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Paper Citation Record · LEDGER

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training

As of 8 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2607.15745.

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

pith.paper-citation-record.v1
2607.15745 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T22:29:41.042742Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

22 of 22 outbound references displayed

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External citation measurements

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Outbound references

Observation 66c80e04-4e28-4da4-a5ee-fd2e7c0feb0b · outbound

This paper cites Review of deep learning: concepts, convolutional neural network architectures, challenges, and applications,.

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training Review of deep learning: concepts, convolutional neural network architectures, challenges, and applications,

Reference 1

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Observation f3f71524-1877-4c91-92fc-c940def3138c · outbound

This paper cites A formal basis for the heuristic determination of minimum cost paths,.

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training A formal basis for the heuristic determination of minimum cost paths,

Reference 2

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Observation 3ca67bea-7595-4f9b-83f7-43bdc45d2d1c · outbound

This paper cites A Systematic Literature Review of A* Pathfinding,.

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training A Systematic Literature Review of A* Pathfinding,

Reference 3

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Observation 375894d6-6365-480e-9195-8ddc0d2a0427 · outbound

This paper cites MedMNIST v2: A Large-Scale Lightweight Benchmark for 2D and 3D Biomedical Image Classification,.

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training MedMNIST v2: A Large-Scale Lightweight Benchmark for 2D and 3D Biomedical Image Classification,

Reference 4

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Observation a4a7f93f-4c0b-43aa-bd18-28563848bde8 · outbound

This paper cites Curriculum Learning,.

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training Curriculum Learning,

Reference 5

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Observation 748dee43-ba2b-47d9-aebb-5dd35b0ef823 · outbound

This paper cites Self-Paced Learning for Latent Variable Models,.

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training Self-Paced Learning for Latent Variable Models,

Reference 6

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Observation 4626fb54-7803-4644-8c3b-ee9b991aafc3 · outbound

This paper cites Training Region-Based Object Detectors with Online Hard Example Mining,.

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training Training Region-Based Object Detectors with Online Hard Example Mining,

Reference 7

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Observation 90f97955-e1cf-47a7-8ec4-1330d7e0b603 · outbound

This paper cites Focal Loss for Dense Object Detection,.

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training Focal Loss for Dense Object Detection,

Reference 8

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Observation bc2976be-6c76-47b1-9b52-8816671b610b · outbound

This paper cites Online Batch Selection for Faster Train- ing of Neural Networks,.

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training Online Batch Selection for Faster Train- ing of Neural Networks,

Reference 9

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Observation c627ee1f-b24c-4b6c-9480-c65a0b6a7333 · outbound

This paper cites Not All Samples Are Created Equal: Deep Learning with Importance Sampling,.

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training Not All Samples Are Created Equal: Deep Learning with Importance Sampling,

Reference 10

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Observation 4a342d2b-3974-4d4f-a799-c736571612f4 · outbound

This paper cites Robust Time Series Forecasting with Non-Heavy-Tailed Gaussian Loss-Weighted Sampler.

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training Robust Time Series Forecasting with Non-Heavy-Tailed Gaussian Loss-Weighted Sampler

Reference 11

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Observation 61d7d239-12fe-4769-b0b0-4a42240eaea9 · outbound

This paper cites An empirical study of example forgetting during deep neural network learning,.

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training An empirical study of example forgetting during deep neural network learning,

Reference 12

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Observation 24ae0dc6-336d-4189-b354-d86122170d6c · outbound

This paper cites Beyond neural scaling laws: Beating power law scaling via data pruning,.

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training Beyond neural scaling laws: Beating power law scaling via data pruning,

Reference 13

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Observation a1667388-7035-4c18-bb0e-ec80be7f4393 · outbound

This paper cites Prioritized training on points that are learnable,.

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training Prioritized training on points that are learnable,

Reference 14

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Observation 03e26409-0670-4bd3-ba20-6d1819113de9 · outbound

This paper cites InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning.

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning

Reference 15

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Observation 41deb0ca-c918-4b8c-8cec-e9cf874ec817 · outbound

This paper cites DeepCore: A Comprehensive Library for Coreset Selection in Deep Learning.

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training DeepCore: A Comprehensive Library for Coreset Selection in Deep Learning

Reference 16

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Observation d21ac4e8-8bc7-4ddc-9db6-ab37cee2e6c8 · outbound

This paper cites Adaptive Subgradient Methods for Online Learning and Stochastic Optimization,.

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training Adaptive Subgradient Methods for Online Learning and Stochastic Optimization,

Reference 17

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Observation 1c4bd5a7-6c1f-43be-83ee-52da954a65c0 · outbound

This paper cites Lecture 6.5 — RMSProp,.

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training Lecture 6.5 — RMSProp,

Reference 18

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Observation a813d9c7-14db-488b-a04f-315283359ebc · outbound

This paper cites Adam: A Method for Stochastic Opti- mization,.

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training Adam: A Method for Stochastic Opti- mization,

Reference 19

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Observation 77ecc468-44c0-4851-9227-c9750ba300df · outbound

This paper cites A disciplined approach to neural network hyper-parameters: Part 1 -- learning rate, batch size, momentum, and weight decay.

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training A disciplined approach to neural network hyper-parameters: Part 1 -- learning rate, batch size, momentum, and weight decay

Reference 20

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Observation 332e77b7-4572-4bce-b1ec-cd798007c88f · outbound

This paper cites On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima,.

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima,

Reference 21

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Observation 1c3013ea-a4eb-4533-a387-6af03cbb2257 · outbound

This paper cites Deep Residual Learning for Image Recognition,.

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training Deep Residual Learning for Image Recognition,

Reference 22

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Pith citing papers

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