This paper cites Efficient decoder for learned image com- pression via structured pruning,.

Structured Pruning and Quantization for Learned Image Compression Efficient decoder for learned image com- pression via structured pruning,

Reference 19

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 528d083e-c5b1-41c3-a4f7-d8301a6cb450 · outbound

This paper cites Complexity scalable learning-based image decoding,.

Structured Pruning and Quantization for Learned Image Compression Complexity scalable learning-based image decoding,

Reference 20

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation fd838bc5-8673-40eb-81d0-b88dfab56b6e · outbound

This paper cites Unified data-free compression: Pruning and quantization without fine- tuning,.

Structured Pruning and Quantization for Learned Image Compression Unified data-free compression: Pruning and quantization without fine- tuning,

Reference 21

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 042a83b5-476a-4c4e-9ef3-e9faba9902b6 · outbound

This paper cites Filter prun- ing via geometric median for deep convolutional neural networks ac- celeration,.

Structured Pruning and Quantization for Learned Image Compression Filter prun- ing via geometric median for deep convolutional neural networks ac- celeration,

Reference 22

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Observation 1f7caab9-a8e2-44ec-8ec5-a238300cfb04 · outbound

This paper cites Hrank: Filter pruning using high-rank feature map,.

Structured Pruning and Quantization for Learned Image Compression Hrank: Filter pruning using high-rank feature map,

Reference 23

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Source-reported events for the cited work

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Observation bbf058e0-47c9-4a42-9900-a6cf4c45ccaf · outbound

This paper cites Scop: Scientific control for reliable neu- ral network pruning,.

Structured Pruning and Quantization for Learned Image Compression Scop: Scientific control for reliable neu- ral network pruning,

Reference 24

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 38eb4800-eb23-4785-a29a-e2bb5f127424 · outbound

This paper cites Chip: Channel independence-based pruning for compact neural networks,.

Structured Pruning and Quantization for Learned Image Compression Chip: Channel independence-based pruning for compact neural networks,

Reference 25

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation e00c3a2c-1107-47c0-9381-4000bab33fa7 · outbound

This paper cites Fast convnets using group-wise brain damage,.

Structured Pruning and Quantization for Learned Image Compression Fast convnets using group-wise brain damage,

Reference 26

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 92ea115a-f783-4c80-a751-dea708427867 · outbound

This paper cites Pruning filter in filter,.

Structured Pruning and Quantization for Learned Image Compression Pruning filter in filter,

Reference 27

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 70c35e47-22f1-485a-8f44-4b1110f78286 · outbound

This paper cites Pconv: The missing but desirable sparsity in dnn weight pruning for real-time execution on mobile de- vices,.

Structured Pruning and Quantization for Learned Image Compression Pconv: The missing but desirable sparsity in dnn weight pruning for real-time execution on mobile de- vices,

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 7cb892cf-beec-4988-9ebf-3b2442fe2153 · outbound

This paper cites Learning both weights and connections for efficient neural network,.

Structured Pruning and Quantization for Learned Image Compression Learning both weights and connections for efficient neural network,

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 233b3bac-f7ec-4217-b45e-9c085a7843a6 · outbound

This paper cites Importance estimation for neural network pruning,.

Structured Pruning and Quantization for Learned Image Compression Importance estimation for neural network pruning,

Reference 30

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 01b501f4-a183-41fd-bdef-54057fda7cd4 · outbound

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

Structured Pruning and Quantization for Learned Image Compression Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks

Reference 31

Resolution
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no resolver link, observed 2026-08-07T11:51:37.752820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:51:37.752820Z digest=sha256:69aa42d5e3b88347eee26b450be5ad7ade2406fdb62756e33b912cf6d681d35c

Observation c1ee5c1b-4b37-4bd7-9596-41e02b9d2627 · outbound

This paper cites Amc: Automl for model compression and acceleration on mobile de- vices,.

Structured Pruning and Quantization for Learned Image Compression Amc: Automl for model compression and acceleration on mobile de- vices,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:51:38.858065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T11:51:37.789092Z digest=sha256:4e9221ae8b3a93fbf9c4dfac50ed82af4b974f9597eff9e339108878e7aeab68

Observation feee4dc2-934f-43c8-b5e3-baa84f56da9a · outbound

This paper cites Metapruning: Meta learning for automatic neural network channel pruning,.

Structured Pruning and Quantization for Learned Image Compression Metapruning: Meta learning for automatic neural network channel pruning,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:51:38.783904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T11:51:37.823013Z digest=sha256:786ab0e3ee6374c58d27aac1049269f434e7a7e4377f7ffbcce2ffab0a8cc3c8

Observation a4b138e4-9ed8-4b79-9705-46e8937811b1 · outbound

This paper cites Dmcp: Differentiable markov channel pruning for neural networks,.

Structured Pruning and Quantization for Learned Image Compression Dmcp: Differentiable markov channel pruning for neural networks,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:51:38.717913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 4f5078d9-79b5-47eb-9282-f5692e1f427e · outbound

This paper cites Towards op- timal structured cnn pruning via generative adversarial learning,.

Structured Pruning and Quantization for Learned Image Compression Towards op- timal structured cnn pruning via generative adversarial learning,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:51:38.642741Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T11:51:37.896442Z digest=sha256:6dc486fda81d02990d237221e1889958d3fa66a5992b1c07d8be16a98487cec6

Observation 83c649f3-d37c-43ba-ab10-9f4b14d9e2f4 · outbound

This paper cites Up or down? adaptive rounding for post- training quantization,.

Structured Pruning and Quantization for Learned Image Compression Up or down? adaptive rounding for post- training quantization,

Reference 36

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 13ce9926-2cf7-4b77-922f-3ce20e3d14af · outbound

This paper cites QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quantization.

Structured Pruning and Quantization for Learned Image Compression QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quantization

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T11:51:37.954450Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:51:37.954450Z digest=sha256:43c3c29afa55075040b59f3d696fa2cf0f2554c35b795a36ae085cd5dae1de16

Observation 45f6b19a-e6b4-4f6a-953c-9b8958f338e4 · outbound

This paper cites PACT: Parameterized Clipping Activation for Quantized Neural Networks.

Structured Pruning and Quantization for Learned Image Compression PACT: Parameterized Clipping Activation for Quantized Neural Networks

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T11:51:37.974260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:51:37.974260Z digest=sha256:b8dd3f2dd46288d39c5bb1ce9449c9c3874aced752807ea4112a06e07c925e26

Observation 40d849c3-31e1-42ab-8cce-2d293def07e2 · outbound

This paper cites Learned Step Size Quantization.

Structured Pruning and Quantization for Learned Image Compression Learned Step Size Quantization

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T11:51:38.003222Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:51:38.003222Z digest=sha256:3c8bfa860d7c5ff0f2a741bd38288236f028bcc725f52825a50d312962d9c7db

Observation c85e424b-638c-42d5-84a6-ddaf26ef776e · outbound

This paper cites Network quan- tization with element-wise gradient scaling,.

Structured Pruning and Quantization for Learned Image Compression Network quan- tization with element-wise gradient scaling,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:51:38.569021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T11:51:38.029362Z digest=sha256:8f060ab18d221ac1408002620afd29ead9d77912a1fe91f32ee430d539cc8834

Observation ce78ad25-1f8b-4474-821c-c14642ce6299 · outbound

This paper cites Pruning Filters for Efficient ConvNets.

Structured Pruning and Quantization for Learned Image Compression Pruning Filters for Efficient ConvNets

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T11:51:38.051278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:51:38.051278Z digest=sha256:20c7c10de7ef1656b2d928404efd7d2d2f40a3fd4d28619c15b1543d6e13b7b9

Observation cd334416-9da0-48e9-b85f-b7993a730f0f · outbound

This paper cites Mi- crosoft coco: Common objects in context,.

Structured Pruning and Quantization for Learned Image Compression Mi- crosoft coco: Common objects in context,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:51:38.494073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T11:51:38.083086Z digest=sha256:a87bbb1fac42a0ab05cfd269424719b6231c11ff29b7f55fc7c9dcfa30eeca48

Observation 552571d3-8b56-4743-bc92-a19ac480f1cd · outbound

This paper cites Calculation of average psnr differences between rd-curves,.

Structured Pruning and Quantization for Learned Image Compression Calculation of average psnr differences between rd-curves,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:51:38.420589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T11:51:38.119875Z digest=sha256:6aefcc379285f65d5981e3e04e6e7443f6218a01fd1c4276b92aeae9bae84c62

Observation 290b5316-bff2-4645-a1f4-c879ad8339a1 · outbound

This paper cites Kodak lossless true color image suite (photocd pcd0992),.

Structured Pruning and Quantization for Learned Image Compression Kodak lossless true color image suite (photocd pcd0992),

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:51:38.346511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T11:51:38.152066Z digest=sha256:cd3c3d111bdbd696bd3d095fb570b12613fa9e73bdf8f2c1a63c6287c4b591ca

Pith citing papers

Observation f9c1a19e-bfc6-446c-a9d0-8bea142433ac · inbound

Structured Pruning and Quantization for Learned Image Compression cites this paper.

Structured Pruning and Quantization for Learned Image Compression Structured Pruning and Quantization for Learned Image Compression

Reference 1

Resolution
metadata mismatch
local_arxiv, observed 2026-08-07T11:51:38.272619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T11:51:36.667838Z digest=sha256:8716699715a9982072e34538ba3c326dbf903e8929d32060702c0fe811ab7952