Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T15:07:14.606324Z
Paper Citation Record · LEDGER
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos
As of 11 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 1 inbound Pith citation observation for arXiv:2505.16376.
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 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-10T02:26:05.178943Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T13:01:26.009993Z
Reference resolution
68 of 68 outbound references displayed
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation ae2df7a1-c806-4363-b43c-c3d6edc5e93e · outbound
This paper cites Localizing Moments in Long Video Via Multimodal Guidance.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Localizing Moments in Long Video Via Multimodal Guidance
Reference 1
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 734dfabf-869d-4785-8a88-7186e4675012 · outbound
This paper cites Is space-time attention all you need for video understanding? InProceedings of the International Conference on Machine Learning (ICML), 2021.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Is space-time attention all you need for video understanding? InProceedings of the International Conference on Machine Learning (ICML), 2021
Reference 2
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 2fb26669-de05-4fa2-a41b-0e1898e086b9 · outbound
This paper cites Accelerating Large Language Model Decoding with Speculative Sampling.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Accelerating Large Language Model Decoding with Speculative Sampling
Reference 3
- Resolution
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Source-reported events for the cited work
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Observation 97a08dd2-881e-4c0b-a204-55fd37ec7454 · outbound
This paper cites A simple framework for contrastive learning of visual representations.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos A simple framework for contrastive learning of visual representations
Reference 4
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 729772a3-d593-44f0-b1eb-e8703159cb37 · outbound
This paper cites Tallformer: Temporal ac- tion localization with a long-memory transformer.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Tallformer: Temporal ac- tion localization with a long-memory transformer
Reference 5
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 6e4644c9-f27d-41eb-83d1-b7efe8beadfa · outbound
This paper cites Every Mistake Counts in Assembly.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Every Mistake Counts in Assembly
Reference 6
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3e662609-413c-48e1-97e7-fee21cb5d846 · outbound
This paper cites Coherent temporal synthesis for incremental action segmentation.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Coherent temporal synthesis for incremental action segmentation
Reference 7
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 7f474fa6-7985-4052-8d49-b6e0396ffde6 · outbound
This paper cites Donahue and E.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Donahue and E
Reference 8
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 7b8d77e5-45df-4c3b-8aae-0ae122dc73c7 · outbound
This paper cites Ms-tcn: Multi-stage tem- poral convolutional network for action segmentation.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Ms-tcn: Multi-stage tem- poral convolutional network for action segmentation
Reference 9
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation b97e68ab-2ed1-4978-a5cc-10d8a6ea3580 · outbound
This paper cites Tall: Temporal activity localization via language query,.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Tall: Temporal activity localization via language query,
Reference 10
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f94cacda-4bcf-45c7-8a20-a012775413d8 · outbound
This paper cites Mac: Mining activity concepts for language-based temporal local- ization, 2018.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Mac: Mining activity concepts for language-based temporal local- ization, 2018
Reference 11
- Resolution
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Source-reported events for the cited work
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Observation d5aecad4-17cf-4c81-8aeb-8ca81a215fa6 · outbound
This paper cites Diverse sequential subset selection for supervised video summarization.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Diverse sequential subset selection for supervised video summarization
Reference 12
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 674c5d0b-aa36-44bc-a1ae-8d076652aedd · outbound
This paper cites Ego4d: Around the world in 3,000 hours of egocentric video.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Ego4d: Around the world in 3,000 hours of egocentric video
Reference 13
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 35623d07-1852-497f-8d1f-6f03ac8bc815 · outbound
This paper cites Rehg, and Hans Peter Graf.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Rehg, and Hans Peter Graf
Reference 14
- Resolution
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Source-reported events for the cited work
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Observation 05dd9555-a5cb-45f1-9380-0ec1d8da37ad · outbound
This paper cites Rgnet: A unified clip retrieval and grounding network for long videos.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Rgnet: A unified clip retrieval and grounding network for long videos
Reference 15
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation f0b1e26a-9730-4bac-9deb-5b593f9ead1a · outbound
This paper cites Localizing mo- ments in video with natural language, 2017.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Localizing mo- ments in video with natural language, 2017
Reference 16
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 1b3328a9-c504-44c5-8cc7-94a8affa16d1 · outbound
This paper cites CONE: An Efficient COarse-to-fiNE Alignment Framework for Long Video Temporal Grounding.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos CONE: An Efficient COarse-to-fiNE Alignment Framework for Long Video Temporal Grounding
Reference 17
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 93c1e88c-29d8-4135-8d71-93a153436513 · outbound
This paper cites Content-based recommendation engine for video streaming platform.arXiv preprint arXiv:2308.08406, 2023.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Content-based recommendation engine for video streaming platform.arXiv preprint arXiv:2308.08406, 2023
Reference 18
- Resolution
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Source-reported events for the cited work
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Observation 7192606e-4a1f-4d4d-aa8f-4374e79b8f9c · outbound
This paper cites Lost in Time: Temporal Analytics for Long-Term Video Surveillance.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Lost in Time: Temporal Analytics for Long-Term Video Surveillance
Reference 19
- Resolution
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Source-reported events for the cited work
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Observation 6ce8c360-bb44-4bc6-b7c1-d62dabc69609 · outbound
This paper cites an unresolved cited work.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Unresolved cited work
Reference 20
- Resolution
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Source-reported events for the cited work
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Observation d856cbe9-1cfb-4abc-b461-7f1652ef7f4c · outbound
This paper cites Detecting mo- ments and highlights in videos via natural language queries.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Detecting mo- ments and highlights in videos via natural language queries
Reference 21
- Resolution
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Source-reported events for the cited work
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Observation a1dcf9d3-6030-41f0-8ddc-1aaeb0fcc28e · outbound
This paper cites Progressive video summarization via multimodal self- supervised learning.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Progressive video summarization via multimodal self- supervised learning
Reference 22
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation e0209547-615e-492e-8d60-e60a7e237f92 · outbound
This paper cites Vigt: proposal-free video grounding with a learnable token in the transformer.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Vigt: proposal-free video grounding with a learnable token in the transformer
Reference 23
- Resolution
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Source-reported events for the cited work
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Observation 6f209de9-cbef-42f5-929f-97f2fe58167b · outbound
This paper cites Egocentric Video-Language Pretraining.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Egocentric Video-Language Pretraining
Reference 24
- Resolution
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Source-reported events for the cited work
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Observation f4f91998-4e2a-4544-86c1-69355657d70f · outbound
This paper cites Univtg: Towards unified video- language temporal grounding.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Univtg: Towards unified video- language temporal grounding
Reference 25
- Resolution
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Source-reported events for the cited work
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Observation 18223565-3af8-4d9f-bda9-2307409591d6 · outbound
This paper cites Solving masked jigsaw puzzles with diffusion vision transformers.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Solving masked jigsaw puzzles with diffusion vision transformers
Reference 26
- Resolution
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Observation 0a97bb5e-49a9-459a-a26d-8d0ed5367c25 · outbound
This paper cites Lu and E.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Lu and E
Reference 27
- Resolution
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Source-reported events for the cited work
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Observation 73c12e15-0789-4216-9cdc-37d35c818bdb · outbound
This paper cites Lu and E.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Lu and E
Reference 28
- Resolution
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Observation 12df5a69-1a8b-41c1-9e7d-17a919f0ed52 · outbound
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DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Lu and E
Reference 29
- Resolution
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Source-reported events for the cited work
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Observation 7aa635ad-2067-4c45-97bf-d0f4c6f5fd3b · outbound
This paper cites Self-supervised multi-object tracking with path consistency.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Self-supervised multi-object tracking with path consistency
Reference 30
- Resolution
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Source-reported events for the cited work
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Observation f4f58543-8c9b-4e7a-99ab-86770587d2e9 · outbound
This paper cites Snag: Scalable and accurate video grounding.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Snag: Scalable and accurate video grounding
Reference 31
- Resolution
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Source-reported events for the cited work
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Observation 65040187-f3a8-4328-b01b-fa54e4bcfa09 · outbound
This paper cites A Content-Driven Micro-Video Recommendation Dataset at Scale.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos A Content-Driven Micro-Video Recommendation Dataset at Scale
Reference 32
- Resolution
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Source-reported events for the cited work
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Observation 2ed9acad-3552-4782-86f8-daa8f8ed2f07 · outbound
This paper cites Scanning only once: An end-to-end framework for fast temporal grounding in long videos.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Scanning only once: An end-to-end framework for fast temporal grounding in long videos
Reference 33
- Resolution
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Source-reported events for the cited work
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Observation 80d047d1-24ed-4fbb-ae91-0228c9368a94 · outbound
This paper cites Category-specific video summarization.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Category-specific video summarization
Reference 34
- Resolution
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Source-reported events for the cited work
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Observation 0e4725ca-c5a2-42ee-926c-82a4f43cff61 · outbound
This paper cites Ramakrishnan, Ziad Al-Halah, and Kristen Grauman.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Ramakrishnan, Ziad Al-Halah, and Kristen Grauman
Reference 35
- Resolution
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Source-reported events for the cited work
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Observation 5f4a9b6c-6c12-468a-8bba-777f6d16c05e · outbound
This paper cites Ground- ing action descriptions in videos.Transactions of the Asso- ciation for Computational Linguistics, 1:25–36, 2013.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Ground- ing action descriptions in videos.Transactions of the Asso- ciation for Computational Linguistics, 1:25–36, 2013
Reference 36
- Resolution
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Source-reported events for the cited work
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Observation 10c82358-3c0e-4a08-b48d-97dc43009052 · outbound
This paper cites Ground- ing action descriptions in videos.Transactions of the Asso- ciation for Computational Linguistics, 2013.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Ground- ing action descriptions in videos.Transactions of the Asso- ciation for Computational Linguistics, 2013
Reference 37
- Resolution
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Source-reported events for the cited work
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Observation 893d8742-df23-435d-8e87-b450ad34db36 · outbound
This paper cites Hat: History-augmented anchor transformer for on- line temporal action localization.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Hat: History-augmented anchor transformer for on- line temporal action localization
Reference 38
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation e8d5ded5-5525-4e78-820d-3a4a3e432de4 · outbound
This paper cites Shen and E.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Shen and E
Reference 39
- Resolution
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Source-reported events for the cited work
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Observation 6cbb5ee6-ff88-422a-af6b-5945ab43b42b · outbound
This paper cites InHollywood in Homes: Crowdsourcing Data Collection for Activity Understanding,.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos InHollywood in Homes: Crowdsourcing Data Collection for Activity Understanding,
Reference 40
- Resolution
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Source-reported events for the cited work
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Observation d5fbc5da-bab8-4139-9844-5c383b082d40 · outbound
This paper cites Sigurdsson, G ¨ul Varol, X.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Sigurdsson, G ¨ul Varol, X
Reference 41
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 237a60ed-e9ff-4250-b006-2b01d5b73066 · outbound
This paper cites Mad: A scalable dataset for language grounding in videos from movie audio descriptions.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Mad: A scalable dataset for language grounding in videos from movie audio descriptions
Reference 42
- Resolution
- verified fuzzy
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Source-reported events for the cited work
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Observation bb10ed4c-3ee4-468e-9e95-4c92540a1cf2 · outbound
This paper cites Multimodal sparse transformer network for audio-visual speech recognition.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Multimodal sparse transformer network for audio-visual speech recognition
Reference 43
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 7f085ade-1ed3-46bd-b6b6-01e68637e3d6 · outbound
This paper cites Ego4d goal-step: To- ward hierarchical understanding of procedural activities.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Ego4d goal-step: To- ward hierarchical understanding of procedural activities
Reference 44
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 39b975e9-f9bc-4d2d-9670-4e37eda2f6bb · outbound
This paper cites Two-stage active learning for efficient temporal action segmentation.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Two-stage active learning for efficient temporal action segmentation
Reference 45
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 9af6307d-f0be-49f8-82c1-7a03a0371ef2 · outbound
This paper cites Structured multi-level interaction network for video moment localization via language query.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Structured multi-level interaction network for video moment localization via language query
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:07:18.365519Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 686d4f19-9817-4f86-a74d-324e4eabae3d · outbound
This paper cites Tempo- rally grounding language queries in videos by contextual boundary-aware prediction, 2019.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Tempo- rally grounding language queries in videos by contextual boundary-aware prediction, 2019
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:07:18.257699Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 81de695d-3da6-4bb5-9847-19c1206b44ee · outbound
This paper cites Language- driven temporal activity localization: A semantic matching reinforcement learning model.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Language- driven temporal activity localization: A semantic matching reinforcement learning model
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:07:17.963263Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation e9ec5d3b-880d-4758-b719-f6cbaf8a96e1 · outbound
This paper cites Proposal relation network for temporal ac- tion detection, 2021.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Proposal relation network for temporal ac- tion detection, 2021
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:07:17.474785Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation d81ad141-bf29-436b-bf85-92275907fadc · outbound
This paper cites Video- groundingdino: Towards open-vocabulary spatio-temporal video grounding, 2024.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Video- groundingdino: Towards open-vocabulary spatio-temporal video grounding, 2024
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:07:17.284477Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation ba9b674a-1c4c-499b-bce2-0dcb3499a4a0 · outbound
This paper cites Explore-and-match: Bridging proposal-based and proposal-free with transformer for sentence grounding in videos, 2022.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Explore-and-match: Bridging proposal-based and proposal-free with transformer for sentence grounding in videos, 2022
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:07:17.165516Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 11986a67-715d-476f-a440-7fa7ada86f8d · outbound
This paper cites Multi-modal circulant fusion for video-to-language and backward.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Multi-modal circulant fusion for video-to-language and backward
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:07:17.065827Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 6e128eb1-2fab-488b-b1ca-211c9bb273b4 · outbound
This paper cites Long-term feature banks for detailed video understanding, 2019.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Long-term feature banks for detailed video understanding, 2019
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:07:16.960157Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation f3c65e69-0fd5-471b-ba6b-f6a908547ad5 · outbound
This paper cites Efficient and effec- tive weakly-supervised action segmentation via action- transition-aware boundary alignment.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Efficient and effec- tive weakly-supervised action segmentation via action- transition-aware boundary alignment
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:07:16.697607Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 0119c123-2cc9-4b07-9e39-b8a7bbab84c3 · outbound
This paper cites Long-Term Identity-Aware Multi-Person Tracking for Surveillance Video Summarization.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Long-Term Identity-Aware Multi-Person Tracking for Surveillance Video Summarization
Reference 55
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T15:07:14.792053Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 8f2976d6-99d4-4df9-b5dd-fef45ba6e2f7 · outbound
This paper cites Dense regression network for video grounding, 2020.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Dense regression network for video grounding, 2020
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:07:16.628692Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 1d7392de-c06f-4158-9df8-52124c9f9e73 · outbound
This paper cites Actionformer: Localizing moments of actions with transformers.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Actionformer: Localizing moments of actions with transformers
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:07:16.510486Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 171d98dd-c7fd-4384-96b3-282bf3bc9fda · outbound
This paper cites Helping hands: An object-aware ego-centric video recogni- tion model.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Helping hands: An object-aware ego-centric video recogni- tion model
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:07:16.341490Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 1f2ab522-d356-44f2-9857-32b249d58841 · outbound
This paper cites Span-based Localizing Network for Natural Language Video Localization.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Span-based Localizing Network for Natural Language Video Localization
Reference 59
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:07:13.924824Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 57cea86e-65e5-4927-8dd8-dd787b05cf85 · outbound
This paper cites Multi-stage aggregated transformer network for temporal language localization in videos.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Multi-stage aggregated transformer network for temporal language localization in videos
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:07:16.241881Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 5a6dd1a7-85af-4112-9c28-8cd967ff9b6e · outbound
This paper cites Learning 2d temporal adjacent networks for moment local- ization with natural language.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Learning 2d temporal adjacent networks for moment local- ization with natural language
Reference 61
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:07:14.093990Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 65b03869-a344-41b4-8491-922c7fa9cad5 · outbound
This paper cites OnlineTAS: An online baseline for temporal action segmentation.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos OnlineTAS: An online baseline for temporal action segmentation
Reference 62
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:07:16.166523Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation f4150bea-bea4-4233-85db-bf828553f88f · outbound
This paper cites Enriching local and global contexts for temporal action localization, 2021.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Enriching local and global contexts for temporal action localization, 2021
Reference 63
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:07:16.074840Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 880c5aee-b2ef-4c2e-bedb-6dd68f762e29 · outbound
This paper cites DeCaf-Grounder consists of the following key components: query-aware temporal aggregation, multi- scale temporal refinement, and classifier & regressor.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos DeCaf-Grounder consists of the following key components: query-aware temporal aggregation, multi- scale temporal refinement, and classifier & regressor
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:07:15.996412Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 73913b8d-8d78-4e82-81a2-4d1ca8d3213c · outbound
This paper cites In Table 12 of this supplementary material, we also show the computation on Ego4D-Goalstep dataset.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos In Table 12 of this supplementary material, we also show the computation on Ego4D-Goalstep dataset
Reference 65
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:07:15.919095Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 6ab0e166-285f-4d74-96f2-2f7acefcd28a · outbound
This paper cites Their settings are consis- Figure 4.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Their settings are consis- Figure 4
Reference 66
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:07:15.815842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 3ceb6c10-5ae9-43ba-85e3-9525209cd799 · outbound
This paper cites For tem- poral convolution [29] in multi-scale temporal refinement, we use 8 layers, where the dilation rate of thei-th convolu- tion layer equals to2 i.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos For tem- poral convolution [29] in multi-scale temporal refinement, we use 8 layers, where the dilation rate of thei-th convolu- tion layer equals to2 i
Reference 67
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:07:15.668468Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 378c83d9-9d18-4883-ae17-49e3ebe721f3 · outbound
This paper cites Where was object X before I used it?.
DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos Where was object X before I used it?
Reference 68
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:07:15.525564Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Pith citing papers
Observation 6ebee684-85bc-42a8-9bdc-221a2b388906 · inbound
GraphRAG-IRL: Personalized Recommendation with Graph-Grounded Inverse Reinforcement Learning and LLM Re-ranking cites this paper.
GraphRAG-IRL: Personalized Recommendation with Graph-Grounded Inverse Reinforcement Learning and LLM Re-ranking DeCafNet: Delegate and Conquer for Efficient Temporal Grounding in Long Videos
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:01:26.019356Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.