Paper Citation Record · LEDGER

SeFAR: Semi-supervised Fine-grained Action Recognition with Temporal Perturbation and Learning Stabilization

As of 20 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 1 inbound Pith citation observation for arXiv:2501.01245.

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

pith.paper-citation-record.v1
2501.01245 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:37:33.989944Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:19:03.529663Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T20:19:04.762757Z

Reference resolution

16 of 16 outbound references displayed

verified exact0
verified fuzzy7
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 084a6e37-c872-4a68-ba26-7a9b5df564e1 · outbound

This paper cites See https://vicuna.

SeFAR: Semi-supervised Fine-grained Action Recognition with Temporal Perturbation and Learning Stabilization See https://vicuna

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:37:34.481887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4f79a517-e34d-4881-b30e-b879115dbd53 · outbound

This paper cites Improved Regularization of Convolutional Neural Networks with Cutout.

SeFAR: Semi-supervised Fine-grained Action Recognition with Temporal Perturbation and Learning Stabilization Improved Regularization of Convolutional Neural Networks with Cutout

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T22:37:33.912254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f47afa19-0b36-462a-b084-c44ccfb345fd · outbound

This paper cites PaLM-E: An Embodied Multimodal Language Model.

SeFAR: Semi-supervised Fine-grained Action Recognition with Temporal Perturbation and Learning Stabilization PaLM-E: An Embodied Multimodal Language Model

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T22:37:33.917295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 915ee6af-cd7b-4b20-b759-8362c0016d8b · outbound

This paper cites Combined CNN Transformer Encoder for Enhanced Fine-grained Human Action Recognition.

SeFAR: Semi-supervised Fine-grained Action Recognition with Temporal Perturbation and Learning Stabilization Combined CNN Transformer Encoder for Enhanced Fine-grained Human Action Recognition

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T22:37:33.931226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5bfdad23-8556-4a7d-b21d-d49b20336729 · outbound

This paper cites In Proceedings of the IEEE/CVF Con- ference on Computer Vision and Pattern Recognition, 9568– 9578.

SeFAR: Semi-supervised Fine-grained Action Recognition with Temporal Perturbation and Learning Stabilization In Proceedings of the IEEE/CVF Con- ference on Computer Vision and Pattern Recognition, 9568– 9578

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:37:34.417401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 53bc015a-3cfa-4e93-aec8-f0d577dbe6be · outbound

This paper cites IEEE Access.

SeFAR: Semi-supervised Fine-grained Action Recognition with Temporal Perturbation and Learning Stabilization IEEE Access

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:37:34.395969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 83020ceb-ef7e-4bd7-9694-efd5b80cf17f · outbound

This paper cites InProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 26077–26087.

SeFAR: Semi-supervised Fine-grained Action Recognition with Temporal Perturbation and Learning Stabilization InProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 26077–26087

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:37:34.374188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9c605137-5d0b-461f-a0c0-26dfbf061253 · outbound

This paper cites ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection.

SeFAR: Semi-supervised Fine-grained Action Recognition with Temporal Perturbation and Learning Stabilization ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T22:37:33.961647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd4c1bb8-80d1-4d77-9dee-c730f417f8b3 · outbound

This paper cites VideoGLUE: Video General Understanding Evaluation of Foundation Models.

SeFAR: Semi-supervised Fine-grained Action Recognition with Temporal Perturbation and Learning Stabilization VideoGLUE: Video General Understanding Evaluation of Foundation Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T22:37:33.978829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd6903af-9981-4dfb-a805-811385cccc95 · outbound

This paper cites run- ning.

SeFAR: Semi-supervised Fine-grained Action Recognition with Temporal Perturbation and Learning Stabilization run- ning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T22:37:33.984143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c74e98ee-91df-437a-b8fd-15291f28c71e · outbound

This paper cites forward” vs. “backward.

SeFAR: Semi-supervised Fine-grained Action Recognition with Temporal Perturbation and Learning Stabilization forward” vs. “backward

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:37:34.353289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5be50374-cfd3-46e9-85a9-6eed03e1ea57 · outbound

This paper cites Hong, J.; Fisher, M.; Gharbi, M.; and Fatahalian, K.

SeFAR: Semi-supervised Fine-grained Action Recognition with Temporal Perturbation and Learning Stabilization Hong, J.; Fisher, M.; Gharbi, M.; and Fatahalian, K

Reference 329

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:37:34.437249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c8117453-c2de-4cbc-94f4-dae5a944dee0 · outbound

This paper cites In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning.

SeFAR: Semi-supervised Fine-grained Action Recognition with Temporal Perturbation and Learning Stabilization In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-10T22:37:33.936316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 689cd4c8-2f6e-4a32-a9c6-570889a5d0b4 · outbound

This paper cites In European conference on computer vision, 242–259.

SeFAR: Semi-supervised Fine-grained Action Recognition with Temporal Perturbation and Learning Stabilization In European conference on computer vision, 242–259

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:37:34.457115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e0c82653-6121-4f62-b930-296d5db7f578 · outbound

This paper cites MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning.

SeFAR: Semi-supervised Fine-grained Action Recognition with Temporal Perturbation and Learning Stabilization MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-10T22:37:33.901652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1667a234-4d85-4b5c-bd30-39e2921aa469 · outbound

This paper cites CMT: Cross Modulation Transformer with Hybrid Loss for Pansharpening.

SeFAR: Semi-supervised Fine-grained Action Recognition with Temporal Perturbation and Learning Stabilization CMT: Cross Modulation Transformer with Hybrid Loss for Pansharpening

Reference 2024

Resolution: metadata mismatch; local_arxiv, observed 2026-08-10T22:37:34.226854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

Observation 30c29b88-d4f5-4fca-9cf8-92cdf6eb58ca · inbound

FinePhys: Fine-grained Human Action Generation by Explicitly Incorporating Physical Laws for Effective Skeletal Guidance cites this paper.

FinePhys: Fine-grained Human Action Generation by Explicitly Incorporating Physical Laws for Effective Skeletal Guidance SeFAR: Semi-supervised Fine-grained Action Recognition with Temporal Perturbation and Learning Stabilization

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-08-15T20:19:04.855458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.