Paper Citation Record · LEDGER

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms

As of 15 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2603.04873.

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

pith.paper-citation-record.v1
2603.04873 v3

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-15T14:58:03.612340Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

30 of 30 outbound references displayed

verified exact0
verified fuzzy0
unresolved30
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8838e852-58cf-4a4f-9655-a6a2cc2c2395 · outbound

This paper cites Pitch classification using variational bayesian gaussian mixture models on trackman data.Journal of Sports Sciences, 2020.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Pitch classification using variational bayesian gaussian mixture models on trackman data.Journal of Sports Sciences, 2020

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Unavailable: canonical work link unavailable.

Observation 9fe98b66-7db6-46f4-821a-5dc078159546 · outbound

This paper cites Clausi, and John S.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Clausi, and John S

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Observation fba36100-c3a9-4801-96ac-9d8f1b49a244 · outbound

This paper cites Distribution and Depth-Aware Transformers for 3D Human Mesh Recovery.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Distribution and Depth-Aware Transformers for 3D Human Mesh Recovery

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Observation e7dae257-9744-4410-8f25-6e676b0fae93 · outbound

This paper cites Scalable injury-risk screening in baseball pitching from broadcast video.arXiv preprint arXiv:2511.09502, 2025.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Scalable injury-risk screening in baseball pitching from broadcast video.arXiv preprint arXiv:2511.09502, 2025

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Observation 555c3b34-ccb8-455e-b214-d13db2e82dd7 · outbound

This paper cites Baseball pitch type recognition based on broadcast videos.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Baseball pitch type recognition based on broadcast videos

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Unavailable: canonical work link unavailable.

Observation 006d8991-ddbd-46fc-9805-7509dd95670c · outbound

This paper cites Xgboost: A scalable tree boosting system.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Xgboost: A scalable tree boosting system

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Observation 44ee828d-d9df-4fc9-b75e-d6400d85fbaf · outbound

This paper cites an unresolved cited work.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Unresolved cited work

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Unavailable: canonical work link unavailable.

Observation dc258798-bf5f-4063-9969-d91d9e7c3d76 · outbound

This paper cites Video-based pitch type classification us- ing openpose and st-gcn in baseball.Proceedings of the IEEE Conference on Computer Vision and Pattern Recog- nition Workshops, 2024.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Video-based pitch type classification us- ing openpose and st-gcn in baseball.Proceedings of the IEEE Conference on Computer Vision and Pattern Recog- nition Workshops, 2024

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Unavailable: canonical work link unavailable.

Observation 7c4881f7-eaa2-4c90-9896-2f51e58cc846 · outbound

This paper cites Statcast pitch classifications.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Statcast pitch classifications

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 431392d4-cf27-4419-aad7-4270d7011c3f · outbound

This paper cites Applying machine learning tech- niques to baseball pitch prediction.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Applying machine learning tech- niques to baseball pitch prediction

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Observation 97d912fa-7488-411a-b28f-09bb0b1d7a97 · outbound

This paper cites Apply- ing machine learning techniques to baseball pitch prediction.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Apply- ing machine learning techniques to baseball pitch prediction

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Observation 3360c54d-74f1-4dd6-8c7c-5b584774dbd6 · outbound

This paper cites The doubly librating Plutinos.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms The doubly librating Plutinos

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Observation b05c2091-17d8-4c4b-bd5a-72853fed8c26 · outbound

This paper cites Black, David W.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Black, David W

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Unavailable: canonical work link unavailable.

Observation 0d6d2e22-23f6-4cab-a3e5-42b1ed30947a · outbound

This paper cites Lightgbm: A highly efficient gradient boosting decision tree.Advances in neural information processing systems, 30, 2017.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Lightgbm: A highly efficient gradient boosting decision tree.Advances in neural information processing systems, 30, 2017

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Unavailable: canonical work link unavailable.

Observation 6a7136ab-5202-421b-9717-52599d3de15c · outbound

This paper cites Prediction of pitch type and location in baseball us- ing ensemble model of deep neural networks.Journal of Sports Analytics, 2022.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Prediction of pitch type and location in baseball us- ing ensemble model of deep neural networks.Journal of Sports Analytics, 2022

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Unavailable: canonical work link unavailable.

Observation 7fdac935-30f5-4900-8ae1-9c15f331dab0 · outbound

This paper cites Prediction of pitch type and location in baseball using ensemble model of deep neural networks.Journal of Sports Analytics, 8(2):115–126, 2022.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Prediction of pitch type and location in baseball using ensemble model of deep neural networks.Journal of Sports Analytics, 8(2):115–126, 2022

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Observation f1638478-6476-4109-b9e4-26f5f207f43c · outbound

This paper cites MediaPipe: A Framework for Building Perception Pipelines.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms MediaPipe: A Framework for Building Perception Pipelines

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Unavailable: canonical work link unavailable.

Observation 8d6978e6-8b77-49de-887b-acb08b3a7c71 · outbound

This paper cites Classification of fast and off-speed pitches using pelvis and trunk kinematics in youth baseball pitchers using machine learning.Journal of Science and Medicine in Sport,.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Classification of fast and off-speed pitches using pelvis and trunk kinematics in youth baseball pitchers using machine learning.Journal of Science and Medicine in Sport,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Unavailable: canonical work link unavailable.

Observation 201ce4dc-c930-4666-a670-90605b079484 · outbound

This paper cites Classification of four pitching styles in japanese baseball players.International Journal of Sports Science & Coaching, 2023.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Classification of four pitching styles in japanese baseball players.International Journal of Sports Science & Coaching, 2023

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Unavailable: canonical work link unavailable.

Observation c6ca7be2-4088-4991-9372-d665236c5738 · outbound

This paper cites Automated classi- fication of baseball pitching phases using machine learning and artificial intelligence-based posture estimation.Applied Sciences, 2025.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Automated classi- fication of baseball pitching phases using machine learning and artificial intelligence-based posture estimation.Applied Sciences, 2025

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

Source-reported events for the cited work

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Observation 9cd91cc4-056c-4fe3-a6be-c62cbb8df991 · outbound

This paper cites Au- tomated classification of baseball pitching phases using ma- chine learning and artificial intelligence-based posture esti- mation.Applied Sciences, 15(22):12155, 2025.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Au- tomated classification of baseball pitching phases using ma- chine learning and artificial intelligence-based posture esti- mation.Applied Sciences, 15(22):12155, 2025

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Unavailable: canonical work link unavailable.

Observation 037c6ccc-ea3b-454e-92b6-72d95e003dce · outbound

This paper cites Trouble With The Curve: Improving MLB Pitch Classification.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Trouble With The Curve: Improving MLB Pitch Classification

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Unavailable: canonical work link unavailable.

Observation 224b786b-60fb-4340-9aae-f152801cb672 · outbound

This paper cites Classifying pitch types in baseball us- ing machine learning algorithms.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Classifying pitch types in baseball us- ing machine learning algorithms

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Unavailable: canonical work link unavailable.

Observation fb035fa2-23a4-4a06-9283-0ead0fec92e3 · outbound

This paper cites Calculating Kolmogorov Complexity from the Transcriptome Data.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Calculating Kolmogorov Complexity from the Transcriptome Data

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Unavailable: canonical work link unavailable.

Observation 1a70eece-e964-44f5-8c44-2361aff06a4f · outbound

This paper cites Using multi-class classification methods to predict baseball pitch types.Journal of Sports Analytics,.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Using multi-class classification methods to predict baseball pitch types.Journal of Sports Analytics,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Observation 15e658ee-8255-480f-9949-9f60fa3f4cf9 · outbound

This paper cites Hawk eye: A logi- cal innovative technology use in sports for effective decision making.Sport Science Review, 21, 2012.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Hawk eye: A logi- cal innovative technology use in sports for effective decision making.Sport Science Review, 21, 2012

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Observation 15c65fdb-273a-4c38-927c-835053e0f2f0 · outbound

This paper cites Automatic pitch type recognition from baseball broadcast videos.2008 Tenth IEEE International Symposium on Multimedia, 2008.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Automatic pitch type recognition from baseball broadcast videos.2008 Tenth IEEE International Symposium on Multimedia, 2008

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Observation 46ef8a16-ea3e-419e-b80b-fedd1ffefbe6 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Gemini: A Family of Highly Capable Multimodal Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Observation 3dc029c6-728c-44ce-b835-fab0a4e1580d · outbound

This paper cites Utilization of pattern recognition techniques to classify baseball pitches.Research in Sports Medicine, 24(4):348–357, 2016.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Utilization of pattern recognition techniques to classify baseball pitches.Research in Sports Medicine, 24(4):348–357, 2016

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Observation c69ea435-67ab-4838-9678-0ee09051e136 · outbound

This paper cites Vit- pose++: Vision transformer for generic body pose estima- tion.IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(2):1212–1230, 2023.

SEA-TS: Self-Evolving Agent for Autonomous Code Generation of Time Series Forecasting Algorithms Vit- pose++: Vision transformer for generic body pose estima- tion.IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(2):1212–1230, 2023

Reference 31

Resolution: unresolved; no resolver link, observed 2026-07-15T14:58:03.612340Z

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Pith citing papers

No inbound Pith citation observations are available.