Paper Citation Record · LEDGER

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction

As of 18 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 1 inbound Pith citation observation for arXiv:2501.16753.

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

pith.paper-citation-record.v1
2501.16753 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T11:00:44.057737Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:18:56.547557Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T22:18:57.314358Z

Reference resolution

34 of 34 outbound references displayed

verified exact0
verified fuzzy26
unresolved7
parse uncertain1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7c8cb39d-cc3d-4353-9c7b-5531f3584465 · outbound

This paper cites Vivit: A video vision transformer.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Vivit: A video vision transformer

Reference 1

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Source-reported events for the cited work

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Observation d9432036-8a94-4b45-aebd-3d59484d4afb · outbound

This paper cites The problem of learning long-term dependencies in recurrent net- works.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction The problem of learning long-term dependencies in recurrent net- works

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.850013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5cbfcd8c-1024-4622-8326-8dd2db28d6ed · outbound

This paper cites Mau: A motion- aware unit for video prediction and beyond.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Mau: A motion- aware unit for video prediction and beyond

Reference 3

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Observation 6e789d69-a2ff-4c76-b4a0-e5945fea68ea · outbound

This paper cites Two deterministic half-quadratic regular- ization algorithms for computed imaging.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Two deterministic half-quadratic regular- ization algorithms for computed imaging

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.815989Z

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Observation e8b29043-774d-4513-a480-1f17d832c552 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 5

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Observation 7a826fde-6fef-4185-b180-1eb9dd480358 · outbound

This paper cites Anticipative video transformer.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Anticipative video transformer

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.792971Z

Source-reported events for the cited work

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Observation 91f251bd-da48-419b-b6af-92f48cbf38fe · outbound

This paper cites Human action recognition and predic- tion: A survey.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Human action recognition and predic- tion: A survey

Reference 7

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Observation fadb459a-d090-488f-bf70-4e5839b83da9 · outbound

This paper cites Self-attention convlstm for spatiotemporal prediction.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Self-attention convlstm for spatiotemporal prediction

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.758053Z

Source-reported events for the cited work

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Observation 0cdd509f-83ef-4f56-b577-56b90f289185 · outbound

This paper cites Decoupled Weight Decay Regularization.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Decoupled Weight Decay Regularization

Reference 9

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Observation 7469969a-c29a-4107-83d5-9abb095623e1 · outbound

This paper cites Future frame prediction using convolutional vrnn for anomaly detection.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Future frame prediction using convolutional vrnn for anomaly detection

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.739666Z

Source-reported events for the cited work

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Observation 23416522-4fbd-4eed-9062-08a519ea5109 · outbound

This paper cites Anomaly detection in crowded scenes.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Anomaly detection in crowded scenes

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.715588Z

Source-reported events for the cited work

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Observation cdad764b-de1b-4124-a5e3-dc2e2cd1e519 · outbound

This paper cites A hybrid transformer-lstm model with 3d separable convolution for video prediction.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction A hybrid transformer-lstm model with 3d separable convolution for video prediction

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.695700Z

Source-reported events for the cited work

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Observation 9872831a-fdfd-43be-affe-e7e7a135de25 · outbound

This paper cites Deep multi-scale video prediction beyond mean square error.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Deep multi-scale video prediction beyond mean square error

Reference 13

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Observation ab9cd15f-5bcd-40d2-a6b7-f921176b97fb · outbound

This paper cites Unflow: Un- supervised learning of optical flow with a bidirectional cen- sus loss.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Unflow: Un- supervised learning of optical flow with a bidirectional cen- sus loss

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.677032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d215e10c-ecdb-4611-bd2d-8180ebaaec77 · outbound

This paper cites Conditional image-to-video gener- ation with latent flow diffusion models.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Conditional image-to-video gener- ation with latent flow diffusion models

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.650439Z

Source-reported events for the cited work

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Observation 44c5114e-a36b-4c70-b69b-799824f00b0f · outbound

This paper cites Mimo is all you need: A strong multi-in-multi-out base- line for video prediction.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Mimo is all you need: A strong multi-in-multi-out base- line for video prediction

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.628550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e37083df-688e-4608-9f80-89771acd2dff · outbound

This paper cites Recog- nizing human actions: a local svm approach.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Recog- nizing human actions: a local svm approach

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.605171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1d24637e-ca10-4901-a752-9c0404cc01e0 · outbound

This paper cites Convolutional lstm network: A machine learning approach for precipitation nowcasting.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Convolutional lstm network: A machine learning approach for precipitation nowcasting

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.560910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 17f09259-cc1e-4456-93d7-e72d166840b2 · outbound

This paper cites Deep learning for precipitation nowcasting: A benchmark and a new model.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Deep learning for precipitation nowcasting: A benchmark and a new model

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.542957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b5f7726a-9b47-49b0-8241-9ba48eaac9e0 · outbound

This paper cites Action recognition in realistic sports videos.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Action recognition in realistic sports videos

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.521276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 798f0b1c-fbc6-40de-91fe-0eb3a067b070 · outbound

This paper cites Attention is all you need.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Attention is all you need

Reference 21

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Source-reported events for the cited work

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Observation 04fe17aa-b451-435b-844f-5baa1e435934 · outbound

This paper cites Predrnn: Recurrent neural networks for predictive learning using spatiotemporal lstms.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Predrnn: Recurrent neural networks for predictive learning using spatiotemporal lstms

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.478919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2ff18651-306f-4d52-8f53-74324415bfa3 · outbound

This paper cites Predrnn++: Towards a resolution of the deep-in-time dilemma in spatiotemporal predictive learn- ing.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Predrnn++: Towards a resolution of the deep-in-time dilemma in spatiotemporal predictive learn- ing

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.454010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 43806011-54cf-40e2-a0f2-1947c8d40a3d · outbound

This paper cites Eidetic 3d lstm: A model for video prediction and beyond.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Eidetic 3d lstm: A model for video prediction and beyond

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.434300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c5ed0d94-e05d-4265-984c-0d96359c6da5 · outbound

This paper cites Memory in memory: A predictive neural network for learning higher-order non- stationarity from spatiotemporal dynamics.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Memory in memory: A predictive neural network for learning higher-order non- stationarity from spatiotemporal dynamics

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.410969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3feae6c7-3cad-4971-80b7-fc3db30f69a5 · outbound

This paper cites Motionrnn: A flexible model for video predic- tion with spacetime-varying motions.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Motionrnn: A flexible model for video predic- tion with spacetime-varying motions

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.385912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 92e5f341-d97f-439d-be6f-40f92f0949c0 · outbound

This paper cites Mo- tionnet: Joint perception and motion prediction for au- tonomous driving based on bird’s eye view maps.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Mo- tionnet: Joint perception and motion prediction for au- tonomous driving based on bird’s eye view maps

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.353236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 69e3ed10-248f-46a5-8b79-55f2ac7c2e3d · outbound

This paper cites Vptr: Efficient transformers for video prediction.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Vptr: Efficient transformers for video prediction

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.330062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation dfdb9c5a-590b-4e6e-b3de-9d7cc930e3f6 · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction The unreasonable effectiveness of deep features as a perceptual metric

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.277133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 361883b8-ac7f-4d10-bb4a-e08116fd2dee · outbound

This paper cites From actemes to action: A strongly-supervised representa- tion for detailed action understanding.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction From actemes to action: A strongly-supervised representa- tion for detailed action understanding

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.251465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 433a0420-11d2-4ee7-aeaf-4a8ee7df0c73 · outbound

This paper cites Extdm: Distribution extrapolation dif- fusion model for video prediction.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Extdm: Distribution extrapolation dif- fusion model for video prediction

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.229542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation dd515da5-fc37-47e4-8109-bc11dab557dc · outbound

This paper cites Video frame prediction from a single image and events.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction Video frame prediction from a single image and events

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.208901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 903df590-80a5-4a5c-a998-0dffafbd1624 · outbound

This paper cites IEEE, 2004.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction IEEE, 2004

Reference 2004

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T11:00:44.582829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c7615b99-958b-4d9c-8cd2-07ce453ce5b1 · outbound

This paper cites 1, 2, 3, 4.

Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction 1, 2, 3, 4

Reference 3499

Resolution: parse uncertain; raw_fallback, observed 2026-08-10T11:00:44.304403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

Observation 81243e9a-94d1-476a-ac69-8518f2ebcf3b · inbound

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion cites this paper.

SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion Overcoming Semantic Dilution in Transformer-Based Next Frame Prediction

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-08-15T22:18:57.321095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.