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Paper Citation Record · LEDGER

Similarity search generalisation in contrastive learning with InfoNCE loss

As of 7 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2607.09405.

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

pith.paper-citation-record.v1
2607.09405 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-13T03:15:48.800246Z

measured 25 of 25 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

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

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Source: cited_works

Reference resolution

25 of 25 outbound references displayed

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Outbound references

Observation 7f9dcaf7-0100-4f5b-a8bc-c416e5554a85 · outbound

This paper cites Spectrally-normalized margin bounds for neural networks.

Similarity search generalisation in contrastive learning with InfoNCE loss Spectrally-normalized margin bounds for neural networks

Reference 1

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source=arxiv_source observed=2026-07-13T03:15:48.800246Z digest=sha256:adcdb256ba4a199a334dae509101bd9b149619b5601f6d720361afb9d6664ebb

Observation 08a5a9c6-4e29-4e88-b92d-cbfcf50d40bd · outbound

This paper cites A simple framework for contrastive learning of visual representations.

Similarity search generalisation in contrastive learning with InfoNCE loss A simple framework for contrastive learning of visual representations

Reference 2

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source=arxiv_source observed=2026-07-13T03:15:48.800246Z digest=sha256:6c90aaa7bf907fdf3aa932260a6e29bf60bc99bf0d0bde2c366dddbb9342af90

Observation baebb9f3-f25d-42fe-a5aa-b868131961e0 · outbound

This paper cites Generalization bounds with logarithmic negative-sample dependence for adversarial contrastive learning.

Similarity search generalisation in contrastive learning with InfoNCE loss Generalization bounds with logarithmic negative-sample dependence for adversarial contrastive learning

Reference 3

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source=arxiv_source observed=2026-07-13T03:15:48.800246Z digest=sha256:a9cc3813d527e2a670bc82f48f21de6af9da7d5bd3e5c64eb72b2577ba7bf896

Observation 34d1f346-3e3f-4581-bbb6-a79025c59421 · outbound

This paper cites Size-independent sample complexity of neural networks.

Similarity search generalisation in contrastive learning with InfoNCE loss Size-independent sample complexity of neural networks

Reference 4

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source=arxiv_source observed=2026-07-13T03:15:48.800246Z digest=sha256:c5d225d93b7155073257d5abe8c9b65bf79375affad3f83092ca35669a24f283

Observation f6807394-9590-42d9-8747-e89f111649c6 · outbound

This paper cites A rescaling-invariant lipschitz bound based on path-metrics for modern relu network parameterizations.

Similarity search generalisation in contrastive learning with InfoNCE loss A rescaling-invariant lipschitz bound based on path-metrics for modern relu network parameterizations

Reference 5

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Observation ca501fa9-1cb9-4fc4-961c-be6b5804e1c1 · outbound

This paper cites Momentum contrast for unsupervised visual representation learning.

Similarity search generalisation in contrastive learning with InfoNCE loss Momentum contrast for unsupervised visual representation learning

Reference 6

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Observation 30f7c4ac-a3b1-45b1-94a3-0240613e7f2b · outbound

This paper cites Data-efficient image recognition with contrastive predictive coding.

Similarity search generalisation in contrastive learning with InfoNCE loss Data-efficient image recognition with contrastive predictive coding

Reference 7

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Observation 6f064df0-20c4-4747-8e8e-643ee9ae6d17 · outbound

This paper cites Generalization analysis for supervised contrastive representation learning under non-iid settings.

Similarity search generalisation in contrastive learning with InfoNCE loss Generalization analysis for supervised contrastive representation learning under non-iid settings

Reference 8

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source=arxiv_source observed=2026-07-13T03:15:48.800246Z digest=sha256:5e4508b47a9745df76fb01126c90ec20dd286881c21bd680ade10a3125601492

Observation 101609fb-e712-4e8f-ad60-c3b720520ed9 · outbound

This paper cites Supervised contrastive learning.

Similarity search generalisation in contrastive learning with InfoNCE loss Supervised contrastive learning

Reference 9

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Observation e1853d89-f913-4323-b89a-6c4fce5bf52c · outbound

This paper cites Data-dependent generalization bounds for multi-class classification.

Similarity search generalisation in contrastive learning with InfoNCE loss Data-dependent generalization bounds for multi-class classification

Reference 10

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source=arxiv_source observed=2026-07-13T03:15:48.800246Z digest=sha256:7daee3dc234546ec8fe53863c888467457be1974e7c94ed229b8639d39cdcf46

Observation 0c2529cd-e2b9-4ede-88d7-98e3048ae22d · outbound

This paper cites Generalization analysis for contrastive representation learning.

Similarity search generalisation in contrastive learning with InfoNCE loss Generalization analysis for contrastive representation learning

Reference 11

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Observation 10805c23-5ea9-410a-ab97-706700902335 · outbound

This paper cites A vector-contraction inequality for rademacher complexities.

Similarity search generalisation in contrastive learning with InfoNCE loss A vector-contraction inequality for rademacher complexities

Reference 12

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source=arxiv_source observed=2026-07-13T03:15:48.800246Z digest=sha256:80fe8b1c5fe640d05bfa94147d4f0cfb922e0aa887e7bc7c14337b2978c4aed7

Observation 4d98f86f-6f21-4587-888a-ff6d15186bca · outbound

This paper cites Foundations of Machine Learning.

Similarity search generalisation in contrastive learning with InfoNCE loss Foundations of Machine Learning

Reference 13

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source=arxiv_source observed=2026-07-13T03:15:48.800246Z digest=sha256:36ef6b7f5fce1bb8338ccce6a8c43d9a3da7e9e73e26e10d7263cd434c896688

Observation 1bd4d9ba-e001-43b2-a305-5650440233c3 · outbound

This paper cites Norm-based capacity control in neural networks.

Similarity search generalisation in contrastive learning with InfoNCE loss Norm-based capacity control in neural networks

Reference 14

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source=arxiv_source observed=2026-07-13T03:15:48.800246Z digest=sha256:d70380674954fc0cfc8e38c6787050731ffb7828d150b493f652030feb345a66

Observation 514eba9a-08bf-451d-b214-ccaa267318ef · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

Similarity search generalisation in contrastive learning with InfoNCE loss Learning Transferable Visual Models From Natural Language Supervision

Reference 15

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source=arxiv_source observed=2026-07-13T03:15:48.800246Z digest=sha256:f9d919d207dd655e4814da6fb091283a5a91670e663ef4aeae1b577cb8c5e774

Observation 5eb53e52-8b2c-41ec-b487-d1900dc61c21 · outbound

This paper cites A theoretical analysis of contrastive unsupervised representation learning.

Similarity search generalisation in contrastive learning with InfoNCE loss A theoretical analysis of contrastive unsupervised representation learning

Reference 16

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source=arxiv_source observed=2026-07-13T03:15:48.800246Z digest=sha256:283af70ea5e6c8908983db1ecc7afc8d105af2f57441b51d7a90a8b9cbc5df1d

Observation 9333f937-2133-41b3-9f4c-e813817b2002 · outbound

This paper cites Contrastive multiview coding.

Similarity search generalisation in contrastive learning with InfoNCE loss Contrastive multiview coding

Reference 17

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source=arxiv_source observed=2026-07-13T03:15:48.800246Z digest=sha256:ff74d3051c8526213bad24f00382b34e1a00e1fc138e7c2be71661f92c62602c

Observation 3787c0e6-1c61-413f-808c-b77cfffcf586 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Similarity search generalisation in contrastive learning with InfoNCE loss Representation Learning with Contrastive Predictive Coding

Reference 18

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source=arxiv_source observed=2026-07-13T03:15:48.800246Z digest=sha256:0c49a78d03c3abf84023ae6a6d4494d85bf70aa25b61665ea0f9f2a66d09a3d1

Observation 151f408d-8a49-4537-95fa-ef92ce810a4b · outbound

This paper cites High-dimensional statistics: A non-asymptotic viewpoint, volume 48.

Similarity search generalisation in contrastive learning with InfoNCE loss High-dimensional statistics: A non-asymptotic viewpoint, volume 48

Reference 19

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source=arxiv_source observed=2026-07-13T03:15:48.800246Z digest=sha256:61e74cf4c7c3930b99c568ff4b17a7f72b9f5ebc74fb0ad03df3aaff11b4cf86

Observation bce8601d-43e5-46cb-977a-a999fa5f32b5 · outbound

This paper cites Understanding contrastive representation learning through alignment and uniformity on the hypersphere.

Similarity search generalisation in contrastive learning with InfoNCE loss Understanding contrastive representation learning through alignment and uniformity on the hypersphere

Reference 20

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source=arxiv_source observed=2026-07-13T03:15:48.800246Z digest=sha256:ef6c20590c75b5471f4964e057d483baf15ac51ec129e20d1a5941f1f024239f

Observation ce2d0208-fe70-4965-a93d-623f65edf165 · outbound

This paper cites Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere.

Similarity search generalisation in contrastive learning with InfoNCE loss Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere

Reference 21

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Observation 09635cb9-d737-4fbc-b7f9-c989f3af52fb · outbound

This paper cites Unsupervised feature learning via non-parametric instance discrimination.

Similarity search generalisation in contrastive learning with InfoNCE loss Unsupervised feature learning via non-parametric instance discrimination

Reference 22

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source=arxiv_source observed=2026-07-13T03:15:48.800246Z digest=sha256:d6aba961a487b816cafa5f7e7ad0b6cc3c1d5b9c7e9ed3aa64f61073bb06a60d

Observation ce2bb7b1-c0e5-41ad-8a3d-9cdb5cdb654b · outbound

This paper cites Tuning large neural networks via zero-shot hyperparameter transfer.

Similarity search generalisation in contrastive learning with InfoNCE loss Tuning large neural networks via zero-shot hyperparameter transfer

Reference 23

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source=arxiv_source observed=2026-07-13T03:15:48.800246Z digest=sha256:9612a5cd17d64b9e809e26eaa4fe8a23c4bd3afbacb094ffed0d656522aa9316

Observation 203b5d78-18a7-41ac-9170-ea08cd35a7f7 · outbound

This paper cites Decoupled contrastive learning.

Similarity search generalisation in contrastive learning with InfoNCE loss Decoupled contrastive learning

Reference 24

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source=arxiv_source observed=2026-07-13T03:15:48.800246Z digest=sha256:115913ffbb92350b05246471f71f228adcb9a402e3c04dceed2b0ebd1cc155eb

Observation 6150db59-94bb-4903-b967-13935d3647e6 · outbound

This paper cites Zimmermann, Yash Sharma, Steffen Schneider, Matthias Bethge, and Wieland Brendel.

Similarity search generalisation in contrastive learning with InfoNCE loss Zimmermann, Yash Sharma, Steffen Schneider, Matthias Bethge, and Wieland Brendel

Reference 25

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