Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T13:52:46.827059Z
Paper Citation Record · LEDGER
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets
As of 10 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2505.20694.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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
Reference resolution
35 of 35 outbound references displayed
- verified exact6
- verified fuzzy19
- unresolved10
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation e48e4885-d170-4866-9b0a-ada5516b692f · outbound
This paper cites Cisco visual networking index (vni) complete forecast update, 2017–2022.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Cisco visual networking index (vni) complete forecast update, 2017–2022
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T13:52:51.456682Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 946f7e63-2cec-4f55-8050-f34dd6c776ea · outbound
This paper cites Quo vadis, action recognition? a new model and the kinetics dataset.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Quo vadis, action recognition? a new model and the kinetics dataset
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:52:43.208253Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2a0ed2eb-b7d1-4399-a23c-b1a371ee27ab · outbound
This paper cites Dataset distillation by matching training trajectories.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Dataset distillation by matching training trajectories
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T13:52:51.301113Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 58349d06-0d00-41e2-a9bc-1163c5d43481 · outbound
This paper cites Generalizing Dataset Distillation via Deep Generative Prior.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Generalizing Dataset Distillation via Deep Generative Prior
Reference 4
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T13:52:48.020320Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation b14e8eda-edff-48ea-86ac-3f0bcca3d9ca · outbound
This paper cites Influence- guided diffusion for dataset distillation.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Influence- guided diffusion for dataset distillation
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T13:52:51.104438Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 71ed087e-c271-4d10-a4c5-f6df19de76d1 · outbound
This paper cites A Large-Scale Study on Video Action Dataset Condensation.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets A Large-Scale Study on Video Action Dataset Condensation
Reference 6
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T13:52:47.846666Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation d337a395-74bd-4f30-9170-bdb74306ce16 · outbound
This paper cites Imagenet: A large- scale hierarchical image database.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Imagenet: A large- scale hierarchical image database
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:52:43.802328Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bfeaeeac-9e53-4645-8893-ddd3e6eb15e5 · outbound
This paper cites Diversity-Driven Synthesis: Enhancing Dataset Distillation through Directed Weight Adjustment.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Diversity-Driven Synthesis: Enhancing Dataset Distillation through Directed Weight Adjustment
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T13:52:47.645575Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation afc16b80-745b-4547-a7ec-b23db5cca3c0 · outbound
This paper cites something something.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets something something
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T13:52:50.948876Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 097c0535-78a0-402a-a441-d879af9f7483 · outbound
This paper cites Efficient dataset distillation via minimax diffusion.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Efficient dataset distillation via minimax diffusion
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T13:52:50.730549Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation ad303815-2e74-4cba-a4c0-8d52e6face4f · outbound
This paper cites Hmdb: a large video database for human motion recognition.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Hmdb: a large video database for human motion recognition
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T13:52:50.560297Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 92233018-82ae-48da-a63d-1d5c4b879fa8 · outbound
This paper cites Dataset distillation with infinitely wide convolutional networks.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Dataset distillation with infinitely wide convolutional networks
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T13:52:50.397585Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 2c23062b-b74c-4be7-8990-965e395e2e2a · outbound
This paper cites Datadam: Efficient dataset distillation with attention matching.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Datadam: Efficient dataset distillation with attention matching
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T13:52:50.260462Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation c1ef747a-546c-4914-94fa-f21af56c0de7 · outbound
This paper cites Generalized large-scale data condensation via various backbone and statistical matching.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Generalized large-scale data condensation via various backbone and statistical matching
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T13:52:50.081628Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 3954ea93-d30f-4014-b684-03c2d2558b2c · outbound
This paper cites Elucidating the Design Space of Dataset Condensation.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Elucidating the Design Space of Dataset Condensation
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:52:44.712492Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b4dfdb29-1554-49df-9033-39fc4ee9220d · outbound
This paper cites Denoising diffusion implicit models.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Denoising diffusion implicit models
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:52:44.775141Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 96681e09-0f04-4bf8-846c-011f7d728bf5 · outbound
This paper cites A dataset of 101 human action classes from videos in the wild.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets A dataset of 101 human action classes from videos in the wild
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T13:52:49.883389Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation c6cfef7c-d9ce-41bb-83d0-2a61ba408022 · outbound
This paper cites Dˆ 4: Dataset distillation via disentangled diffusion model.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Dˆ 4: Dataset distillation via disentangled diffusion model
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T13:52:49.763422Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation e647f9e0-6d3f-4337-bd0a-3f2dabdcc7ab · outbound
This paper cites On the diversity and realism of distilled dataset: An efficient dataset distillation paradigm.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets On the diversity and realism of distilled dataset: An efficient dataset distillation paradigm
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:52:45.041649Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e3de8310-9ea8-43dd-aeb6-2b4c7d7b7e8e · outbound
This paper cites Learning spa- tiotemporal features with 3d convolutional networks.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Learning spa- tiotemporal features with 3d convolutional networks
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T13:52:49.554378Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 5b436c88-ff35-4afb-8027-7c00339eb1f7 · outbound
This paper cites Dataset Distillation.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Dataset Distillation
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:52:45.224048Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 03f817d1-5762-40f2-97be-5751054213d0 · outbound
This paper cites Adaptive focus for efficient video recognition.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Adaptive focus for efficient video recognition
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T13:52:49.399271Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation fa0db96d-c920-498f-9895-14e92f4d9614 · outbound
This paper cites Dancing with still images: video distillation via static-dynamic disentanglement.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Dancing with still images: video distillation via static-dynamic disentanglement
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T13:52:49.201309Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation e2536c68-3a51-47ed-a858-06fd49173733 · outbound
This paper cites Dreaming to distill: Data-free knowledge transfer via deepinversion.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Dreaming to distill: Data-free knowledge transfer via deepinversion
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T13:52:48.976218Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 497aaa94-6958-4221-9958-e7e73aff3b15 · outbound
This paper cites Dataset distillation via curriculum data synthesis in large data era.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Dataset distillation via curriculum data synthesis in large data era
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T13:52:48.802753Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 4447c7aa-3b17-4856-9e6d-cba85eb5df16 · outbound
This paper cites Squeeze, recover and relabel: Dataset condensation at imagenet scale from a new perspective.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Squeeze, recover and relabel: Dataset condensation at imagenet scale from a new perspective
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T13:52:48.564315Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation d7bd810c-ccc5-4db2-a016-3cb413eb9991 · outbound
This paper cites Cutmix: Regularization strategy to train strong classifiers with localizable features.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Cutmix: Regularization strategy to train strong classifiers with localizable features
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T13:52:48.411323Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation dd078137-15cf-4394-ac74-84aff2ba5bcd · outbound
This paper cites VideoMix: Rethinking Data Augmentation for Video Classification.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets VideoMix: Rethinking Data Augmentation for Video Classification
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:52:46.092992Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 25d5c771-9c21-4692-a54c-6f4a32927998 · outbound
This paper cites mixup: Beyond Empirical Risk Minimization.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets mixup: Beyond Empirical Risk Minimization
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:52:46.156884Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation de745e62-1783-4b0f-b3e2-c95fabfb4ff6 · outbound
This paper cites Dataset Condensation with Distribution Matching.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Dataset Condensation with Distribution Matching
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:52:46.252600Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7b948157-e3b6-4449-bc1b-a6fd72b8cb02 · outbound
This paper cites Dataset condensation with gradient matching.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Dataset condensation with gradient matching
Reference 31
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- verified fuzzy
- raw_fallback, observed 2026-08-07T13:52:48.218348Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation bf326d9a-9a10-438c-a3d8-561afef86ab4 · outbound
This paper cites Video Set Distillation: Information Diversification and Temporal Densification.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Video Set Distillation: Information Diversification and Temporal Densification
Reference 32
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T13:52:47.399911Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 46ab8f06-5a7e-4921-a2c9-ab08c19a9b09 · outbound
This paper cites Going Beyond Feature Similarity: Effective Dataset Distillation based on Class-Aware Conditional Mutual Information.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Going Beyond Feature Similarity: Effective Dataset Distillation based on Class-Aware Conditional Mutual Information
Reference 33
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T13:52:47.187163Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation acfdd477-21cf-4096-b58e-2619d8453be4 · outbound
This paper cites Hierarchical Features Matter: A Deep Exploration of Progressive Parameterization Method for Dataset Distillation.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Hierarchical Features Matter: A Deep Exploration of Progressive Parameterization Method for Dataset Distillation
Reference 34
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- unresolved
- no resolver link, observed 2026-08-07T13:52:46.756294Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 117f76b4-0e4d-4fb9-b070-65896507c81f · outbound
This paper cites Towards Consistent and Efficient Dataset Distillation via Diffusion-Driven Selection.
Temporal Saliency-Guided Distillation: A Scalable Framework for Distilling Video Datasets Towards Consistent and Efficient Dataset Distillation via Diffusion-Driven Selection
Reference 35
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T13:52:47.023775Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Pith citing papers
No inbound Pith citation observations are available.