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Paper Citation Record · LEDGER

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports

As of 8 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 0 inbound Pith citation observations for arXiv:2506.03335.

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

pith.paper-citation-record.v1
2506.03335 v1

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:10:34.375083Z

measured 56 of 56 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

56 of 56 outbound references displayed

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  • verified fuzzy38
  • unresolved17
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5f2e0dde-e963-4f19-8bbc-2fcf5bf1e67d · outbound

This paper cites BoT- SORT: Robust Associations Multi-Pedestrian Tracking,.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports BoT- SORT: Robust Associations Multi-Pedestrian Tracking,

Reference 1

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Observation 0f66bb95-5289-4eef-a497-a6348027839d · outbound

This paper cites Evaluating mul- tiple object tracking performance: the clear mot metrics.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Evaluating mul- tiple object tracking performance: the clear mot metrics

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 13f14c1d-b9a1-497f-9fad-dfe1dfe004a1 · outbound

This paper cites Simple online and realtime tracking.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Simple online and realtime tracking

Reference 3

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Observation ea9813fa-50db-4d91-829c-baabd003592c · outbound

This paper cites Mitigating mo- tion blur for robust 3d baseball player pose modeling for pitch analysis.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Mitigating mo- tion blur for robust 3d baseball player pose modeling for pitch analysis

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 927ccb68-c012-4bcf-a866-fb381114378e · outbound

This paper cites Observation-centric sort: Rethink- ing sort for robust multi-object tracking.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Observation-centric sort: Rethink- ing sort for robust multi-object tracking

Reference 5

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Observation cf5b396a-5e85-4e31-b7c5-8a8cf2a33771 · outbound

This paper cites End-to- end object detection with transformers.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports End-to- end object detection with transformers

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 9058b240-8e4f-4668-95bd-fffa5e3022ba · outbound

This paper cites Mixformer: End-to-end tracking with iterative mixed atten- tion.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Mixformer: End-to-end tracking with iterative mixed atten- tion

Reference 7

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source=pdf_text observed=2026-08-07T11:10:30.502527Z digest=sha256:719cf09661b30a213174a404add174cef3ae164e620874b6c2065e6bb86cc3eb

Observation 037b3140-e947-41d5-8c21-05d60459336c · outbound

This paper cites Sportsmot: A large multi- object tracking dataset in multiple sports scenes.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Sportsmot: A large multi- object tracking dataset in multiple sports scenes

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 76c2dbb3-aa57-4d4a-974d-71731b9b3853 · outbound

This paper cites Non linear filtering: Interacting particle solution.Markov Processes and Related Fields, 2:555–580,.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Non linear filtering: Interacting particle solution.Markov Processes and Related Fields, 2:555–580,

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation fa174c46-263b-4e59-be4c-70cc78d550c7 · outbound

This paper cites Giaotracker: A compre- hensive framework for mcmot with global information and optimizing strategies in visdrone 2021.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Giaotracker: A compre- hensive framework for mcmot with global information and optimizing strategies in visdrone 2021

Reference 10

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation bf8166c5-b444-4d20-a398-2d701fbccc40 · outbound

This paper cites Strongsort: Make deep- sort great again.IEEE Transactions on Multimedia, 25: 8725–8737, 2023.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Strongsort: Make deep- sort great again.IEEE Transactions on Multimedia, 25: 8725–8737, 2023

Reference 11

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 797100d6-8ada-4b23-a335-eae12b9a747c · outbound

This paper cites Qdtrack: Quasi-dense similarity learning for appearance-only multi- ple object tracking.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Qdtrack: Quasi-dense similarity learning for appearance-only multi- ple object tracking.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023

Reference 12

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Observation efd92873-297f-4ea3-8358-078af442a3d0 · outbound

This paper cites Memotr: Long-term memory-augmented transformer for multi-object tracking.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Memotr: Long-term memory-augmented transformer for multi-object tracking

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 91538843-17a0-4bc1-8da2-7e03b1987216 · outbound

This paper cites YOLOX: Exceeding YOLO Series in 2021.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports YOLOX: Exceeding YOLO Series in 2021

Reference 14

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Observation 917c6cd8-91fe-49b3-aff8-02360c2a684c · outbound

This paper cites Are we ready for autonomous driving? the kitti vision benchmark suite.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Are we ready for autonomous driving? the kitti vision benchmark suite

Reference 15

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation f4c5cd5d-420c-42d9-8705-38d5e129a0f8 · outbound

This paper cites Soccernet: A scalable dataset for action spotting in soccer videos.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Soccernet: A scalable dataset for action spotting in soccer videos

Reference 16

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Observation 0668191e-31a8-43f2-9f1d-423611cf840b · outbound

This paper cites Fast r-cnn.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Fast r-cnn

Reference 17

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Observation 9f25c5fb-e58d-4c13-97a5-6eba4b0cc11d · outbound

This paper cites Deep HM-SORT: Enhancing Multi-Object Tracking in Sports with Deep Features, Harmonic Mean, and Expansion IOU.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Deep HM-SORT: Enhancing Multi-Object Tracking in Sports with Deep Features, Harmonic Mean, and Expansion IOU

Reference 18

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Observation 91027808-f8c3-4f0e-9fb6-ca18d1db77ca · outbound

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

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 19

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Observation 2978b813-91f5-4100-acc2-53c14ef57109 · outbound

This paper cites FastReID: A Pytorch Toolbox for General Instance Re-identification.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports FastReID: A Pytorch Toolbox for General Instance Re-identification

Reference 20

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Observation 29abedb8-85c7-4299-9bcf-c97102918bc6 · outbound

This paper cites TrackSSM: A General Motion Predictor by State-Space Model.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports TrackSSM: A General Motion Predictor by State-Space Model

Reference 21

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Observation 17be39f4-4345-45f1-89af-0c84bdb99abf · outbound

This paper cites MambaMOT: State-Space Model as Motion Predictor for Multi-Object Tracking.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports MambaMOT: State-Space Model as Motion Predictor for Multi-Object Tracking

Reference 22

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Observation eaf712f5-3888-4af7-8c11-4a09354afa06 · outbound

This paper cites Exploring Learning- based Motion Models in Multi-Object Tracking, 2024.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Exploring Learning- based Motion Models in Multi-Object Tracking, 2024

Reference 23

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Observation 74cf0e72-766f-40a1-ba2a-30c375c2dc9d · outbound

This paper cites Iterative scale-up expansioniou and deep features association for multi-object tracking in sports.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Iterative scale-up expansioniou and deep features association for multi-object tracking in sports

Reference 24

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Observation 213eed62-de9f-408e-bbea-60cbf955421a · outbound

This paper cites an unresolved cited work.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Unresolved cited work

Reference 25

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Observation f66bb484-19a2-46dc-a00f-45fb896a4d38 · outbound

This paper cites an unresolved cited work.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Unresolved cited work

Reference 26

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Observation 67cde88f-f129-413e-9fb5-67a8044f3fe7 · outbound

This paper cites Hota: A higher order metric for evaluating multi-object tracking.International journal of computer vision, 129:548– 578, 2021.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Hota: A higher order metric for evaluating multi-object tracking.International journal of computer vision, 129:548– 578, 2021

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 7170d98e-f0d7-4e06-a6db-5bd314aeb930 · outbound

This paper cites Diffusiontrack: Diffusion model for multi-object tracking.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Diffusiontrack: Diffusion model for multi-object tracking

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation ade1e11f-22a5-4a6e-8054-00c2bcb4de38 · outbound

This paper cites Diffmot: A real-time diffusion-based multiple object tracker with non-linear prediction.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Diffmot: A real-time diffusion-based multiple object tracker with non-linear prediction

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 16846368-8340-4c8a-80b2-d943e28e8dcf · outbound

This paper cites Deep oc-sort: Multi-pedestrian tracking by adaptive re-identification.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Deep oc-sort: Multi-pedestrian tracking by adaptive re-identification

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation dec717e2-fb91-4e51-8aa0-bada7e766c3e · outbound

This paper cites Trackformer: Multi-object track- ing with transformers.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Trackformer: Multi-object track- ing with transformers

Reference 31

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Observation f82fac57-4560-4f7a-9e9c-a2133e4d31fd · outbound

This paper cites Vip-htd: A public benchmark for multi-player tracking in ice hockey.Journal of Computa- tional Vision and Imaging Systems, 9(1):22–25, 2023.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Vip-htd: A public benchmark for multi-player tracking in ice hockey.Journal of Computa- tional Vision and Imaging Systems, 9(1):22–25, 2023

Reference 32

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation d51f9f63-f914-48aa-8d37-ab7ff62ff446 · outbound

This paper cites Faster R-CNN: Towards real-time object detection with re- gion proposal networks.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Faster R-CNN: Towards real-time object detection with re- gion proposal networks

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:10:32.849387Z digest=sha256:2dad9de7a3194e3c5e5768bd9b2adf2dde604bdba64044d5fa8d1191fb79d6a7

Observation 00de1249-194b-4644-a763-df6950ee9f65 · outbound

This paper cites Performance measures and a data set for multi-target, multi-camera tracking.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Performance measures and a data set for multi-target, multi-camera tracking

Reference 34

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raw_fallback, observed 2026-08-07T11:10:34.676909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:10:32.942193Z digest=sha256:9c4cd7d4fec0a6b2f98b0dd58f390c7edfe084d31ad46baf2d01aeede946a7ec

Observation e202a235-449e-4ce2-8546-f0d558453513 · outbound

This paper cites Probabilistic track- let scoring and inpainting for multiple object tracking.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Probabilistic track- let scoring and inpainting for multiple object tracking

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:34.666817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:10:33.009747Z digest=sha256:ae6720f47cab2361f7b50abe86efd524cecbfc19b18f36182ac88d66eb6020a2

Observation e6a6b97c-de71-49e1-8cd7-3befca156900 · outbound

This paper cites TransTrack: Multiple Object Tracking with Transformer,.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports TransTrack: Multiple Object Tracking with Transformer,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:34.656814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:10:33.084698Z digest=sha256:069e1207e8a9f14c703a28a1589bbdaa64fbffcf70904d376291970173e20e32

Observation b8c82e1e-36e0-4c3c-9971-572d9e7a142b · outbound

This paper cites Dancetrack: Multi-object track- ing in uniform appearance and diverse motion.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Dancetrack: Multi-object track- ing in uniform appearance and diverse motion

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:34.646074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:10:33.168719Z digest=sha256:0a550d280f75c2e01897f5c4d2d093d72099a774c1e6350c1a0d80698b1ee41b

Observation 734ef1b7-6743-47d6-9e11-dd1a886e1896 · outbound

This paper cites Attention is all you need.Advances in Neural Information Processing Systems, 2017.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Attention is all you need.Advances in Neural Information Processing Systems, 2017

Reference 38

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unresolved
no resolver link, observed 2026-08-07T11:10:33.257688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:10:33.257688Z digest=sha256:e0a5a78f11a78609cd4faadf9cebf18d50f29a6d75cc01d7b55cf1c55ede5181

Observation b92dec16-9874-4d8f-81d8-eed297884943 · outbound

This paper cites Clausi, and John S.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Clausi, and John S

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:34.628290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:10:33.342983Z digest=sha256:a407c15d7f3ab27e90eba64cb218c2faa72bdf281347d4df7f8ff7a4e709dd79

Observation b08db01f-512f-426c-96dc-47e57ebe1a76 · outbound

This paper cites Player tracking and identification in ice hockey.Expert systems with applications, 213:119250,.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Player tracking and identification in ice hockey.Expert systems with applications, 213:119250,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:34.617987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:10:33.380295Z digest=sha256:10792c17b063682e3547b1ef41a1a7ffa33b428590a787abd47e653a1397b131

Observation 112820a6-1af5-4b86-abbb-b46d0facda22 · outbound

This paper cites RNNs are not Transformers (Yet): The Key Bottleneck on In-context Retrieval.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports RNNs are not Transformers (Yet): The Key Bottleneck on In-context Retrieval

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T11:10:33.477637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:10:33.477637Z digest=sha256:363154e9956ff737d6078e91ff66904637103740e51f224a56126f299b37388d

Observation 3dc073d5-0884-46c4-ba27-8aee0bf33053 · outbound

This paper cites Simple online and realtime tracking with a deep association metric.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Simple online and realtime tracking with a deep association metric

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:34.607997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:10:33.610314Z digest=sha256:0fc1207f456ec21ccdf30d7b05b94ae17843a860b92e9eab40c19b26ea8ef312

Observation fc8032e5-0ccf-40da-87df-dca5c8ad79b5 · outbound

This paper cites Mambatrack: a simple baseline for multiple object tracking with state space model.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Mambatrack: a simple baseline for multiple object tracking with state space model

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T11:10:33.939440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:10:33.939440Z digest=sha256:f9043e5efb5f5d2de1f15104b572f3b5d809b4751f7ebb6176d89fdfea481965

Observation fda50ce8-74b3-4dad-8baf-dfd1d4a24249 · outbound

This paper cites Motiontrack: Learning motion predictor for multiple object tracking.Neu- ral Networks, 179:106539, 2024.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Motiontrack: Learning motion predictor for multiple object tracking.Neu- ral Networks, 179:106539, 2024

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:34.591611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:10:34.052915Z digest=sha256:f4552e8a37ae5414a3f5b3363428addeaf3c2f9c6ed62d68127b2c49eb0a25e9

Observation 258f3087-8608-49e2-aa7a-eba7e65ce4ec · outbound

This paper cites Robust Tracking via Mamba-based Context-aware Token Learning.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Robust Tracking via Mamba-based Context-aware Token Learning

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T11:10:34.189849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:10:34.189849Z digest=sha256:39fd4beeb12ff3e45259e327a8f3bb36f3c572a4cf4d85c63605f5bbbce8b9c7

Observation 2ba405c7-866b-435f-be02-093db32ba665 · outbound

This paper cites Hard to track objects with irregular motions and sim- ilar appearances? make it easier by buffering the matching space.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Hard to track objects with irregular motions and sim- ilar appearances? make it easier by buffering the matching space

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:34.581725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:10:34.257065Z digest=sha256:06443f11c100ad67d94a75deb08da1000751cd8f109455252a695d53ad4852ac

Observation 194d5a59-1366-4382-9012-0e00f05e7c52 · outbound

This paper cites MOTRv3: Release-fetch supervi- sion for end-to-end multi-object tracking, 2024.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports MOTRv3: Release-fetch supervi- sion for end-to-end multi-object tracking, 2024

Reference 48

Resolution
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raw_fallback, observed 2026-08-07T11:10:34.571792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:10:34.338557Z digest=sha256:55e714c1f86de4f112d589108cf1c9ce55f13fe0fd03f8c0c3838e44dd488cae

Observation 862f5f7c-b66d-41bf-bb9d-7d99351926d5 · outbound

This paper cites Bdd100k: A diverse driving dataset for heterogeneous multitask learning.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Bdd100k: A diverse driving dataset for heterogeneous multitask learning

Reference 49

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unresolved
no resolver link, observed 2026-08-07T11:10:34.342648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:10:34.342648Z digest=sha256:1b413e3b88a7cc0cd008af30826760cc1ece2b179d706e183557383528a0ae69

Observation ee51022c-3709-492b-9941-0a8c85394d32 · outbound

This paper cites Motr: End-to-end multiple- object tracking with transformer.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Motr: End-to-end multiple- object tracking with transformer

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:34.555448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:10:34.357168Z digest=sha256:9b5826d91513a816cd0577b98244ad766b186600c64d88731a767de01b8c738f

Observation 1bccf13b-ad09-4326-a5a2-dcc85b218ec8 · outbound

This paper cites Fairmot: On the fairness of detection and re-identification in multiple object tracking.International journal of computer vision, 129:3069–3087, 2021.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Fairmot: On the fairness of detection and re-identification in multiple object tracking.International journal of computer vision, 129:3069–3087, 2021

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:34.543575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:10:34.360342Z digest=sha256:348ce64c8051a40c836baabdb9663a5934f916b98713e25562d90c12f116bc41

Observation 3118bba7-a6e5-4ffd-b4a7-7b8e5d4660e2 · outbound

This paper cites Bytetrack: Multi-object tracking by associating every detection box.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Bytetrack: Multi-object tracking by associating every detection box

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:34.532897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:10:34.363185Z digest=sha256:2230a559de86e4d4b04e552ef5a0be0994cb85c10e8ab1b378c88f62f971db44

Observation 47c93818-5c73-4268-b3c3-3ee87baf558a · outbound

This paper cites Learning generalisable omni-scale representations for person re-identification.TPAMI, 2021.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Learning generalisable omni-scale representations for person re-identification.TPAMI, 2021

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:34.523515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:10:34.366310Z digest=sha256:b17664859ebeaa191c50e046a4ef2a997b1b0a3a45c57e24ad156a19dede6b9e

Observation 8a72f94a-d790-48bc-8195-7d77fc4192d0 · outbound

This paper cites Objects as Points.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Objects as Points

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-07T11:10:34.369309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:10:34.369309Z digest=sha256:429522e1068bdd27cfe3dc734bf8934b4299bb0b68dfcebc0f2ba5d6faa54118

Observation 222e1634-331c-4ce2-bef8-d1b71e97d92c · outbound

This paper cites Tracking objects as points.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Tracking objects as points

Reference 55

Resolution
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raw_fallback, observed 2026-08-07T11:10:34.513509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:10:34.372229Z digest=sha256:e6cab8a87207e2351738e3dee4d55eac4a85e208d5128268118bd9c529eb0ee9

Observation ceb2fbcb-e59a-4153-b554-9138e66ef532 · outbound

This paper cites Global tracking transformers.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports Global tracking transformers

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:34.504352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:10:34.375083Z digest=sha256:ed1c4062741309794646a1d54e40d75c473eeb8fa59bb02e9a2586ebc1993db2

Observation 4ab942ae-f5fb-49bc-9ea4-9e517eb921c6 · outbound

This paper cites BoT-SORT: Robust Associations Multi-Pedestrian Tracking.

SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports BoT-SORT: Robust Associations Multi-Pedestrian Tracking

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-07T11:10:29.685314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:10:29.685314Z digest=sha256:8550c59ece6819077602ce36ab0f6d31c7515adb08c21796327a1f18df4558dc

Pith citing papers

No inbound Pith citation observations are available.