Paper Citation Record · LEDGER

A Survey of Model Compression and Acceleration for Deep Neural Networks

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 30 inbound Pith citation observations for arXiv:1710.09282.

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

pith.paper-citation-record.v1
1710.09282 v9

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 30 of 30 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:50:32.391662Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T03:37:35.883997Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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malformed identifier0
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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 9ec7b532-4c54-4be3-a929-4b7da762f849 · inbound

Group Pruning using a Bounded-Lp norm for Group Gating and Regularization cites this paper.

Group Pruning using a Bounded-Lp norm for Group Gating and Regularization A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 4

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Observation 72e9e5c7-c4bf-4ef9-8c9f-79aabeed21b2 · inbound

JEDI-net: a jet identification algorithm based on interaction networks cites this paper.

JEDI-net: a jet identification algorithm based on interaction networks A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 52

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Observation 381989c4-de2e-4ab5-9c19-b171a3b54e97 · inbound

Restricted Recurrent Neural Networks cites this paper.

Restricted Recurrent Neural Networks A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 5

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Observation 901de54f-141f-4d50-b7e4-1799b1832d8c · inbound

Language Modeling Is Compression cites this paper.

Language Modeling Is Compression A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 4

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Source-reported events for the cited work

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Observation d3d94d24-ac1a-451c-b51c-19a817d5517e · inbound

ASVD: Activation-aware Singular Value Decomposition for Compressing Large Language Models cites this paper.

ASVD: Activation-aware Singular Value Decomposition for Compressing Large Language Models A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-20T13:49:33.806737Z

Source-reported events for the cited work

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Observation 68b1ee71-d573-4453-bc09-1ef64faec237 · inbound

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition cites this paper.

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T20:22:43.594335Z

Source-reported events for the cited work

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Observation 23d135a2-d564-4abb-96bd-ac44da227479 · inbound

Is Oracle Pruning the True Oracle? cites this paper.

Is Oracle Pruning the True Oracle? A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T10:22:09.025260Z

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Observation 654620ec-49ff-41e0-a74a-981d3917502c · inbound

Separate the Wheat from the Chaff: A Post-Hoc Approach to Safety Re-Alignment for Fine-Tuned Language Models cites this paper.

Separate the Wheat from the Chaff: A Post-Hoc Approach to Safety Re-Alignment for Fine-Tuned Language Models A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T15:26:52.462508Z

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Observation ef8354af-14ae-4bf3-ab86-f1919a6324a9 · inbound

Low Rank Based Subspace Inference for the Laplace Approximation of Bayesian Neural Networks cites this paper.

Low Rank Based Subspace Inference for the Laplace Approximation of Bayesian Neural Networks A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:42:27.728661Z

Source-reported events for the cited work

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Observation ff14f3dc-5d70-4473-addd-62db01879b37 · inbound

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives cites this paper.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 13

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Observation c1310b56-6ac4-4264-8559-7fe6a711bf47 · inbound

EfficientLLM: Efficiency in Large Language Models cites this paper.

EfficientLLM: Efficiency in Large Language Models A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-15T20:13:34.780807Z

Source-reported events for the cited work

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Observation d83c6c19-4989-49fa-9427-1bb37040006f · inbound

Smooth Model Compression without Fine-Tuning cites this paper.

Smooth Model Compression without Fine-Tuning A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T12:30:06.748067Z

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Observation ba9c1090-111d-416b-94f4-b82b7664c2ff · inbound

Equally Critical: Samples, Targets, and Their Mappings in Datasets cites this paper.

Equally Critical: Samples, Targets, and Their Mappings in Datasets A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T20:50:32.391662Z

Source-reported events for the cited work

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Observation 164dd18b-e9a1-4477-af30-c60f4e476ab8 · inbound

UnIT: Scalable Unstructured Inference-Time Pruning for MAC-efficient Neural Inference on MCUs cites this paper.

UnIT: Scalable Unstructured Inference-Time Pruning for MAC-efficient Neural Inference on MCUs A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T18:36:42.375343Z

Source-reported events for the cited work

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Observation c64b74a9-3ed2-49d3-af89-5a7316794209 · inbound

FedKLPR: KL-Guided Pruning-Aware Federated Learning for Person Re-Identification cites this paper.

FedKLPR: KL-Guided Pruning-Aware Federated Learning for Person Re-Identification A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-18T21:01:51.160725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7f673da3-a165-431c-92f2-a1fd40930726 · inbound

FedKLPR: KL-Guided Pruning-Aware Federated Learning for Person Re-Identification cites this paper.

FedKLPR: KL-Guided Pruning-Aware Federated Learning for Person Re-Identification A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-21T22:30:42.736037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5b8e66ec-3020-4d5c-9282-26d1febe9be5 · inbound

Foundation Models for Autonomous Driving Perception: A Survey Through Core Capabilities cites this paper.

Foundation Models for Autonomous Driving Perception: A Survey Through Core Capabilities A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 131

Resolution: unresolved; no resolver link, observed 2026-08-04T20:52:06.749915Z

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Observation 303f4ae1-4401-403c-b8de-d30005933a72 · inbound

Modality Alignment with Multi-scale Bilateral Attention for Multimodal Recommendation cites this paper.

Modality Alignment with Multi-scale Bilateral Attention for Multimodal Recommendation A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T19:44:04.714579Z

Source-reported events for the cited work

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Observation 1f11a043-1223-4d84-8a1d-53899f79b6c4 · inbound

CoT-X: An Adaptive Framework for Cross-Model Chain-of-Thought Transfer and Optimization cites this paper.

CoT-X: An Adaptive Framework for Cross-Model Chain-of-Thought Transfer and Optimization A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-03T23:30:23.101407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13e851b6-dc89-4b4c-9010-531678c9e968 · inbound

Sparse-on-Dense: Area and Energy-Efficient Computing of Sparse Neural Networks on Dense Matrix Multiplication Accelerators cites this paper.

Sparse-on-Dense: Area and Energy-Efficient Computing of Sparse Neural Networks on Dense Matrix Multiplication Accelerators A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:11:27.031735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5ffd9b89-4d21-48b9-8e2f-0c0ec358272b · inbound

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices cites this paper.

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 91

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T03:36:19.932712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0f2233c7-61af-4e09-b46b-f1eb5be6cce9 · inbound

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices cites this paper.

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 91

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T07:32:30.274369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c9fd5cc9-fee6-4376-a3b9-896dcd8c68f2 · inbound

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices cites this paper.

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 91

Resolution: metadata mismatch; arxiv_id, observed 2026-05-21T07:59:50.231902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 252dce62-8947-4f75-bfc2-9d81a17efaa4 · inbound

Nonlinear Bipolar Compensation: Handling Outliers in Post-Training Quantization cites this paper.

Nonlinear Bipolar Compensation: Handling Outliers in Post-Training Quantization A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-20T20:59:01.920162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 758f7ff0-2845-4d07-8ec4-6d684eed7a04 · inbound

GPTQ-intrinsic LoRA: A Near-optimal Algorithm for Low-precision Quantization with Low-rank Adaptation cites this paper.

GPTQ-intrinsic LoRA: A Near-optimal Algorithm for Low-precision Quantization with Low-rank Adaptation A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-07-01T21:06:14.399420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 20049b2f-560a-462a-8505-b1cb9e73c595 · inbound

Rethinking Depth: A study of the Recursive-Transformer for Speech Recognition cites this paper.

Rethinking Depth: A study of the Recursive-Transformer for Speech Recognition A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-07-03T03:37:35.885948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0357eab3-0e02-4787-b2ca-0a5819735c04 · inbound

LACE-SVD: Loss-Aware SVD with Cumulative Error Correction for LLM Compression cites this paper.

LACE-SVD: Loss-Aware SVD with Cumulative Error Correction for LLM Compression A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-12T05:11:18.690792Z

Source-reported events for the cited work

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Observation 17e47db2-2722-4e05-b3d5-442f0167671c · inbound

Contrastive Predictive Coding with Compression for Enhanced Channel State Feedback in Wireless Networks cites this paper.

Contrastive Predictive Coding with Compression for Enhanced Channel State Feedback in Wireless Networks A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-12T11:27:53.538015Z

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Unavailable: canonical work link unavailable.

Observation fa3075ae-7cee-4f4d-8383-d4b63355a211 · inbound

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models cites this paper.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-01T03:51:32.502889Z

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Unavailable: canonical work link unavailable.

Observation d11a501a-0a22-4279-a763-f2a9a578ef23 · inbound

Input convex neural networks as surrogates in mathematical optimisation cites this paper.

Input convex neural networks as surrogates in mathematical optimisation A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T12:21:10.082979Z

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Unavailable: canonical work link unavailable.