Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T19:02:14.437243Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2507.06979.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T19:02:14.437243Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
52 of 52 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation bc0a47fd-9e83-4503-a627-56a875aa3e4c · outbound
A Principled Framework for Multi-View Contrastive Learning Understanding contrastive representation learning through alignment and uniformity on the hypersphere,
Reference 1
Source-reported events for the cited work
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Observation 487264dc-2627-4eea-b00a-5324f8714ad8 · outbound
A Principled Framework for Multi-View Contrastive Learning Learning representations by maximizing mutual information across views,
Reference 2
Source-reported events for the cited work
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Observation 9842ecbf-b7d2-45de-9726-9361e80212dc · outbound
A Principled Framework for Multi-View Contrastive Learning Drawing Multiple Augmentation Samples Per Image During Training Efficiently Decreases Test Error
Reference 3
Source-reported events for the cited work
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Observation 890e70a4-64f9-4d90-9142-96dd29d94eb9 · outbound
A Principled Framework for Multi-View Contrastive Learning Augment your batch: Improving generalization through instance repeti- tion,
Reference 4
Source-reported events for the cited work
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Observation d0cfaa85-f2d5-47cc-9508-9b47bb221ff1 · outbound
A Principled Framework for Multi-View Contrastive Learning The good, the bad and the ugly sides of data augmentation: An implicit spectral regularization perspective,
Reference 5
Source-reported events for the cited work
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Observation 8314b134-59e2-48b3-8b94-02529bb4749c · outbound
A Principled Framework for Multi-View Contrastive Learning Unsupervised learning of visual features by contrasting cluster assign- ments,
Reference 6
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Observation 26d5b057-395f-4fca-833c-9e9db129bb17 · outbound
A Principled Framework for Multi-View Contrastive Learning Emerging properties in self-supervised vision transformers,
Reference 7
Source-reported events for the cited work
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Observation 95174f07-9652-4ada-9fed-24be24fce467 · outbound
A Principled Framework for Multi-View Contrastive Learning Vicregl: Self-supervised learning of local visual features,
Reference 8
Source-reported events for the cited work
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Observation 290ece9f-a986-4ad1-bc66-50f91e7113e5 · outbound
A Principled Framework for Multi-View Contrastive Learning Contrastive multiview coding,
Reference 9
Source-reported events for the cited work
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Observation f390be64-6339-4609-8b4e-eb55a3f894b5 · outbound
A Principled Framework for Multi-View Contrastive Learning Poly-view contrastive learning,
Reference 10
Source-reported events for the cited work
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Observation d2db9797-93c6-46f6-899f-8516443eb28a · outbound
A Principled Framework for Multi-View Contrastive Learning Bridging mini-batch and asymptotic analysis in contrastive learning: From infoNCE to kernel-based losses,
Reference 11
Source-reported events for the cited work
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Observation 52aff91c-a2b3-4ac2-86ce-5ad1205e03db · outbound
A Principled Framework for Multi-View Contrastive Learning Understanding dimensional collapse in contrastive self-supervised learning,
Reference 12
Source-reported events for the cited work
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Observation 92901114-9b1b-4a80-aefd-a69fecfa49f8 · outbound
A Principled Framework for Multi-View Contrastive Learning Learning transferable visual models from natural language supervision,
Reference 13
Source-reported events for the cited work
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Observation fb0219a0-cdbb-47f4-bd14-d4772dcc84cd · outbound
A Principled Framework for Multi-View Contrastive Learning Tricolo: Trimodal contrastive loss for text to shape retrieval,
Reference 14
Source-reported events for the cited work
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Observation d2b67a94-c88a-43a1-b9c8-4afa5f82372a · outbound
A Principled Framework for Multi-View Contrastive Learning Contrastive multimodal fusion with tupleinfonce,
Reference 15
Source-reported events for the cited work
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Observation bfc30664-9b92-48dd-ae9e-b9a308f04a73 · outbound
A Principled Framework for Multi-View Contrastive Learning Contextual augmented global contrast for multimodal intent recognition,
Reference 16
Source-reported events for the cited work
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Observation 6b945324-f172-4099-970c-69cee2e58f5a · outbound
A Principled Framework for Multi-View Contrastive Learning Learning a similarity metric discriminatively, with application to face verification,
Reference 17
Source-reported events for the cited work
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Observation 31956479-74c2-4fee-9947-f6a8db5699b3 · outbound
A Principled Framework for Multi-View Contrastive Learning Improved deep metric learning with multi-class n-pair loss objective,
Reference 18
Source-reported events for the cited work
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Observation f0b6f4aa-0c6c-41ce-bd79-dcc960fe60ac · outbound
A Principled Framework for Multi-View Contrastive Learning Representation Learning with Contrastive Predictive Coding
Reference 19
Source-reported events for the cited work
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Observation c4b21919-cf78-4750-a354-be8f7762d403 · outbound
A Principled Framework for Multi-View Contrastive Learning A simple framework for contrastive learning of visual representations,
Reference 20
Source-reported events for the cited work
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Observation 0af9efc3-38ed-4cd5-945b-17f48c616b75 · outbound
A Principled Framework for Multi-View Contrastive Learning With a little help from my friends: Nearest-neighbor contrastive learning of visual representations,
Reference 21
Source-reported events for the cited work
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Observation 3e47573c-57e7-4d07-a5a4-2766fba508ce · outbound
A Principled Framework for Multi-View Contrastive Learning Decoupled contrastive learning,
Reference 22
Source-reported events for the cited work
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Observation c336da5a-5f63-4fb3-8fbc-1e1f4d8df3d6 · outbound
A Principled Framework for Multi-View Contrastive Learning Momentum contrast for unsupervised visual representation learning,
Reference 23
Source-reported events for the cited work
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Observation c03ea183-6810-4047-8831-09a80fa23b54 · outbound
A Principled Framework for Multi-View Contrastive Learning Contrastive learning with hard negative samples,
Reference 24
Source-reported events for the cited work
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Observation 33b3cf60-5414-448f-890b-57de8141381c · outbound
A Principled Framework for Multi-View Contrastive Learning On feature decorrelation in self-supervised learning,
Reference 25
Source-reported events for the cited work
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Observation d344dc1f-a96f-4262-b79f-7300882a38a8 · outbound
A Principled Framework for Multi-View Contrastive Learning Understanding dimensional collapse in contrastive self-supervised learning,
Reference 26
Source-reported events for the cited work
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Observation 26fe4c9c-d67b-4cf8-9686-8c929e390af6 · outbound
A Principled Framework for Multi-View Contrastive Learning How much data are augmentations worth? an investigation into scaling laws, invariance, and implicit regularization,
Reference 27
Source-reported events for the cited work
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Observation ec8b8fa0-3107-4d17-af7b-c00b1841bf1a · outbound
A Principled Framework for Multi-View Contrastive Learning Grounding inductive biases in natural images: invariance stems from variations in data,
Reference 28
Source-reported events for the cited work
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Observation d5b9cd6d-c2ed-489a-b228-0ffa612ec291 · outbound
A Principled Framework for Multi-View Contrastive Learning EMP-SSL: Towards Self-Supervised Learning in One Training Epoch
Reference 29
Source-reported events for the cited work
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Observation 1587bc72-02ab-434d-8e78-afa956907489 · outbound
A Principled Framework for Multi-View Contrastive Learning Whitening for self-supervised representation learning,
Reference 30
Source-reported events for the cited work
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Observation fee42788-4be4-497f-beed-5d763c7718f5 · outbound
A Principled Framework for Multi-View Contrastive Learning Adaptive multi-head contrastive learning,
Reference 31
Source-reported events for the cited work
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Observation 98ed067d-f483-42bf-9bba-84d7c77662db · outbound
A Principled Framework for Multi-View Contrastive Learning From global to local: Multi-patch and multi-scale contrastive similarity learning for unsupervised defocus blur detection,
Reference 32
Source-reported events for the cited work
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Observation 162f87fc-2b6a-45f2-8518-187f37b62a08 · outbound
A Principled Framework for Multi-View Contrastive Learning Multi- view action recognition using contrastive learning,
Reference 33
Source-reported events for the cited work
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Observation 6003f504-3b3a-45d3-b8ec-c94e760224af · outbound
A Principled Framework for Multi-View Contrastive Learning Multi-level feature learning for contrastive multi-view clustering,
Reference 34
Source-reported events for the cited work
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Observation ef2bf66f-5ddc-4103-8d15-5089584690af · outbound
A Principled Framework for Multi-View Contrastive Learning Contrasting multiple representations with the multi-marginal matching gap,
Reference 35
Source-reported events for the cited work
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Observation 59e92252-0379-49b5-8097-1f50483bc275 · outbound
A Principled Framework for Multi-View Contrastive Learning Bootstrap your own latent-a new approach to self-supervised learning,
Reference 36
Source-reported events for the cited work
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Observation d640d37d-e86e-49f1-85f6-fd5457cf2bb5 · outbound
A Principled Framework for Multi-View Contrastive Learning Fastsiam: Resource- efficient self-supervised learning on a single gpu,
Reference 37
Source-reported events for the cited work
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Observation 983abdf1-b0f9-43c1-a18a-a9325ceb5d9d · outbound
A Principled Framework for Multi-View Contrastive Learning Unsupervised feature learning by cross- level instance-group discrimination,
Reference 38
Source-reported events for the cited work
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Observation d84a2323-8e68-4716-bc0d-dd4e511cb823 · outbound
A Principled Framework for Multi-View Contrastive Learning Dual temperature helps contrastive learning without many negative samples: Towards understanding and simplifying moco,
Reference 39
Source-reported events for the cited work
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Observation 95e96c4a-3280-41ec-a3ff-641c08a72067 · outbound
A Principled Framework for Multi-View Contrastive Learning Unsupervised feature learning via non-parametric instance discrimination,
Reference 40
Source-reported events for the cited work
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Observation f692fc97-591d-43b0-b091-aadf34845f84 · outbound
A Principled Framework for Multi-View Contrastive Learning Multizoo & multibench: A standardized toolkit for multimodal deep learning,
Reference 41
Source-reported events for the cited work
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Observation 54366bbe-3655-488c-a447-19de8e49e231 · outbound
A Principled Framework for Multi-View Contrastive Learning M-sena: An integrated platform for multimodal sentiment analysis,
Reference 42
Source-reported events for the cited work
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Observation 56767095-2aa5-42c1-aec4-b68594fba3ba · outbound
A Principled Framework for Multi-View Contrastive Learning Multimodal language analysis in the wild: CMU-MOSEI dataset and interpretable dynamic fusion graph,
Reference 43
Source-reported events for the cited work
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Observation 3954f81b-8cb8-457e-a98e-5e598c73d026 · outbound
A Principled Framework for Multi-View Contrastive Learning Ch- sims: A chinese multimodal sentiment analysis dataset with fine-grained annotation of modality,
Reference 44
Source-reported events for the cited work
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Observation a6105407-85ed-4c4c-bb42-8cf8048a8a8e · outbound
A Principled Framework for Multi-View Contrastive Learning Geometrical and statistical properties of systems of linear inequalities with applications in pattern recognition,
Reference 45
Source-reported events for the cited work
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Observation 46b63d65-ed5d-44bf-8325-b5853d12037d · outbound
A Principled Framework for Multi-View Contrastive Learning Rankme: Assessing the downstream performance of pretrained self-supervised representations by their rank,
Reference 46
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b225beb6-03f3-48a9-9087-773fcd2543b2 · outbound
A Principled Framework for Multi-View Contrastive Learning MERBench: A Unified Evaluation Benchmark for Multimodal Emotion Recognition
Reference 47
Source-reported events for the cited work
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Observation 2ff16ee6-9d8e-4453-8a50-9c34888b4ef7 · outbound
A Principled Framework for Multi-View Contrastive Learning BERT: Pre- training of deep bidirectional transformers for language understanding,
Reference 48
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a653cb5a-1244-48c4-89fc-2d66edc99b47 · outbound
A Principled Framework for Multi-View Contrastive Learning Hubert: Self-supervised speech representation learning by masked prediction of hidden units,
Reference 49
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9d57fd5b-82c4-4d6c-b9a0-754386429ea7 · outbound
A Principled Framework for Multi-View Contrastive Learning An image is worth 16x16 words: Transformers for image recognition at scale,
Reference 50
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bdc89af6-7217-4234-9fd0-8a6573349160 · outbound
A Principled Framework for Multi-View Contrastive Learning Decoupled weight decay regularization,
Reference 51
Source-reported events for the cited work
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Observation 77562faa-ffd6-45c3-ae8e-1fe1b7b59baa · outbound
A Principled Framework for Multi-View Contrastive Learning Unresolved cited work
Reference 52
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
No inbound Pith citation observations are available.