Paper Citation Record · LEDGER

An Attention-based Framework for Fair Contrastive Learning

As of 18 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2411.14765.

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

pith.paper-citation-record.v1
2411.14765 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:01:41.380506Z

measured 41 of 41 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 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

verified exact1
verified fuzzy11
unresolved29
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External citation measurements

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Outbound references

Observation 9f32bd27-a2e7-4836-a552-39be5c64fbfb · outbound

This paper cites In particu- lar, we avoid specifying any particular kernel and allow our attention mechanism to learn the bias-causing interactions.

An Attention-based Framework for Fair Contrastive Learning In particu- lar, we avoid specifying any particular kernel and allow our attention mechanism to learn the bias-causing interactions

Reference 2

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Observation c6c68782-0fe8-44a6-a60c-d3dc075d932d · outbound

This paper cites log ef (x,ypos) ef (x,ypos) + Pb i=1 ef (x,yneg,i) # , (21) and FAREContrast is given as: sup f E{(xi,yi,zi)}b i=1∼P ⊗b XY Z.

An Attention-based Framework for Fair Contrastive Learning log ef (x,ypos) ef (x,ypos) + Pb i=1 ef (x,yneg,i) # , (21) and FAREContrast is given as: sup f E{(xi,yi,zi)}b i=1∼P ⊗b XY Z

Reference 3

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Observation d0ecc7a2-97e6-4da5-a617-504783f19e06 · outbound

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An Attention-based Framework for Fair Contrastive Learning Unresolved cited work

Reference 4

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Observation 281bbc3a-127f-4072-ba97-81cf66ce3740 · outbound

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An Attention-based Framework for Fair Contrastive Learning Unresolved cited work

Reference 6

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Observation 94c931aa-dfc3-4c92-bb6d-19fa75eae003 · outbound

This paper cites doi: 10.18653/v1/W19-4828.

An Attention-based Framework for Fair Contrastive Learning doi: 10.18653/v1/W19-4828

Reference 7

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Observation ca83523d-4787-4385-ba5f-55aee424ac10 · outbound

This paper cites Fairness metrics: A comparative analysis.

An Attention-based Framework for Fair Contrastive Learning Fairness metrics: A comparative analysis

Reference 8

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Observation fd34df9e-d7bc-40f4-8f7a-345940913d1a · outbound

This paper cites Designing and interpreting probes with control tasks.

An Attention-based Framework for Fair Contrastive Learning Designing and interpreting probes with control tasks

Reference 9

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Observation 54e01caf-3b95-467d-8db1-a45312c5ae5d · outbound

This paper cites Learning deep representations by mutual information estimation and maximization.

An Attention-based Framework for Fair Contrastive Learning Learning deep representations by mutual information estimation and maximization

Reference 10

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Observation bbe24fb0-c2ba-4d04-af8e-92768968fd91 · outbound

This paper cites Reformer: The Efficient Transformer.

An Attention-based Framework for Fair Contrastive Learning Reformer: The Efficient Transformer

Reference 11

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Observation 76a570ce-b36e-471a-97da-0680be8d2472 · outbound

This paper cites Large-scale celebfaces attributes (celeba) dataset.

An Attention-based Framework for Fair Contrastive Learning Large-scale celebfaces attributes (celeba) dataset

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:01:42.607518Z

Source-reported events for the cited work

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Observation 44e711f8-7943-4295-a96c-43f5fd0d4e3a · outbound

This paper cites Duet: A tuning-free device-cloud collaborative parameters generation frame- work for efficient device model generalization.

An Attention-based Framework for Fair Contrastive Learning Duet: A tuning-free device-cloud collaborative parameters generation frame- work for efficient device model generalization

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:01:42.576070Z

Source-reported events for the cited work

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Observation e43f135f-7676-4e8e-b83d-b3df90adf186 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

An Attention-based Framework for Fair Contrastive Learning Representation Learning with Contrastive Predictive Coding

Reference 15

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Observation a8aaca57-ed3c-4f6e-858d-abeb877e65de · outbound

This paper cites Contrastive Learning with Hard Negative Samples.

An Attention-based Framework for Fair Contrastive Learning Contrastive Learning with Hard Negative Samples

Reference 17

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Observation 1edf600b-2105-4520-b2b5-5e2c7323f50a · outbound

This paper cites Contrastive Learning for Fair Representations.

An Attention-based Framework for Fair Contrastive Learning Contrastive Learning for Fair Representations

Reference 19

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Observation afc92f09-99a5-413c-848b-9c40a94731e9 · outbound

This paper cites doi: 10.18653/v1/P19-1452.

An Attention-based Framework for Fair Contrastive Learning doi: 10.18653/v1/P19-1452

Reference 21

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Observation f3859fdc-7c88-4593-ba55-b6387b086cfd · outbound

This paper cites Transformer Dissection: A Unified Understanding of Transformer's Attention via the Lens of Kernel.

An Attention-based Framework for Fair Contrastive Learning Transformer Dissection: A Unified Understanding of Transformer's Attention via the Lens of Kernel

Reference 22

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Observation 69dbcb13-3bf0-453b-8bed-cb59c8d4b2ab · outbound

This paper cites Self-supervised Representation Learning with Relative Predictive Coding.

An Attention-based Framework for Fair Contrastive Learning Self-supervised Representation Learning with Relative Predictive Coding

Reference 23

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Observation 01a2e37d-d8fc-4ffb-83ca-6cb49b9ba576 · outbound

This paper cites doi: 10.18653/v1/W19-4808.

An Attention-based Framework for Fair Contrastive Learning doi: 10.18653/v1/W19-4808

Reference 25

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Observation ffcde1c3-7647-432d-bb49-32cb88ee25f7 · outbound

This paper cites doi: 10.18653/v1/P19-1580.

An Attention-based Framework for Fair Contrastive Learning doi: 10.18653/v1/P19-1580

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-12T15:01:41.251595Z

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Observation f7a6cbce-8fe0-4906-bcaf-98470e4b07f1 · outbound

This paper cites Transformers are Deep Infinite-Dimensional Non-Mercer Binary Kernel Machines.

An Attention-based Framework for Fair Contrastive Learning Transformers are Deep Infinite-Dimensional Non-Mercer Binary Kernel Machines

Reference 27

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Observation 11763011-f7c5-4e15-824f-010fcc2be396 · outbound

This paper cites Conditional Negative Sampling for Contrastive Learning of Visual Representations.

An Attention-based Framework for Fair Contrastive Learning Conditional Negative Sampling for Contrastive Learning of Visual Representations

Reference 28

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Observation 63bd31c5-2bcf-44bc-8138-a74f6321030a · outbound

This paper cites Large Batch Training of Convolutional Networks.

An Attention-based Framework for Fair Contrastive Learning Large Batch Training of Convolutional Networks

Reference 29

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Observation f7e92f60-9f18-49d6-b4d4-257c07418d85 · outbound

This paper cites (2020), Robinson et al.

An Attention-based Framework for Fair Contrastive Learning (2020), Robinson et al

Reference 31

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Observation 2c048c82-7461-4f6a-8c9a-50656cd99ed8 · outbound

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An Attention-based Framework for Fair Contrastive Learning Unresolved cited work

Reference 33

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Observation 205123e3-f4c2-45a8-b5fa-931eb4edb719 · outbound

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An Attention-based Framework for Fair Contrastive Learning Unresolved cited work

Reference 34

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An Attention-based Framework for Fair Contrastive Learning Unresolved cited work

Reference 35

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Observation 95f0a089-ed0b-4373-bf95-98d6324be25f · outbound

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An Attention-based Framework for Fair Contrastive Learning Unresolved cited work

Reference 36

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Observation c0f2bde3-369a-41a9-8ae6-7a2082f9001e · outbound

This paper cites Proof of kernel-based scoring function estimation.

An Attention-based Framework for Fair Contrastive Learning Proof of kernel-based scoring function estimation

Reference 38

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Observation c6d89749-caa6-4698-9b5b-cdb8a579c964 · outbound

This paper cites Fare and SparseFARE in comparison with unsupervised and supervised models under partial sensitive label access.

An Attention-based Framework for Fair Contrastive Learning Fare and SparseFARE in comparison with unsupervised and supervised models under partial sensitive label access

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:01:42.154642Z

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Observation 90f4055a-8da5-409e-91d1-449ed5c26320 · outbound

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An Attention-based Framework for Fair Contrastive Learning Unresolved cited work

Reference 41

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Observation c4f39181-6ab9-4892-86d9-559cd498e856 · outbound

This paper cites Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization.

An Attention-based Framework for Fair Contrastive Learning Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization

Reference 1956

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Observation b11f960d-5f0e-4bc1-baf0-83a454e7e75a · outbound

This paper cites Gradient reversal against discrimination: A fair neural network learning approach.

An Attention-based Framework for Fair Contrastive Learning Gradient reversal against discrimination: A fair neural network learning approach

Reference 1962

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:01:42.541381Z

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Observation 8c5eba28-3269-4c53-81e2-c75f958199b5 · outbound

This paper cites Nonlinear SVD with Asymmetric Kernels: feature learning and asymmetric Nystr\"om method.

An Attention-based Framework for Fair Contrastive Learning Nonlinear SVD with Asymmetric Kernels: feature learning and asymmetric Nystr\"om method

Reference 2013

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Observation ffdcc3d1-628a-4aa6-ab38-f770458c9a38 · outbound

This paper cites Unbiased Supervised Contrastive Learning.

An Attention-based Framework for Fair Contrastive Learning Unbiased Supervised Contrastive Learning

Reference 2015

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Observation d0e2bb20-4ff1-4a50-bab2-b1ac376b6248 · outbound

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An Attention-based Framework for Fair Contrastive Learning Unresolved cited work

Reference 2016

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Observation 4f876b86-8f6e-4c35-ac9b-981fd237d990 · outbound

This paper cites Analyzing the structure of attention in a transformer language model.

An Attention-based Framework for Fair Contrastive Learning Analyzing the structure of attention in a transformer language model

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:01:42.509566Z

Source-reported events for the cited work

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Observation 0f467cf9-0929-4782-909b-1cb845e4b663 · outbound

This paper cites The Variational Fair Autoencoder.

An Attention-based Framework for Fair Contrastive Learning The Variational Fair Autoencoder

Reference 2018

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Observation 6e6b2606-1b5f-4e13-8875-4708e027809b · outbound

This paper cites Generating Long Sequences with Sparse Transformers.

An Attention-based Framework for Fair Contrastive Learning Generating Long Sequences with Sparse Transformers

Reference 2019

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Source-reported events for the cited work

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Observation 54c90435-3397-42c2-8769-9ca5bc3073ea · outbound

This paper cites On the dangers of stochastic parrots: Can language models be too big? In Proceedings of the 2021 ACM conference on fairness, accountability, and transparency, pp.

An Attention-based Framework for Fair Contrastive Learning On the dangers of stochastic parrots: Can language models be too big? In Proceedings of the 2021 ACM conference on fairness, accountability, and transparency, pp

Reference 2020

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This paper cites FairFil: Contrastive Neural Debiasing Method for Pretrained Text Encoders.

An Attention-based Framework for Fair Contrastive Learning FairFil: Contrastive Neural Debiasing Method for Pretrained Text Encoders

Reference 2021

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Observation 096ee502-b977-483c-b18e-8ae8d928b33c · outbound

This paper cites Longformer: The Long-Document Transformer.

An Attention-based Framework for Fair Contrastive Learning Longformer: The Long-Document Transformer

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-12T15:01:40.993658Z

Source-reported events for the cited work

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Pith citing papers

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