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Paper Citation Record · LEDGER

PySeizure: A single machine learning classifier framework to detect seizures in diverse datasets

As of 9 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2508.07253.

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

pith.paper-citation-record.v1
2508.07253 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:18:05.150726Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

14 of 14 outbound references displayed

  • verified exact0
  • verified fuzzy1
  • unresolved11
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d7e59e26-d885-4a83-9c37-ab0c44ded2ff · outbound

This paper cites SpatialCoT: Advancing Spatial Reasoning through Coordinate Alignment and Chain-of-Thought for Embodied Task Planning.

PySeizure: A single machine learning classifier framework to detect seizures in diverse datasets SpatialCoT: Advancing Spatial Reasoning through Coordinate Alignment and Chain-of-Thought for Embodied Task Planning

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-05T22:18:05.094176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:18:05.094176Z digest=sha256:1f91be250a991716f4306bed8869e705bdf428b64104c6e59aed92d805a3482d

Observation f8e02fa0-d921-44dd-96d1-12f8decbea66 · outbound

This paper cites GPT4Scene: Understand 3D Scenes from Videos with Vision-Language Models.

PySeizure: A single machine learning classifier framework to detect seizures in diverse datasets GPT4Scene: Understand 3D Scenes from Videos with Vision-Language Models

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-05T22:18:05.099810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:18:05.099810Z digest=sha256:ea83d7cb7b486f31d3d94dad57d21104049acd865a2b2bc206c95ee582979908

Observation d3b4e8a4-a4c6-4b98-8e2b-cb2f7c4893ae · outbound

This paper cites Learning 4D Panoptic Scene Graph Generation from Rich 2D Visual Scene.

PySeizure: A single machine learning classifier framework to detect seizures in diverse datasets Learning 4D Panoptic Scene Graph Generation from Rich 2D Visual Scene

Reference 8

Resolution
metadata mismatch
local_arxiv, observed 2026-08-05T22:18:06.181096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:18:05.117084Z digest=sha256:588d6896a79599fffa3983ecdcaefcd1ddd40b8661471fac095360dd8329e697

Observation 8e4e8dc4-e183-471f-a647-449bd00eab2b · outbound

This paper cites 3UR-LLM: An End-to-End Multimodal Large Language Model for 3D Scene Understanding.

PySeizure: A single machine learning classifier framework to detect seizures in diverse datasets 3UR-LLM: An End-to-End Multimodal Large Language Model for 3D Scene Understanding

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-05T22:18:05.122134Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:18:05.122134Z digest=sha256:7d5987313601817ef47995586351a9fa841dc52bc2d3ecba58fab4dbb42dd809

Observation 8b1c1768-91f3-429a-9132-e6c9abd2b6a2 · outbound

This paper cites ADL4D: Towards A Contextually Rich Dataset for 4D Activities of Daily Living.

PySeizure: A single machine learning classifier framework to detect seizures in diverse datasets ADL4D: Towards A Contextually Rich Dataset for 4D Activities of Daily Living

Reference 10

Resolution
metadata mismatch
local_arxiv, observed 2026-08-05T22:18:06.139876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:18:05.127166Z digest=sha256:b3f8e668cedf77f6f03c2fb45c90d28974b09a9a25fd17b825e1d6600f3b1576

Observation d0451e2c-52f2-4350-9651-cc636640bb4d · outbound

This paper cites FutureSightDrive: Thinking Visually with Spatio-Temporal CoT for Autonomous Driving.

PySeizure: A single machine learning classifier framework to detect seizures in diverse datasets FutureSightDrive: Thinking Visually with Spatio-Temporal CoT for Autonomous Driving

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-05T22:18:05.133521Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:18:05.133521Z digest=sha256:ceeac392c0bb77b2559105126cd2780b4238794f69785fa35b96b90373679e26

Observation 202736fe-1137-428f-b620-72e7ada45cc9 · outbound

This paper cites Zheng, D.; Huang, S.; and Wang, L.

PySeizure: A single machine learning classifier framework to detect seizures in diverse datasets Zheng, D.; Huang, S.; and Wang, L

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-05T22:18:05.140235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:18:05.140235Z digest=sha256:3856fe7fbcaf81127f184190f15bc1366c7421f4023beb56ef5151968319b82a

Observation 1e9284c9-fd54-4ae4-b25a-7a28cb9dc245 · outbound

This paper cites LLaVA-4D: Embedding SpatioTemporal Prompt into LMMs for 4D Scene Understanding.

PySeizure: A single machine learning classifier framework to detect seizures in diverse datasets LLaVA-4D: Embedding SpatioTemporal Prompt into LMMs for 4D Scene Understanding

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-05T22:18:05.145079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:18:05.145079Z digest=sha256:275967671a0cb288b914bbe560a64b44d1cd6c656f2659336c2e5665dd64ce80

Observation 3cb81618-21a3-405b-8dac-28d034d2a138 · outbound

This paper cites LLaVA-3D: A Simple yet Effective Pathway to Empowering LMMs with 3D-awareness.

PySeizure: A single machine learning classifier framework to detect seizures in diverse datasets LLaVA-3D: A Simple yet Effective Pathway to Empowering LMMs with 3D-awareness

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-05T22:18:05.150726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:18:05.150726Z digest=sha256:a127ff4062413f8e50d948d3a158e4c61531bba0bb4a23817e24406c8df06118

Observation 313ec8e8-8d3e-4937-ac5e-43ebfb4f3b8e · outbound

This paper cites InCom- puter Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XX.

PySeizure: A single machine learning classifier framework to detect seizures in diverse datasets InCom- puter Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XX

Reference 2020

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:18:06.296999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:18:05.082323Z digest=sha256:c89af8f087c5ec459c1b411dbdc074991f35e70606007fff92e8a3edcb7e9bb2

Observation cc66a7c2-3f92-4e32-80ae-875a5e3b0a56 · outbound

This paper cites Johnson-Lindenstrauss Lemma, Linear and Nonlinear Random Projections, Random Fourier Features, and Random Kitchen Sinks: Tutorial and Survey.

PySeizure: A single machine learning classifier framework to detect seizures in diverse datasets Johnson-Lindenstrauss Lemma, Linear and Nonlinear Random Projections, Random Fourier Features, and Random Kitchen Sinks: Tutorial and Survey

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-05T22:18:05.088170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:18:05.088170Z digest=sha256:83ed61c16c1994be3054bdee376ebbd8ec39db12c15c7df35cbca1d69429acbc

Observation 8d67dd88-b8eb-444b-8831-e21c2c2aa3b3 · outbound

This paper cites Chat-3D: Data-efficiently Tuning Large Language Model for Universal Dialogue of 3D Scenes.

PySeizure: A single machine learning classifier framework to detect seizures in diverse datasets Chat-3D: Data-efficiently Tuning Large Language Model for Universal Dialogue of 3D Scenes

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-05T22:18:05.111034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:18:05.111034Z digest=sha256:29a786bc13e91bf37b952cec292f85d92b399ed1f032709a56d8de50d0783b7e

Observation 06ed0679-4a3f-486a-9e0f-3c5071987df5 · outbound

This paper cites VideoCoT: A Video Chain-of-Thought Dataset with Active Annotation Tool.

PySeizure: A single machine learning classifier framework to detect seizures in diverse datasets VideoCoT: A Video Chain-of-Thought Dataset with Active Annotation Tool

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-05T22:18:05.105288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:18:05.105288Z digest=sha256:eb4743c27ee0d19cf0e0db656d32fd62b7edf06e3b82cb9af9dedab9e4a265f0

Observation 940a7956-ec5c-49aa-95d2-52ecc80c7c57 · outbound

This paper cites Qwen2.5-VL Technical Report.

PySeizure: A single machine learning classifier framework to detect seizures in diverse datasets Qwen2.5-VL Technical Report

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-05T22:18:05.076582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:18:05.076582Z digest=sha256:20fb303a2940f16e55bc12e5900dcc0e4f63dd761bf675ab30c8e5204d1a7fc0

Pith citing papers

No inbound Pith citation observations are available.