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Paper Citation Record · LEDGER

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning

As of 14 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 0 inbound Pith citation observations for arXiv:2501.16917.

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

pith.paper-citation-record.v1
2501.16917 v1

Coverage vector

measured 61 of 61 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T05:42:01.225701Z

measured 61 of 61 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

61 of 61 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 91903f96-6414-40f3-b75d-78f345a9212f · outbound

This paper cites FDLite: A Single Stage Lightweight Face Detector Network.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning FDLite: A Single Stage Lightweight Face Detector Network

Reference 1

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Observation 6cb0b5ea-ecea-4976-9aa2-e850c655faad · outbound

This paper cites Struc- tured pruning of deep convolutional neural networks.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Struc- tured pruning of deep convolutional neural networks

Reference 2

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Observation 52a3ec25-8b50-4935-8578-9e055eaa6d4b · outbound

This paper cites Efficient neural net- work pruning using model-based reinforcement learning.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Efficient neural net- work pruning using model-based reinforcement learning

Reference 3

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Observation 3d9944e4-5f5c-4ae4-8433-6db8fbe31d1f · outbound

This paper cites The exploration-exploitation dilemma: a multidisci- plinary framework.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning The exploration-exploitation dilemma: a multidisci- plinary framework

Reference 4

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Observation 749c4286-edda-40c3-998b-75112b8fe88c · outbound

This paper cites Learning compact representations of neural networks using discrim- inative masking (DAM).

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Learning compact representations of neural networks using discrim- inative masking (DAM)

Reference 5

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Observation 323aaa9d-d785-4ff4-868e-e6fafc6a851f · outbound

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

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning A survey on deep neural network pruning: Taxonomy, compar- ison, analysis, and recommendations

Reference 6

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Observation d030f02f-3c80-49f3-906c-ff71494fbda3 · outbound

This paper cites Basic enhancement strategies when using bayesian optimization for hyperparam- eter tuning of deep neural networks.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Basic enhancement strategies when using bayesian optimization for hyperparam- eter tuning of deep neural networks

Reference 7

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Observation fbabdc5c-acec-4b80-b85e-618a7689c809 · outbound

This paper cites Retinaface: Single-shot multi-level face localisation in the wild.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Retinaface: Single-shot multi-level face localisation in the wild

Reference 8

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Observation 337ef26a-f27c-4963-b449-5b85b186a860 · outbound

This paper cites Real-time face detection and tracking on mobile phones for criminal detection.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Real-time face detection and tracking on mobile phones for criminal detection

Reference 9

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Observation 9a8a45f4-cd5e-461d-b9d9-3de13e245165 · outbound

This paper cites Depgraph: Towards any structural pruning.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Depgraph: Towards any structural pruning

Reference 10

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Observation e6b64f1a-1952-49c1-b3d9-120e62508ce3 · outbound

This paper cites A Tutorial on Bayesian Optimization.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning A Tutorial on Bayesian Optimization

Reference 11

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Observation 908b20dc-3041-4f8f-8371-f29991b1a93d · outbound

This paper cites Filter-pruning of lightweight face detectors using a geometric median criterion.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Filter-pruning of lightweight face detectors using a geometric median criterion

Reference 12

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Observation b7c10280-fa87-4c1c-a490-7a2f8a89e8ae · outbound

This paper cites Fast and control- lable post-training sparsity: Learning optimal sparsity allo- cation with global constraint in minutes.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Fast and control- lable post-training sparsity: Learning optimal sparsity allo- cation with global constraint in minutes

Reference 13

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Source-reported events for the cited work

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Observation 91e188af-9fbf-443c-bceb-96c6207f1822 · outbound

This paper cites Sample and computation redistribution for effi- cient face detection.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Sample and computation redistribution for effi- cient face detection

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 76c0ca58-dc66-47d4-84b6-6e47d4e72f3c · outbound

This paper cites Learning to Prune Deep Neural Networks via Reinforcement Learning.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Learning to Prune Deep Neural Networks via Reinforcement Learning

Reference 15

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Observation 9b781b42-a10a-4afc-972b-8118dbe140a0 · outbound

This paper cites Cap: Context-aware pruning for semantic segmentation.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Cap: Context-aware pruning for semantic segmentation

Reference 16

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Observation a8807319-d0d4-4c8c-9f20-62ff1e1f693a · outbound

This paper cites Soft filter pruning for accelerating deep convolutional neural networks.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Soft filter pruning for accelerating deep convolutional neural networks

Reference 17

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Observation 71d2b53c-4111-4333-a80c-e0b361e67bfb · outbound

This paper cites Amc: Automl for model compression and accel- eration on mobile devices.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Amc: Automl for model compression and accel- eration on mobile devices

Reference 18

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Observation 3c42b274-fe26-4332-aff2-a90322cf820a · outbound

This paper cites Filter pruning via Geometric Median for deep convolutional neural networks acceleration.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Filter pruning via Geometric Median for deep convolutional neural networks acceleration

Reference 19

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Observation 65cbe0df-74ab-49ce-92ca-b334fd3e1a6a · outbound

This paper cites LFFD: A Light and Fast Face Detector for Edge Devices.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning LFFD: A Light and Fast Face Detector for Edge Devices

Reference 20

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Observation 7db273fa-44b1-4054-aa3a-a4e5ec3dc5a3 · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 21

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Observation 98fceb89-f9f0-4862-bfb5-6e6dfec67869 · outbound

This paper cites Control of exploitation–exploration meta-parameter in reinforcement learning.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Control of exploitation–exploration meta-parameter in reinforcement learning

Reference 22

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Observation a41c4b62-514e-4844-9aab-4cb70a28c64b · outbound

This paper cites EResFD: Rediscovery of the effectiveness of standard convolution for lightweight face detection.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning EResFD: Rediscovery of the effectiveness of standard convolution for lightweight face detection

Reference 23

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Observation cf341ce5-8935-4e97-8807-0af991bf0020 · outbound

This paper cites A review of yolo algorithm developments.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning A review of yolo algorithm developments

Reference 24

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Observation d0667a14-6337-4c3c-b23c-3e84416208cb · outbound

This paper cites Learning lightweight face detector with knowledge distillation.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Learning lightweight face detector with knowledge distillation

Reference 25

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This paper cites A review on genetic algorithm: past, present, and future.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning A review on genetic algorithm: past, present, and future

Reference 26

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Observation 5fd26da5-2c07-4409-a7a8-960600c11286 · outbound

This paper cites Face de- tection techniques: a review.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Face de- tection techniques: a review

Reference 27

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Observation 5bd829fe-ff2b-43ec-9085-1fb4a5f873cf · outbound

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B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Pruning filters for efficient convnets

Reference 28

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Observation dd967f4f-91bc-4165-8b3c-8c4589097a3e · outbound

This paper cites DSFD: dual shot face detector.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning DSFD: dual shot face detector

Reference 29

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This paper cites Differentiable transportation pruning.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Differentiable transportation pruning

Reference 30

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Observation 5ee4c9ac-ebd6-42fe-9dde-37cb8f2c5d80 · outbound

This paper cites PruneFaceDet: Pruning lightweight face detection network by sparsity training.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning PruneFaceDet: Pruning lightweight face detection network by sparsity training

Reference 31

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Observation 5bc68127-5395-4cdd-9fbd-245d9846f84e · outbound

This paper cites Layer importance estimation with imprinting for neural network quantization.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Layer importance estimation with imprinting for neural network quantization

Reference 32

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Observation 8c2886cb-e762-4724-b2fc-31a15fe100c8 · outbound

This paper cites SSD: Single shot multibox detector.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning SSD: Single shot multibox detector

Reference 33

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Observation b639d6f5-d8f8-480f-a011-4702f0d8c4cf · outbound

This paper cites Revisiting token pruning for object detection and instance segmentation.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Revisiting token pruning for object detection and instance segmentation

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:42:01.819552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.095402Z digest=sha256:08bc1142698837b6622b192149005d3b4aa85db91f6ef020052b8d43a4d3670b

Observation 4b3c2946-5e58-499b-879c-b1e46ae567b0 · outbound

This paper cites ThiNet: A filter level pruning method for deep neural network compression.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning ThiNet: A filter level pruning method for deep neural network compression

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-10T05:42:01.804332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.100319Z digest=sha256:b2deaeed4b2b96bee4d96c6023dac83212b89cc688a22fc5e862ac99d6c80665

Observation 00c6eae4-99d0-4acd-a045-9e72869fae8e · outbound

This paper cites Llm-pruner: On the structural pruning of large language models.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Llm-pruner: On the structural pruning of large language models

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-10T05:42:01.788783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.105052Z digest=sha256:88343ed29af761a9c1c44cca37af95937e242c0305949d90cce72e697ca5a2a9

Observation 5fb34d78-556c-4126-96b7-0e7eb34402df · outbound

This paper cites Going Deeper Into Face Detection: A Survey.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Going Deeper Into Face Detection: A Survey

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-08-10T05:42:01.355047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.111330Z digest=sha256:6ce2b931ea8bafb088df43c1e5eae67cc4f948a5c29dead314728cefc8b0a7e7

Observation b22f5987-37b4-4c1c-a515-87cbe926fe31 · outbound

This paper cites Importance estimation for neural network pruning.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Importance estimation for neural network pruning

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:42:01.772660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.116770Z digest=sha256:08b8c0e5e99bfcc0c796c96a4d665711404272e608d659fd0c0290949efeb904

Observation 99bd0bbc-727c-498b-8990-a135294e5c98 · outbound

This paper cites Channel-level acceleration of deep face representations.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Channel-level acceleration of deep face representations

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:42:01.756634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.121825Z digest=sha256:f198ce05a69c8f384dda1460164d43dbc7b7d4e25b1a995c02d2fed12e0a91a1

Observation 26891a75-3ca0-43de-bebc-48ee1f5b146d · outbound

This paper cites YOLO5Face: why reinventing a face detector.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning YOLO5Face: why reinventing a face detector

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:42:01.741212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.126623Z digest=sha256:6b64b48ba80a7716ddeb1fc705d861b32c702f33ae479b7774c73142bfa640b5

Observation f7dd6e32-d3c7-40bf-bcff-e55d0fa3db7c · outbound

This paper cites Automatic enemy detecting defense robot by using face detection technique’.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Automatic enemy detecting defense robot by using face detection technique’

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:42:01.725177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.131376Z digest=sha256:45789bbf54de961ebe27b8fb642363618e1a56fc86f25c723dae722c26dc6d09

Observation aaccaefa-d68c-4717-8c57-840b754ea1f9 · outbound

This paper cites Deep learning-based face detection and recognition on drones.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Deep learning-based face detection and recognition on drones

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:42:01.709616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.136253Z digest=sha256:52ef2d308664b07d8500f084de49c164c6606f2904740945a1f26670ad13452b

Observation 0dfe09fa-f4b6-4264-b6d4-f8bd215ae515 · outbound

This paper cites Deep feature-based face detection on mobile devices.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Deep feature-based face detection on mobile devices

Reference 43

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verified fuzzy
raw_fallback, observed 2026-08-10T05:42:01.693529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.141094Z digest=sha256:221e85aa08af5e05f5d2edbca3ec3dc9f944730d114fad2041d5360a72991899

Observation fce10583-0167-4cd6-896c-ab39fef82f0c · outbound

This paper cites Taking the human out of the loop: A review of bayesian optimization.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Taking the human out of the loop: A review of bayesian optimization

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:42:01.677727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.146026Z digest=sha256:de70352a130db7c90ed1a78afe3a3ea24e3bb0b47c3b462776e2cc6066a5cd03

Observation ebd9d8f8-ba34-4b74-85e4-2f7c9766e1ba · outbound

This paper cites Prac- tical bayesian optimization of machine learning algorithms.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Prac- tical bayesian optimization of machine learning algorithms

Reference 45

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verified fuzzy
raw_fallback, observed 2026-08-10T05:42:01.662069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.151070Z digest=sha256:633ff4697024bdb4d14ba3f79f9fc1bf5148363c4daee36cd9d41fa78c362293

Observation 3453ff7c-47b0-460e-b089-16c9124e23a9 · outbound

This paper cites Gaussian process optimization in the ban- dit setting: No regret and experimental design.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Gaussian process optimization in the ban- dit setting: No regret and experimental design

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:42:01.646431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.155433Z digest=sha256:14d9ec918fd6fcb1d6712bd67847c610742633251203cf34119e5df234c482eb

Observation 4e393f14-4ec9-4bcf-abcf-5b434d1c8bb4 · outbound

This paper cites A Simple and Effective Pruning Approach for Large Language Models.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning A Simple and Effective Pruning Approach for Large Language Models

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-10T05:42:01.159657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T05:42:01.159657Z digest=sha256:c3bc340e58aa99bd64131ab9ac5238f576d6d4682ce47b1ed55cd83f5518fa70

Observation 1e5e5006-3503-4c16-925c-0e13a9c98018 · outbound

This paper cites Pyra- midbox: A context-assisted single shot face detector.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Pyra- midbox: A context-assisted single shot face detector

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:42:01.631393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.164204Z digest=sha256:6b74355e8df1dad58d6267f52b90780bf1922fb0567101f80df1f0a42f550999

Observation 9bae3662-f0e1-45fb-892a-06ba73966d54 · outbound

This paper cites ChipNet: Budget-aware pruning with heaviside con- tinuous approximations.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning ChipNet: Budget-aware pruning with heaviside con- tinuous approximations

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:42:01.617099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.168560Z digest=sha256:44a2317a8a62720972bc5c999dfb10ab28b47f284cc5ec201396c67133d25b30

Observation f80ade69-5d9a-4c4b-b90c-a2d0f39098b1 · outbound

This paper cites Fine-Pruning: Joint Fine-Tuning and Compression of a Convolutional Network with Bayesian Optimization.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Fine-Pruning: Joint Fine-Tuning and Compression of a Convolutional Network with Bayesian Optimization

Reference 50

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unresolved
no resolver link, observed 2026-08-10T05:42:01.173000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T05:42:01.173000Z digest=sha256:15411667b8170d10069dc42256bad1693952c322a6156d73c9c2cfd022c3a9fb

Observation 07d30b11-78e5-488d-97e2-293416b0fc7a · outbound

This paper cites Multimodal approach to human-face detection and tracking.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Multimodal approach to human-face detection and tracking

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:42:01.602207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.177946Z digest=sha256:2286c001acdb38c9d4e08200c60c67db602a0800dec69a4e8c10e3a115b14a2d

Observation f498f4fb-b3e9-4925-a9bd-22df0c62ba0d · outbound

This paper cites Deep rein- forcement learning: A survey.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Deep rein- forcement learning: A survey

Reference 52

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verified fuzzy
raw_fallback, observed 2026-08-10T05:42:01.587441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.182379Z digest=sha256:1e4641a7369b7d9e3bbb145a260aaedabea6018fd7bf602e7c9a689d19f479b9

Observation b859abfa-1ffb-49dd-8d6d-0ac628188149 · outbound

This paper cites Yunet: A tiny millisecond-level face detector.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Yunet: A tiny millisecond-level face detector

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:42:01.571835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.186972Z digest=sha256:da077fe3ff9f6741c19b4fbb51f44b59ebb12fa27f1f8c1046c33dfd0651b38a

Observation e805cbbc-ccda-4862-af13-2a48d861debb · outbound

This paper cites Joint face detection and facial expression recognition with MTCNN.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Joint face detection and facial expression recognition with MTCNN

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:42:01.555952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.191774Z digest=sha256:589e513e42595ca0b42c2bd3dc672db3054c33ce25a613cf7747682adaf79f40

Observation 5a695b2e-6c39-46b9-8fe4-645621d0256d · outbound

This paper cites WIDER FACE: A face detection benchmark.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning WIDER FACE: A face detection benchmark

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:42:01.539421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.196577Z digest=sha256:e74b72ee7ba5f055c974de34a3a4ba69963d8ee51f38809142aea2655d6ae1a8

Observation f773224a-287d-4ad3-8407-1e8034ccdad4 · outbound

This paper cites EXTD: Extremely Tiny Face Detector via Iterative Filter Reuse.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning EXTD: Extremely Tiny Face Detector via Iterative Filter Reuse

Reference 56

Resolution
verified exact
local_arxiv, observed 2026-08-10T05:42:01.297626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.201575Z digest=sha256:e99805567351ad3303451f1626819e344aa34d5a4135f650a97ccb19385b9989

Observation a7f9452b-6847-44d1-94c8-2db292656dec · outbound

This paper cites Faceboxes: A CPU real-time face de- tector with high accuracy.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Faceboxes: A CPU real-time face de- tector with high accuracy

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:42:01.522814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.207082Z digest=sha256:fa8569fe3ed59c0a999fd3bc846029a30d1db9e30478c1d0f3ec22a52e95d97b

Observation 1729da13-62a8-4f0d-b3cb-b563152e4c51 · outbound

This paper cites S3FD: Single shot scale-invariant face detector.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning S3FD: Single shot scale-invariant face detector

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:42:01.507207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.211827Z digest=sha256:2dc1784b618dc96a19d10d0681a4241f629f2e83f68bc0c6969d3fb9d605d4fa

Observation 77945d39-01fc-4f11-ab53-d2c52fd54107 · outbound

This paper cites Real-time multi-scale face detector on em- bedded devices.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Real-time multi-scale face detector on em- bedded devices

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:42:01.490746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.216365Z digest=sha256:5eab68d32d17425d103295a852a3e7ed2353919911528064631ad47fbdc9f1b7

Observation f8776a4e-27bd-48be-b6be-5a39c0d491cf · outbound

This paper cites Real-time multi-scale face detector on em- bedded devices.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning Real-time multi-scale face detector on em- bedded devices

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:42:01.474421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.220945Z digest=sha256:b156c74d0cef32d30d94f0d19ab1c7ba275e2287984752752c089a4f032adb83

Observation ac1e06b1-1518-48d9-b272-ab769872e876 · outbound

This paper cites TinaFace: Strong but Simple Baseline for Face Detection.

B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning TinaFace: Strong but Simple Baseline for Face Detection

Reference 61

Resolution
verified exact
local_arxiv, observed 2026-08-10T05:42:01.273362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T05:42:01.225701Z digest=sha256:0b2e4122c810cec28e70956d6031877be1a288c98eac82e7b4464b2a47fcfcd7

Pith citing papers

No inbound Pith citation observations are available.