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Paper Citation Record · LEDGER

An In-Depth Analysis of Adversarial Discriminative Domain Adaptation for Digit Classification

As of 17 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2412.19391.

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

pith.paper-citation-record.v1
2412.19391 v2

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T00:40:47.795497Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

16 of 16 outbound references displayed

  • verified exact0
  • verified fuzzy12
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ec34a711-b286-47de-a01e-af78aa442e43 · outbound

This paper cites an unresolved cited work.

An In-Depth Analysis of Adversarial Discriminative Domain Adaptation for Digit Classification Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-11T00:40:48.089429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T00:40:47.721799Z digest=sha256:de5675dda16f1d752e3e09a3ee951d6fe1a7904b66a3913b7d81125736fd91f1

Observation 19d15395-47d7-45e6-bfe9-0657ee756896 · outbound

This paper cites Deep domain confusion: Maximizing for domain invariance, 2014.

An In-Depth Analysis of Adversarial Discriminative Domain Adaptation for Digit Classification Deep domain confusion: Maximizing for domain invariance, 2014

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:40:48.074265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T00:40:47.727912Z digest=sha256:d8dac3bf10c547038524209c2049eb4c9401ac4481b7cdef5f31fa0465dae675

Observation 9f0079fc-a8b6-4eca-98fb-8aa7e1dad012 · outbound

This paper cites Adversarial discriminative domain adaptation, 2017.

An In-Depth Analysis of Adversarial Discriminative Domain Adaptation for Digit Classification Adversarial discriminative domain adaptation, 2017

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:40:48.057451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T00:40:47.732757Z digest=sha256:0f0a5ad8f357de43c6d8ed0759be23bb6d07ccc53a8431d14c8cb8aaf3839bf5

Observation 82120ae1-db26-4ba0-bb19-54fe19176a22 · outbound

This paper cites Lecun, L.

An In-Depth Analysis of Adversarial Discriminative Domain Adaptation for Digit Classification Lecun, L

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:40:48.041452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T00:40:47.737901Z digest=sha256:d66acda2f1d9f8ea3fcccaab14bb54cc1d288be643ea29b5bbb00577aa0d24bd

Observation 7aa3e606-4421-4470-b6cd-ce08b37ae842 · outbound

This paper cites an unresolved cited work.

An In-Depth Analysis of Adversarial Discriminative Domain Adaptation for Digit Classification Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-11T00:40:48.024819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T00:40:47.742927Z digest=sha256:9819b5ff653ec494ca0433fbd808a4b1e31e9fdf92e07034c095a8bdd0509076

Observation 7b58b526-75fe-47bf-a11c-af92ee90d85a · outbound

This paper cites an unresolved cited work.

An In-Depth Analysis of Adversarial Discriminative Domain Adaptation for Digit Classification Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-11T00:40:48.006083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T00:40:47.747941Z digest=sha256:9e93e4c83cf4a2c4991ad8a348185c2f373118a69e15f49555a58b1d2af2975b

Observation e8102216-3fdd-4fbd-af1a-1a88c483a4da · outbound

This paper cites Kouw and Marco Loog.

An In-Depth Analysis of Adversarial Discriminative Domain Adaptation for Digit Classification Kouw and Marco Loog

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:40:47.989050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T00:40:47.753259Z digest=sha256:610d167a902a860c782b193a5bd69bebd1ee5dd3aeb3cbea9d89a9fd9419542c

Observation 2e885dd4-7ffb-4e3d-88f3-3b29696f2e0b · outbound

This paper cites Hospedales.

An In-Depth Analysis of Adversarial Discriminative Domain Adaptation for Digit Classification Hospedales

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:40:47.971277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T00:40:47.758154Z digest=sha256:2283821a927fd1536972173bbda42121b63aadb836ed11e6be03f27b61d6186a

Observation 44a81218-b805-43c8-ac39-633338d9dd37 · outbound

This paper cites Domain-adversarial train- ing of neural networks, 2016.

An In-Depth Analysis of Adversarial Discriminative Domain Adaptation for Digit Classification Domain-adversarial train- ing of neural networks, 2016

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:40:47.955351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T00:40:47.762846Z digest=sha256:3708d1fea559b2d006351a49298b8c95f690ad540005101f3de7c76bd3128b71

Observation e24b5233-9442-45a2-90d0-d2c6db53ed52 · outbound

This paper cites Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio.

An In-Depth Analysis of Adversarial Discriminative Domain Adaptation for Digit Classification Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:40:47.939541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T00:40:47.767478Z digest=sha256:691416aeb17039a4cef7ed440a573407aa5e2a1bf06c2feb88f8f5782337c968

Observation bb2544a5-10b1-45e8-a412-cffb271548dd · outbound

This paper cites Adversarial autoencoders,.

An In-Depth Analysis of Adversarial Discriminative Domain Adaptation for Digit Classification Adversarial autoencoders,

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-11T00:40:47.772095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:40:47.772095Z digest=sha256:ebb06238e299b07f93a3b62dbec8423afb39018eb95a0357bc9332c2da77aff5

Observation 5f6d910d-946a-4de1-90b5-c347dabab8ae · outbound

This paper cites Domain randomization for transferring deep neural networks from simulation to the real world, 2017.

An In-Depth Analysis of Adversarial Discriminative Domain Adaptation for Digit Classification Domain randomization for transferring deep neural networks from simulation to the real world, 2017

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:40:47.910204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T00:40:47.776643Z digest=sha256:565c939f824de7e0fe0c926bdd0e95b63472e0a83185be19b95ad633970d3890

Observation bc5d5a28-b4f3-41eb-a397-4fc45ab74f5d · outbound

This paper cites Caffe: Convolutional architecture for fast feature embedding, 2014.

An In-Depth Analysis of Adversarial Discriminative Domain Adaptation for Digit Classification Caffe: Convolutional architecture for fast feature embedding, 2014

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:40:47.891244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T00:40:47.781234Z digest=sha256:a473032807d6af787f278d1a5ba28bef912a0c2957df303b09574be7a5bfd38e

Observation a1f5e9ac-c3f4-499c-9cfd-e60dfc8ebdf6 · outbound

This paper cites Kingma and Jimmy Ba.

An In-Depth Analysis of Adversarial Discriminative Domain Adaptation for Digit Classification Kingma and Jimmy Ba

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:40:47.871883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T00:40:47.786130Z digest=sha256:1dfa9b004d1f0e773073974d666f4087783b73389fdbeda330376bee8165ddbe

Observation 58e80adf-6f8f-4389-83cd-802d5ff3a8d2 · outbound

This paper cites Visualizing data using t-sne.

An In-Depth Analysis of Adversarial Discriminative Domain Adaptation for Digit Classification Visualizing data using t-sne

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:40:47.854248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T00:40:47.791027Z digest=sha256:b9b889a1bdf7c78b4a07f90d782f45d4be462612873c6927798ec5851d7aa8bd

Observation 1005e44c-f288-4025-979f-5ea7ec8afc83 · outbound

This paper cites Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Ba- tra.

An In-Depth Analysis of Adversarial Discriminative Domain Adaptation for Digit Classification Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Ba- tra

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:40:47.835556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T00:40:47.795497Z digest=sha256:35b3df483aa5654d67b2c173938e3e59290fb278b9e94b9b265ae5ad0537e0dc

Pith citing papers

No inbound Pith citation observations are available.