Paper Citation Record · LEDGER

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection

As of 11 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2505.19948.

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

pith.paper-citation-record.v1
2505.19948 v1

Coverage vector

measured 31 of 31 reference resolution

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measured 31 of 31 standing notices

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

31 of 31 outbound references displayed

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External citation measurements

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Outbound references

Observation a517cedf-de1b-4a76-b54b-af80dcdb7e78 · outbound

This paper cites Cellular struc- tural biology as revealed by cryo-electron tomogra- phy.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection Cellular struc- tural biology as revealed by cryo-electron tomogra- phy

Reference 1

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Observation f579a07d-eded-4dde-8de2-86464a6023c5 · outbound

This paper cites Cryo-electron tomography: gaining insight into cellular processes by structural approaches.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection Cryo-electron tomography: gaining insight into cellular processes by structural approaches

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:55.395994Z

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Observation 444679c5-360c-4cbb-bbeb-2943c8b02855 · outbound

This paper cites The architecture of inactivated SARS-CoV-2 with postfusion spikes revealed by cryo-EM and cryo- ET.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection The architecture of inactivated SARS-CoV-2 with postfusion spikes revealed by cryo-EM and cryo- ET

Reference 3

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Observation 851a8d45-212b-47ab-bde7-b28bea0342b6 · outbound

This paper cites Gum-net: Unsupervised geometric matching for fast and accurate 3d subtomogram im- age alignment and averaging.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection Gum-net: Unsupervised geometric matching for fast and accurate 3d subtomogram im- age alignment and averaging

Reference 4

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Observation 933d9e14-51e6-4cea-8fb7-11a72f572634 · outbound

This paper cites De novo structural pattern min- ing in cellular electron cryotomograms.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection De novo structural pattern min- ing in cellular electron cryotomograms

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:54.764397Z

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Observation 98ada6c8-5aa4-4955-a73b-14ade11c0e75 · outbound

This paper cites Cryo-electron tomography of cellular mi- crotubules.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection Cryo-electron tomography of cellular mi- crotubules

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:54.508006Z

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Observation 6ceb576c-569b-4512-ae98-761a3b8a5361 · outbound

This paper cites Structural biology in situ—the potential of subtomogram averaging.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection Structural biology in situ—the potential of subtomogram averaging

Reference 7

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Observation f4d78cb1-c68e-4a49-b173-969501001a0f · outbound

This paper cites Deep learn- ing improves macromolecule identification in 3D cel- lular cryo-electron tomograms.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection Deep learn- ing improves macromolecule identification in 3D cel- lular cryo-electron tomograms

Reference 8

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Observation ef7b4278-fd00-4ac8-8c42-a4a3dfdd0502 · outbound

This paper cites SHREC 2020: Classi- fication in cryo-electron tomograms.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection SHREC 2020: Classi- fication in cryo-electron tomograms

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:53.916751Z

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Observation 0d08a979-1d7d-478a-a99d-6e2406b8a720 · outbound

This paper cites DeepET- Picker: Fast and accurate 3D particle picking for cryo- electron tomography using weakly supervised deep learning.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection DeepET- Picker: Fast and accurate 3D particle picking for cryo- electron tomography using weakly supervised deep learning

Reference 10

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Observation e2f492ca-0f84-4f62-a361-2e6a6214e6e8 · outbound

This paper cites Augmix: A simple data pro- cessing method to improve robustness and uncertainty.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection Augmix: A simple data pro- cessing method to improve robustness and uncertainty

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:53.490700Z

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Observation 9413d8d6-28be-43f5-8deb-5b14f7193e87 · outbound

This paper cites The surprising effectiveness of representation learning for visual imitation.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection The surprising effectiveness of representation learning for visual imitation

Reference 12

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Observation 8cc4f307-a8db-48b7-bf2f-e97465838538 · outbound

This paper cites Unsupervised visual representation learning by context prediction.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection Unsupervised visual representation learning by context prediction

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:53.065255Z

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Observation 9d744335-49f9-4ff2-94e1-7e18aff57ea6 · outbound

This paper cites Boosting self-supervised learning via knowledge transfer.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection Boosting self-supervised learning via knowledge transfer

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:52.764057Z

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Observation bd1596cb-1fe3-4449-b045-e9cd5fe52169 · outbound

This paper cites Identification of macromolecu- lar complexes in cryoelectron tomograms of phantom cells.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection Identification of macromolecu- lar complexes in cryoelectron tomograms of phantom cells

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:52.520112Z

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Observation 74f9fab4-1d05-4723-9278-f50b4bb3f131 · outbound

This paper cites DoG Picker and TiltPicker: software tools to facilitate particle selection in single particle electron microscopy.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection DoG Picker and TiltPicker: software tools to facilitate particle selection in single particle electron microscopy

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:52.264885Z

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Observation a47c2440-b7b6-4169-8d43-04638128ac9f · outbound

This paper cites Detection and identification of macromolecu- lar complexes in cryo-electron tomograms using sup- port vector machines.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection Detection and identification of macromolecu- lar complexes in cryo-electron tomograms using sup- port vector machines

Reference 17

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Observation 7d9591b3-8849-432d-8af8-027cace4a8e4 · outbound

This paper cites Improved deep learning-based macromolecules structure classification from electron cryo-tomograms.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection Improved deep learning-based macromolecules structure classification from electron cryo-tomograms

Reference 18

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Observation bdd35af3-51d4-470d-8b8b-0512e4db072e · outbound

This paper cites Very deep convolutional networks for large-scale image recognition.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection Very deep convolutional networks for large-scale image recognition

Reference 19

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Observation 9b1e7d72-161d-4b2e-9c93-3e0d8eae8959 · outbound

This paper cites Deep residual learning for image recognition.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection Deep residual learning for image recognition

Reference 20

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Observation 052e1400-0fa6-4bfa-accb-974e0c5b78e4 · outbound

This paper cites SuRV oS: super-region volume seg- mentation workbench.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection SuRV oS: super-region volume seg- mentation workbench

Reference 21

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Observation e5001c27-b0b3-4d6f-93d9-714b875f1a04 · outbound

This paper cites Convolutional neural networks for auto- mated annotation of cellular cryo-electron tomograms.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection Convolutional neural networks for auto- mated annotation of cellular cryo-electron tomograms

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:51.024838Z

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Observation 642bf26b-e353-41f2-96f7-384cdf8b2af8 · outbound

This paper cites Automatic localization and identification of mi- tochondria in cellular electron cryo-tomography using faster-RCNN.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection Automatic localization and identification of mi- tochondria in cellular electron cryo-tomography using faster-RCNN

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:50.842073Z

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Observation fbc153c8-38b5-43c9-b122-6e4bd1723603 · outbound

This paper cites Faster R-CNN: To- wards real-time object detection with region proposal networks.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection Faster R-CNN: To- wards real-time object detection with region proposal networks

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:50.676789Z

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Observation f8a49956-1a02-497e-b209-3b64589066e2 · outbound

This paper cites Few-shot learning for classification of novel macro- molecular structures in cryo-electron tomograms.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection Few-shot learning for classification of novel macro- molecular structures in cryo-electron tomograms

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:50.512312Z

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Observation 49c51559-eb3a-4a4f-9f20-51362a231a73 · outbound

This paper cites Un- derstanding and improving the role of projection head in self-supervised learning.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection Un- derstanding and improving the role of projection head in self-supervised learning

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:50.313640Z

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Observation 8b601d2b-e022-4bdd-ad9d-aa77268baf7d · outbound

This paper cites cc3d: Connected components on mul- tilabel 3D & 2D images.; 2021.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection cc3d: Connected components on mul- tilabel 3D & 2D images.; 2021

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:50.149638Z

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Observation 313a51da-8c6e-41c2-bc3d-861f828f1598 · outbound

This paper cites In situ structure of neuronal C9orf72 poly-GA aggregates reveals proteasome re- cruitment.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection In situ structure of neuronal C9orf72 poly-GA aggregates reveals proteasome re- cruitment

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:49.983992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 65488872-a8b8-4d0a-b503-5c96643f42e1 · outbound

This paper cites SHREC 2021: Classification in Cryo-electron Tomograms.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection SHREC 2021: Classification in Cryo-electron Tomograms

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:49.796810Z

Source-reported events for the cited work

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Observation ae3e9cda-e34d-487f-aaa3-1e6939c1ab6e · outbound

This paper cites A value for n-person games.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection A value for n-person games

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:49.588752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b8a281f8-a096-4a32-adfc-9a10a6fdc5fc · outbound

This paper cites A unified approach to inter- preting model predictions.

SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection A unified approach to inter- preting model predictions

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:07:49.365189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Pith citing papers

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