Paper Citation Record · LEDGER

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows

As of 17 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 1 inbound Pith citation observation for arXiv:2506.01119.

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

pith.paper-citation-record.v1
2506.01119 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:55:28.601657Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-22T05:41:39.396469Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-22T05:44:38.774124Z

Reference resolution

43 of 43 outbound references displayed

verified exact0
verified fuzzy29
unresolved14
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6dbce686-65b1-4798-8744-c1c3aa65eeae · outbound

This paper cites Gundavarapu, Liangzhe Yuan, Hao Zhou, Shen Yan, Jennifer J.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Gundavarapu, Liangzhe Yuan, Hao Zhou, Shen Yan, Jennifer J

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.990505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 31296b17-4e1d-4577-ad09-ca09a7c82ab2 · outbound

This paper cites The Kinetics Human Action Video Dataset.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows The Kinetics Human Action Video Dataset

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T11:55:28.393424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7d5e1b8-23fc-4be0-917f-49c2ba3768fc · outbound

This paper cites The human visual system and its role in motion perception.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows The human visual system and its role in motion perception

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.981697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5ab418a0-6bfc-4f97-990e-a8b928f6f186 · outbound

This paper cites Is Space-Time Attention All You Need for Video Understanding?.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Is Space-Time Attention All You Need for Video Understanding?

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T11:55:28.412053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46b2f413-8943-40e6-8cb2-27593dab6d00 · outbound

This paper cites Vivit: A video vision transformer.2021 IEEE/CVF International Conference on Computer Vision (ICCV), pages 6816–6826, 2021.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Vivit: A video vision transformer.2021 IEEE/CVF International Conference on Computer Vision (ICCV), pages 6816–6826, 2021

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.973074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation dfb07648-2b4f-402e-9a76-45ec7b1d00b5 · outbound

This paper cites De Gruyter, Berlin, Boston, 2016.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows De Gruyter, Berlin, Boston, 2016

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.963711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a7113b0f-7476-4a94-a79a-75a6b8fdb899 · outbound

This paper cites Action recognition for surveillance applications using optic flow and svm.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Action recognition for surveillance applications using optic flow and svm

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.955123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d4797cdf-ccde-4b0e-ba25-09f695a2a5c8 · outbound

This paper cites Conv3d-based video violence detection network using optical flow and rgb data.Sensors, 24(2):317, 2024.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Conv3d-based video violence detection network using optical flow and rgb data.Sensors, 24(2):317, 2024

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.946060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 247d453b-637f-4fcc-8dcb-6eb04aab0fad · outbound

This paper cites A multi-modal egocentric activity recognition approach towards video domain generalization.Sensors, 24(8):2491, 2024.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows A multi-modal egocentric activity recognition approach towards video domain generalization.Sensors, 24(8):2491, 2024

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.936770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 30e22078-01a4-4dd2-aa6a-52eb4cde4e96 · outbound

This paper cites Nayak, and Shrikanth S.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Nayak, and Shrikanth S

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.927244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 48e6121a-cc97-4115-b8b8-8d0048e1dc14 · outbound

This paper cites Kosloski, Siddhi Patel, Zeke A.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Kosloski, Siddhi Patel, Zeke A

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.918941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3f00602f-9e2d-4f81-8fbc-2185311414f8 · outbound

This paper cites Childplay: A new benchmark for understanding children’s gaze behaviour.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Childplay: A new benchmark for understanding children’s gaze behaviour

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.909200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation bb5d62d2-7286-4735-90b4-4d41ed1d31e2 · outbound

This paper cites Barner, and Roghayeh Leila Barmaki.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Barner, and Roghayeh Leila Barmaki

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.900092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation dcc67fb1-afe9-4b82-9f4c-4b6c84bf1209 · outbound

This paper cites Reversible vision transformers.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Reversible vision transformers

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.890570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 94e91b00-0004-4897-9bb8-5b2b282ea082 · outbound

This paper cites Multiscale vision transformers.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Multiscale vision transformers

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.881706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation fe739488-63d3-493d-9d5e-3d0e52ce9576 · outbound

This paper cites X3d: Expanding architectures for efficient video recognition.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows X3d: Expanding architectures for efficient video recognition

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.872697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 6d16135b-8ed2-40d3-8f03-1628219ff299 · outbound

This paper cites A large-scale study on unsupervised spatiotemporal representation learning.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows A large-scale study on unsupervised spatiotemporal representation learning

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.863939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 06197e95-cd25-434e-b15c-0c73abe5192e · outbound

This paper cites Spatio- temporal collaborative module for efficient action recognition.IEEE Transactions on Image Processing, 31:7279–7291, 2022.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Spatio- temporal collaborative module for efficient action recognition.IEEE Transactions on Image Processing, 31:7279–7291, 2022

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.854792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ea230c41-9731-4304-9776-7504f3072ba9 · outbound

This paper cites Quo vadis, action recognition? a new model and the kinetics dataset.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Quo vadis, action recognition? a new model and the kinetics dataset

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.845441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 469ec2df-3213-41ce-8db6-06f55bcefd40 · outbound

This paper cites Batch transformer: Look for attention in batch, 2024.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Batch transformer: Look for attention in batch, 2024

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.836220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3bd54dc5-556c-4af1-bb20-de4ee4845e82 · outbound

This paper cites Videomae: masked autoencoders are data-efficient learners for self-supervised video pre-training.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Videomae: masked autoencoders are data-efficient learners for self-supervised video pre-training

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.827404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2867165f-1f18-46b0-b603-81f640b3bc1d · outbound

This paper cites Videomae v2: Scaling video masked autoencoders with dual masking.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Videomae v2: Scaling video masked autoencoders with dual masking

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.818394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 01f74cea-7896-458c-a9d7-63a76d406320 · outbound

This paper cites Video swin transformer.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Video swin transformer

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.809366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a4733bde-7530-4e67-893c-184e944c8ecb · outbound

This paper cites Pyslowfast.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Pyslowfast

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T11:55:28.534382Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b58e5f88-f92c-4727-b35e-a2b9a5c8914b · outbound

This paper cites Jampani, Andreas Geiger, and Michael J.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Jampani, Andreas Geiger, and Michael J

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.794641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d35cb0e2-e7ea-4b65-bac0-d7ecd28ba1b0 · outbound

This paper cites Henriques.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Henriques

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.784880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f6fd2541-73a6-4144-957a-d50c8ae420b2 · outbound

This paper cites Memflow: Optical flow estimation and prediction with memory, 2024.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Memflow: Optical flow estimation and prediction with memory, 2024

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.776070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation fe05929b-d2e5-4667-8e2a-a6d2f7bc8fa8 · outbound

This paper cites Reformer: The Efficient Transformer.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Reformer: The Efficient Transformer

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T11:55:28.547233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fdd2c949-005b-4f33-9cbf-a3c67a4305b0 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T11:55:28.551969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97448051-ee0f-460c-b750-ae3501c43f0c · outbound

This paper cites Raft: Recurrent all-pairs field transforms for optical flow.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Raft: Recurrent all-pairs field transforms for optical flow

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.766560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 39b7184f-ab40-4135-bc7d-b3a461216f70 · outbound

This paper cites an unresolved cited work.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Unresolved cited work

Reference 31

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:55:28.757518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f48e9839-fec3-489c-9e26-7f1322ae2cd6 · outbound

This paper cites Vision transformers need registers, 2023.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Vision transformers need registers, 2023

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.748304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 48a7837c-a8b6-4d22-8428-c966ac4a442c · outbound

This paper cites an unresolved cited work.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Unresolved cited work

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T11:55:28.565743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f8d3a28-c38d-4d96-9cf0-917e8ebab219 · outbound

This paper cites something something.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows something something

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.733996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3ff158d3-b578-4830-8336-25fd38b8a102 · outbound

This paper cites Haa500: Human-centric atomic action dataset with curated videos.2021 IEEE/CVF International Conference on Computer Vision (ICCV), pages 13445–13454, 2020.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Haa500: Human-centric atomic action dataset with curated videos.2021 IEEE/CVF International Conference on Computer Vision (ICCV), pages 13445–13454, 2020

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.724868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a183b072-d9e6-47f7-b98a-ecb2db274ecf · outbound

This paper cites UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T11:55:28.576141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49b04534-6599-45ae-8e45-a02de3856930 · outbound

This paper cites Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T11:55:28.579305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11b6460c-27c4-44d8-a83a-db3a97378f3b · outbound

This paper cites VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T11:55:28.582939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a77fe62-b43d-4c1f-a132-461310eeec73 · outbound

This paper cites VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T11:55:28.586764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ca677bd-85df-4f23-bf31-c6e4b77df4bb · outbound

This paper cites SlowFast-LLaVA: A Strong Training-Free Baseline for Video Large Language Models.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows SlowFast-LLaVA: A Strong Training-Free Baseline for Video Large Language Models

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T11:55:28.590775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38aef75a-669e-4a59-9487-ed095bf3ccb4 · outbound

This paper cites Video-LLaVA: Learning United Visual Representation by Alignment Before Projection.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows Video-LLaVA: Learning United Visual Representation by Alignment Before Projection

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T11:55:28.593941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8d45bca-9cee-4951-a3ea-6d6c44723162 · outbound

This paper cites LanguageBind: Extending Video-Language Pretraining to N-modality by Language-based Semantic Alignment.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows LanguageBind: Extending Video-Language Pretraining to N-modality by Language-based Semantic Alignment

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T11:55:28.598004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba947274-ad79-41ca-93f7-98a7c4503750 · outbound

This paper cites running” or “jumping.

MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows running” or “jumping

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:55:28.713614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

Observation 3d7e4a8f-ac48-45cc-8d2e-b9a52f16edca · inbound

Which Way Did It Move? Diagnosing and Overcoming Directional Motion Blindness in Video-LLMs cites this paper.

Which Way Did It Move? Diagnosing and Overcoming Directional Motion Blindness in Video-LLMs MOOSE: Pay Attention to Temporal Dynamics for Video Understanding via Optical Flows

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-22T05:44:38.777481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.