Paper Citation Record · LEDGER

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification

As of 10 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2607.25830.

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

pith.paper-citation-record.v1
2607.25830 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T01:26:09.330379Z

measured 41 of 41 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

41 of 41 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7ba6848e-2680-4049-ba55-b8906add6c60 · outbound

This paper cites https://github.com/sdm2026/ldal.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification https://github.com/sdm2026/ldal

Reference 1

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Observation 9c49bc50-37d8-45a1-a832-eea95b8ac49e · outbound

This paper cites Deepsat: a learning framework for satellite imagery.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Deepsat: a learning framework for satellite imagery

Reference 2

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Observation 763fd183-8040-402b-bb5e-045cceb3adb2 · outbound

This paper cites Learning imbalanced datasets with label-distribution-aware margin loss, 2019.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Learning imbalanced datasets with label-distribution-aware margin loss, 2019

Reference 3

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Observation a1021246-66bc-4718-8b2b-4bb295e2c48f · outbound

This paper cites Area: Adaptive reweighting via effective area for long-tailed classification.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Area: Adaptive reweighting via effective area for long-tailed classification

Reference 4

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Observation 9f3cd2cd-611c-4df1-8dbc-d19b5b54a6ab · outbound

This paper cites Progressively growing generative adversarial networks for high resolution semantic segmentation of satellite images.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Progressively growing generative adversarial networks for high resolution semantic segmentation of satellite images

Reference 5

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Observation e14a5414-34c1-4ca9-922b-ef18b68f6c14 · outbound

This paper cites Class-balanced loss based on effective number of samples, 2019.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Class-balanced loss based on effective number of samples, 2019

Reference 6

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Observation 63b966a3-24d5-4f03-973c-edf44ec067e2 · outbound

This paper cites Class rectification hard mining for imbalanced deep learning.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Class rectification hard mining for imbalanced deep learning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:02.586803Z

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Observation 6599af4b-a95d-410b-a119-821e44d605c5 · outbound

This paper cites Borderline-smote: a new over-sampling method in imbalanced data sets learning.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Borderline-smote: a new over-sampling method in imbalanced data sets learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:02.828517Z

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Observation f63e286d-9b18-493d-9326-0db969d1c8d3 · outbound

This paper cites Learning deep representation for imbalanced classification.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Learning deep representation for imbalanced classification

Reference 9

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Observation 9121d0f2-4308-4cf8-a522-563fb77aacae · outbound

This paper cites Decoupling representation and classifier for long-tailed recognition, 2020.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Decoupling representation and classifier for long-tailed recognition, 2020

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:04.964075Z

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Observation a8724f71-6d94-4be1-aa30-da8b794d2f34 · outbound

This paper cites M2m: Imbalanced classification via major-to-minor translation.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification M2m: Imbalanced classification via major-to-minor translation

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:05.098770Z

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Observation ebe76d2d-914a-4d8f-af8d-28e812392ccf · outbound

This paper cites Re-weighted softmax cross-entropy to control forgetting in federated learning, 2023.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Re-weighted softmax cross-entropy to control forgetting in federated learning, 2023

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:05.245593Z

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Observation 112b9c1e-5619-47c8-adba-dc5b9a2474e6 · outbound

This paper cites Focal-sam: Focal sharpness-aware minimization for long-tailed classification, 2025.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Focal-sam: Focal sharpness-aware minimization for long-tailed classification, 2025

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:05.445274Z

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Observation f0bdcf59-82a9-4db0-9198-b7cd042f4d19 · outbound

This paper cites Focal loss for dense object detection.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Focal loss for dense object detection

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:05.584246Z

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Observation c46e403f-9e13-4fb5-a3e4-31fad343ecfd · outbound

This paper cites Focal loss for dense object detection, 2018.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Focal loss for dense object detection, 2018

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:05.698035Z

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Observation 3ae862e1-cf99-4ecd-9fa9-b2a8d23c1af5 · outbound

This paper cites Large-scale long-tailed recognition in an open world.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Large-scale long-tailed recognition in an open world

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:05.801181Z

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Observation 7203c9cf-fc78-4df7-9c19-4e40f8ca7bdb · outbound

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Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Unresolved cited work

Reference 17

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Observation 90d41271-3ff4-48db-b439-46f422028e59 · outbound

This paper cites Pursuing better decision boundaries for long-tailed object detection via category information amount, 2025.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Pursuing better decision boundaries for long-tailed object detection via category information amount, 2025

Reference 18

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Observation a8b5879a-5ef1-43c9-9617-abb4a66e7e5d · outbound

This paper cites Delving into semantic scale imbalance, 2023.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Delving into semantic scale imbalance, 2023

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:06.225646Z

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Observation c07f4099-aeee-4f5a-a996-d0132f285230 · outbound

This paper cites Factors in finetuning deep model for object detection with long-tail distribution.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Factors in finetuning deep model for object detection with long-tail distribution

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:06.392507Z

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Observation 66c73034-ddc7-49e6-a19b-fdaf14c68870 · outbound

This paper cites The majority can help the minority: Context-rich minority oversampling for long-tailed classification.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification The majority can help the minority: Context-rich minority oversampling for long-tailed classification

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:06.494269Z

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Observation 72df1386-bb32-4a52-954d-0ba82aab969e · outbound

This paper cites Influence- balanced loss for imbalanced visual classification, 2021.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Influence- balanced loss for imbalanced visual classification, 2021

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:06.621442Z

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Observation c342e318-36a1-43d9-91c2-fd9fcf82ae48 · outbound

This paper cites Balanced meta-softmax for long-tailed visual recognition, 2020.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Balanced meta-softmax for long-tailed visual recognition, 2020

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:06.760863Z

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Observation b7699e72-e5e1-450e-81ab-cb9f46da5700 · outbound

This paper cites Managing bias in ai.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Managing bias in ai

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:06.898020Z

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Observation efbe7ee0-5ed2-4235-9518-7b730667334c · outbound

This paper cites Lift+: Lightweight fine-tuning for long-tail learning, 2025.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Lift+: Lightweight fine-tuning for long-tail learning, 2025

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:07.022018Z

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Observation c4c5fd9a-f0bf-4850-b2a2-5c450930ea4e · outbound

This paper cites Meta-weight-net: Learning an explicit mapping for sample weighting.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Meta-weight-net: Learning an explicit mapping for sample weighting

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:07.173204Z

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Observation b1a6a79f-6028-4466-b72a-6970c71df6b1 · outbound

This paper cites Solar: Sinkhorn label refinery for imbalanced partial-label learning, 2022.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Solar: Sinkhorn label refinery for imbalanced partial-label learning, 2022

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:07.307208Z

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Observation b2318108-dc8c-465a-ae69-62b8958b91bc · outbound

This paper cites Rsg: A simple but effective module for learning imbalanced datasets, 2021.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Rsg: A simple but effective module for learning imbalanced datasets, 2021

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:07.457950Z

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Observation 19dd2606-7d7e-4d10-83eb-6168a7dd8e4a · outbound

This paper cites Long-tailed Recognition by Routing Diverse Distribution-Aware Experts.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Long-tailed Recognition by Routing Diverse Distribution-Aware Experts

Reference 30

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Observation 52e6c97b-a7f3-449f-b5b4-fea43f9b9a69 · outbound

This paper cites A survey on long- tailed visual recognition.International Journal of Computer Vision, 130(7):1837–1872, 2022.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification A survey on long- tailed visual recognition.International Journal of Computer Vision, 130(7):1837–1872, 2022

Reference 31

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Observation cb6db059-a65a-43e2-9978-9df454a36146 · outbound

This paper cites Automated situation- aware service composition in service-oriented computing.International Journal of Web Services Research (IJWSR), 4(4):59–82, 2007.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Automated situation- aware service composition in service-oriented computing.International Journal of Web Services Research (IJWSR), 4(4):59–82, 2007

Reference 32

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Observation 70b8f381-a194-4cc0-94fa-21abd6689d87 · outbound

This paper cites Adaptable situation-aware secure service-based (as/sup 3/) systems.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Adaptable situation-aware secure service-based (as/sup 3/) systems

Reference 33

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Observation a18cd161-7087-4fd6-839b-e16bf23d4d5e · outbound

This paper cites Self- supervised aggregation of diverse experts for test-agnostic long-tailed recognition.Advances in Neural Information Processing Systems, 35:34077–34090, 2022.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Self- supervised aggregation of diverse experts for test-agnostic long-tailed recognition.Advances in Neural Information Processing Systems, 35:34077–34090, 2022

Reference 34

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This paper cites Self- supervised aggregation of diverse experts for test-agnostic long-tailed recognition, 2022.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Self- supervised aggregation of diverse experts for test-agnostic long-tailed recognition, 2022

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:08.400787Z

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This paper cites Deep long-tailed learning: A survey, 2023.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Deep long-tailed learning: A survey, 2023

Reference 36

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Observation b4549ef2-cee8-4e72-873f-ff118f8a2974 · outbound

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Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Unresolved cited work

Reference 37

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Observation 72b4e0a4-7414-4293-8a6d-f9851e9dfd55 · outbound

This paper cites Learning fast sample re-weighting without reward data, 2021.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Learning fast sample re-weighting without reward data, 2021

Reference 38

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Observation 815d1c3b-bb3d-43b2-9e5e-3f471db48c4d · outbound

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Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Improving calibration for long-tailed recognition

Reference 39

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Observation caa1f280-e8f8-4fc6-8962-c7aff602913c · outbound

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Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Improving calibration for long-tailed recognition, 2021

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:08.983863Z

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Observation 17067192-26ae-453d-92a8-8593df3ac955 · outbound

This paper cites Bbn: Bilateral-branch network with cumulative learning for long-tailed visual recognition.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Bbn: Bilateral-branch network with cumulative learning for long-tailed visual recognition

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:09.188238Z

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Observation 920eedf6-0958-488e-8d8d-cac822625614 · outbound

This paper cites Inflated episodic memory with region self-attention for long-tailed visual recognition.

Beyond Static Costs: Learning-Dynamics Aware Loss Functions for Long-Tailed Classification Inflated episodic memory with region self-attention for long-tailed visual recognition

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:09.330379Z

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Pith citing papers

No inbound Pith citation observations are available.