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Paper Citation Record · LEDGER

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation

As of 8 August 2026, this Paper Citation Record lists 100 of 125 outbound references and 0 inbound Pith citation observations for arXiv:2505.22099.

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

pith.paper-citation-record.v1
2505.22099 v1

Coverage vector

measured 100 of 125 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:23:23.738084Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

100 of 125 outbound references displayed

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  • verified fuzzy33
  • unresolved63
  • parse uncertain0
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External citation measurements

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Outbound references

Observation da042f2b-2574-4d26-9643-1def957d2440 · outbound

This paper cites Domain-adversarial training of neural networks,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Domain-adversarial training of neural networks,

Reference 1

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Observation f3d458ea-de26-4f6b-be04-77d9e5df316f · outbound

This paper cites Unsupervised multi-class domain adaptation: Theory, algorithms, and practice,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Unsupervised multi-class domain adaptation: Theory, algorithms, and practice,

Reference 2

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Observation 8397acf6-7ff4-43f9-891f-60f533d01eae · outbound

This paper cites Unified optimal transport framework for universal domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Unified optimal transport framework for universal domain adaptation,

Reference 3

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Observation 98bfc3bd-3554-461c-8a50-33ad1d2c4b5c · outbound

This paper cites Transvqa: Transferable vector quantization alignment for unsupervised domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Transvqa: Transferable vector quantization alignment for unsupervised domain adaptation,

Reference 4

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Observation 2c22f1cd-f41c-4a08-b38e-3181f37f57e6 · outbound

This paper cites Learning transferable conceptual prototypes for interpretable unsupervised domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Learning transferable conceptual prototypes for interpretable unsupervised domain adaptation,

Reference 5

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Observation 345b2bcb-cf00-46cc-ab7c-490aafadc119 · outbound

This paper cites Wasserstein distance guided representation learning for domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Wasserstein distance guided representation learning for domain adaptation,

Reference 6

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Observation da34af0a-c6f8-467e-bd11-b6a067ca2346 · outbound

This paper cites Wasserstein generative adversarial networks,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Wasserstein generative adversarial networks,

Reference 7

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Observation 52509e20-2cf5-4ec4-89da-599366122c82 · outbound

This paper cites Bridging theory and algorithm for domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Bridging theory and algorithm for domain adaptation,

Reference 8

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Observation f6c310b2-f1bd-47c6-b41c-503bce7b2202 · outbound

This paper cites Probability- polarized optimal transport for unsupervised domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Probability- polarized optimal transport for unsupervised domain adaptation,

Reference 9

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Observation 462f7540-a8ab-4f13-a30d-1f8756bf5810 · outbound

This paper cites Prompt-based distribution alignment for unsupervised domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Prompt-based distribution alignment for unsupervised domain adaptation,

Reference 10

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Observation 8abbf2a0-7414-4cc5-8066-b29893b4df89 · outbound

This paper cites Unsupervised and semi-supervised robust spherical space domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Unsupervised and semi-supervised robust spherical space domain adaptation,

Reference 11

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Observation 9d5f3618-bf9a-4143-9ad6-1d3c3dc9ebf6 · outbound

This paper cites Pseudo-calibration: Improving predictive uncertainty estimation in unsupervised domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Pseudo-calibration: Improving predictive uncertainty estimation in unsupervised domain adaptation,

Reference 12

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Observation 698152d5-8e19-4f6b-adbf-a7473b0ea690 · outbound

This paper cites Class-incremental unsupervised domain adaptation via pseudo-label distillation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Class-incremental unsupervised domain adaptation via pseudo-label distillation,

Reference 13

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Observation 6732a5df-5ed8-4889-9d3d-8202554c16ea · outbound

This paper cites A versatile framework for unsupervised domain adaptation based on instance weighting,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation A versatile framework for unsupervised domain adaptation based on instance weighting,

Reference 14

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Observation 32d8b530-0443-472a-a044-bb1c669ed506 · outbound

This paper cites Where and how to transfer: Knowledge aggregation-induced transferability perception for unsupervised domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Where and how to transfer: Knowledge aggregation-induced transferability perception for unsupervised domain adaptation,

Reference 15

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Observation a2ee67c5-e752-455b-911d-5d7826496932 · outbound

This paper cites Contrastive adap- tation network for unsupervised domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Contrastive adap- tation network for unsupervised domain adaptation,

Reference 16

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Observation bfaf7374-1f09-4f69-a48f-cde338a2e186 · outbound

This paper cites Robust local preserving and global aligning network for adversarial domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Robust local preserving and global aligning network for adversarial domain adaptation,

Reference 17

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Observation d179553c-a24d-4953-b046-25b2e738228a · outbound

This paper cites Auxiliary task guided mean and covariance alignment network for adversarial domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Auxiliary task guided mean and covariance alignment network for adversarial domain adaptation,

Reference 18

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Observation c7b22be4-782f-476f-ac6b-059e1c96e5a3 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Representation Learning with Contrastive Predictive Coding

Reference 19

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Observation f9bee578-1497-4008-9ff3-9afa8a419207 · outbound

This paper cites A simple framework for contrastive learning of visual representations,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation A simple framework for contrastive learning of visual representations,

Reference 20

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Observation 95ac679a-904f-4617-b8a0-0325502e7e7b · outbound

This paper cites Intriguing Properties of Contrastive Losses.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Intriguing Properties of Contrastive Losses

Reference 21

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Observation abfe331b-353f-46a9-8be6-13e6fe1b5a06 · outbound

This paper cites Understanding self-training for gradual domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Understanding self-training for gradual domain adaptation,

Reference 22

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Observation accabe56-9db2-4673-acfd-2cdc5b494191 · outbound

This paper cites Margin-aware adversarial domain adaptation with optimal transport,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Margin-aware adversarial domain adaptation with optimal transport,

Reference 23

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Observation 91cbc1b3-f527-4c34-819b-794810431cd5 · outbound

This paper cites Robust Optimal Transport with Applications in Generative Modeling and Domain Adaptation.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Robust Optimal Transport with Applications in Generative Modeling and Domain Adaptation

Reference 24

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Observation 6f1ab504-f2c9-4ad4-9fb9-9e517cd2a893 · outbound

This paper cites Gradually vanishing bridge for adversarial domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Gradually vanishing bridge for adversarial domain adaptation,

Reference 25

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Observation 82d04898-004a-4642-a6f6-d8fb68f2bcda · outbound

This paper cites Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift

Reference 26

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Observation 89a93504-10a3-4261-acd1-9eb3ca864443 · outbound

This paper cites Heuristic Domain Adaptation.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Heuristic Domain Adaptation

Reference 27

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Observation c22d5e17-14fa-45b2-8591-06718aa6eb9b · outbound

This paper cites Unsupervised domain adaptation with hierarchical gradient synchronization,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Unsupervised domain adaptation with hierarchical gradient synchronization,

Reference 28

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Observation c28b684c-09ed-4238-82ed-1d43ae232a8c · outbound

This paper cites Pixel-Level Cycle Association: A New Perspective for Domain Adaptive Semantic Segmentation.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Pixel-Level Cycle Association: A New Perspective for Domain Adaptive Semantic Segmentation

Reference 29

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Observation af91c079-4f34-4117-aac7-7b3500e78915 · outbound

This paper cites Unsupervised domain adaptation via structurally regularized deep clustering,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Unsupervised domain adaptation via structurally regularized deep clustering,

Reference 30

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Observation 6bf023c9-0a5a-4da1-bcf4-2b86cf56ede5 · outbound

This paper cites A kernel two-sample test,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation A kernel two-sample test,

Reference 31

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Observation 62ce4794-45ad-4023-a277-07ac723bd9ea · outbound

This paper cites Deep Domain Confusion: Maximizing for Domain Invariance.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Deep Domain Confusion: Maximizing for Domain Invariance

Reference 32

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Observation 18f04e58-85bb-405f-9ac8-355d077a6083 · outbound

This paper cites Return of frustratingly easy domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Return of frustratingly easy domain adaptation,

Reference 33

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Observation 96c51cc3-aa5d-45ae-bc9d-36b585ececdf · outbound

This paper cites Unsupervised domain adaptation based on source-guided discrepancy,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Unsupervised domain adaptation based on source-guided discrepancy,

Reference 34

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Observation 2c18065b-19c1-43fb-be8a-7d522ccc2f28 · outbound

This paper cites Sliced wasserstein discrepancy for unsupervised domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Sliced wasserstein discrepancy for unsupervised domain adaptation,

Reference 35

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Observation d25a715a-3a2d-4598-a2be-82f8cb72d4ec · outbound

This paper cites Domain adaptation with asymmetrically-relaxed distribution alignment,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Domain adaptation with asymmetrically-relaxed distribution alignment,

Reference 36

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Observation 045aca7d-2aa1-4663-9b94-f5a304ccaec8 · outbound

This paper cites Reliable weighted optimal transport for unsupervised domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Reliable weighted optimal transport for unsupervised domain adaptation,

Reference 37

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Observation def9c42f-4b8c-4e6f-8ea4-7fb09996d84c · outbound

This paper cites Enhanced transport distance for unsupervised domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Enhanced transport distance for unsupervised domain adaptation,

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Observation 2d2df161-176c-495d-b451-3a2a2e307f28 · outbound

This paper cites Transferability vs. discriminability: Batch spectral penalization for adversarial domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Transferability vs. discriminability: Batch spectral penalization for adversarial domain adaptation,

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Observation 5aca8283-3358-46f4-b323-a4d76f5dfaed · outbound

This paper cites Gradient harmonization in unsuper- vised domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Gradient harmonization in unsuper- vised domain adaptation,

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Observation f01b1265-8215-4614-af64-be017f75c67b · outbound

This paper cites Cycle self-training for domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Cycle self-training for domain adaptation,

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Observation 2b1e2d32-60ce-467f-aef2-4ede4053c6cd · outbound

This paper cites Domain Adaptation: Learning Bounds and Algorithms.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Domain Adaptation: Learning Bounds and Algorithms

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Observation 8deb3e22-5ed5-4760-9f5e-5702f2b3688d · outbound

This paper cites A theory of learning from different domains,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation A theory of learning from different domains,

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Observation de9d7289-486c-43f3-80f4-d27776f40c0d · outbound

This paper cites New analysis and algorithm for learning with drifting distributions,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation New analysis and algorithm for learning with drifting distributions,

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Observation 3bf31d16-1a2a-4b02-aa4d-7af9bf514fd1 · outbound

This paper cites A pac-bayesian approach for domain adaptation with specialization to linear classifiers,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation A pac-bayesian approach for domain adaptation with specialization to linear classifiers,

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Observation baad5ba3-fce8-4504-b0ce-69484bf5cee2 · outbound

This paper cites Adaptation algorithm and theory based on generalized discrepancy,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Adaptation algorithm and theory based on generalized discrepancy,

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Observation ff3d0307-f73f-48ca-8557-855da7ad5369 · outbound

This paper cites Theoretical analysis of domain adaptation with optimal transport,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Theoretical analysis of domain adaptation with optimal transport,

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Observation c08df585-75a6-42e5-baa0-72b91ba6a953 · outbound

This paper cites On learn- ing invariant representations for domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation On learn- ing invariant representations for domain adaptation,

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source=pdf_text observed=2026-08-07T13:23:18.667251Z digest=sha256:a6ab052d417f3da4e72f4c6d04225e04dccc0f28538b9fea7470f7c4f99d17d8

Observation 2d6d6670-7618-4b2a-bd6e-751aab067669 · outbound

This paper cites The information bottleneck method.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation The information bottleneck method

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source=pdf_text observed=2026-08-07T13:23:18.823031Z digest=sha256:b08e58019fb303b8413f3e38ba676ebe1ab15701652017f1c4146b178173340d

Observation d0b1bf02-e7ce-4af7-9c91-9f8a31b373d3 · outbound

This paper cites An information theoretic framework for multi-view learning,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation An information theoretic framework for multi-view learning,

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Observation e6fb5ab3-1ca4-46f1-905b-eb0d3c7a90bc · outbound

This paper cites A Survey on Multi-view Learning.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation A Survey on Multi-view Learning

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Observation 4d6d9321-a3ea-403d-8112-4721ecc633a1 · outbound

This paper cites Self-supervised Learning from a Multi-view Perspective.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Self-supervised Learning from a Multi-view Perspective

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Observation c8c19593-e513-42c0-82e0-e78d7a995ee2 · outbound

This paper cites an unresolved cited work.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Unresolved cited work

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Observation 686f65ae-0a51-4137-b888-712ce2d82760 · outbound

This paper cites Representation learning: A review and new perspectives,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Representation learning: A review and new perspectives,

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Observation 41296997-b960-407c-b797-0513dc14e6e4 · outbound

This paper cites Learning deep features for discriminative localization,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Learning deep features for discriminative localization,

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Observation 2b35cb55-af61-49ae-b5c4-9cf83988eae3 · outbound

This paper cites Focal Loss for Dense Object Detection.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Focal Loss for Dense Object Detection

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Observation e32e7879-49fd-46cd-9fae-961db68ef65b · outbound

This paper cites Efficient Estimation of Word Representations in Vector Space.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Efficient Estimation of Word Representations in Vector Space

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Observation 6a5368ee-d7e1-4891-9bbf-1d3a21f5144f · outbound

This paper cites Earth mover’s distances on discrete surfaces,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Earth mover’s distances on discrete surfaces,

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source=pdf_text observed=2026-08-07T13:23:19.840446Z digest=sha256:ba7cad2afbdf0d5e28485435c04b8a7a02c0d2870c91b9139fde7832e1777cfa

Observation b3211d25-ece8-4016-bc68-3335a5eec847 · outbound

This paper cites The earth mover’s distance as a metric for image retrieval,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation The earth mover’s distance as a metric for image retrieval,

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Observation 6f7b29a9-900e-428f-a829-dbd31f657c8a · outbound

This paper cites Transport information geometry I: Riemannian calculus on probability simplex.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Transport information geometry I: Riemannian calculus on probability simplex

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 70ed45be-3f8c-438c-8cd8-d0b6d9c5d73b · outbound

This paper cites Wasserstein of wasserstein loss for learning generative models,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Wasserstein of wasserstein loss for learning generative models,

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Observation 9b007feb-fa2f-43cb-a754-d8dff797f607 · outbound

This paper cites Villaniet al.,Optimal transport: old and new.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Villaniet al.,Optimal transport: old and new

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Observation bfd9ae88-1fe4-4378-b128-349203563e48 · outbound

This paper cites Improved training of wasserstein gans,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Improved training of wasserstein gans,

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Observation 9b94e0ef-cc73-482a-9cd8-9ce86974fd62 · outbound

This paper cites On the regularization of wasserstein gans,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation On the regularization of wasserstein gans,

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation e0ea0db1-17a8-4d4f-be9a-64c3f63bf498 · outbound

This paper cites Relations between entropy and error probability,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Relations between entropy and error probability,

Reference 65

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation cba2e500-e00f-48ed-8445-b62be5242a1f · outbound

This paper cites Deep hashing network for unsupervised domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Deep hashing network for unsupervised domain adaptation,

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation f5c1925c-59db-42cd-9420-567eb541e36a · outbound

This paper cites Adapting visual category models to new domains,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Adapting visual category models to new domains,

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation dc7884a4-d858-454d-9056-485eef89178d · outbound

This paper cites VisDA: The Visual Domain Adaptation Challenge.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation VisDA: The Visual Domain Adaptation Challenge

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Observation ef4665bb-d4ae-4396-b0c2-b5bf4eff88f5 · outbound

This paper cites A database for handwritten text recognition research,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation A database for handwritten text recognition research,

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation abf2ade8-7fef-4c0d-8dc7-38d549df7fcd · outbound

This paper cites Reading digits in natural images with unsupervised feature learning,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Reading digits in natural images with unsupervised feature learning,

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation f0cab972-5d7a-4b07-8df7-35299107e81d · outbound

This paper cites Gradient-based learning applied to document recognition,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Gradient-based learning applied to document recognition,

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 11847eff-8892-4ef0-aa86-40af4f620adb · outbound

This paper cites Moment matching for multi-source domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Moment matching for multi-source domain adaptation,

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation e12afb27-278b-45ef-829f-182731de0067 · outbound

This paper cites Deep residual learning for image recognition,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Deep residual learning for image recognition,

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source=pdf_text observed=2026-08-07T13:23:21.047562Z digest=sha256:beede8296afc083ce634167dbee70394ead8a5b16589645b009aee77167eadf4

Observation 24eceb98-99b8-467c-9800-62bd97b69ead · outbound

This paper cites Learning transferable features with deep adaptation networks,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Learning transferable features with deep adaptation networks,

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verified fuzzy
raw_fallback, observed 2026-08-07T13:23:36.954292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 366dc9b5-3d82-4cc0-b374-ed05319ef507 · outbound

This paper cites Deep transfer learning with joint adaptation networks,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Deep transfer learning with joint adaptation networks,

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source=pdf_text observed=2026-08-07T13:23:21.193929Z digest=sha256:c1356208eaf7b605d70d5bce9d5b1f12fc50abd9190a1ff2665bab938d62420e

Observation 99cfdae0-0550-45ee-871d-17782e3a826e · outbound

This paper cites Generate to adapt: Aligning domains using generative adversarial networks,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Generate to adapt: Aligning domains using generative adversarial networks,

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:23:21.302987Z digest=sha256:75892a0ab775a3188d8a346562c150b37cfcb92bf64add00ccbc575837e39af7

Observation 895f1bcd-747f-4906-84e3-6dea38055726 · outbound

This paper cites Adversarial discrimi- native domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Adversarial discrimi- native domain adaptation,

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:36.464581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:23:21.394541Z digest=sha256:9cfb3c1cec46164f19646b26b76712141f0b4a6f3fece96adedc4961c5809fad

Observation bdf0555f-290e-4247-bf68-1f5df4835e69 · outbound

This paper cites Unsupervised image-to-image transla- tion networks,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Unsupervised image-to-image transla- tion networks,

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:36.317603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:23:21.514154Z digest=sha256:2ab82e5969921d403e8be9279997224ea65c6608aea6ced7a48e6450e4075730

Observation 226e25c5-66a6-4ae4-a2de-38af3e49c818 · outbound

This paper cites Cycada: Cycle-consistent adversarial domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Cycada: Cycle-consistent adversarial domain adaptation,

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:36.134986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:23:21.623489Z digest=sha256:8ba24795c722386dc944a114c2f63bd8c574b2d4b18338310675adfa5bb82bcd

Observation 636071f6-5307-40a5-8f7a-99639860e554 · outbound

This paper cites Conditional Adversarial Domain Adaptation.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Conditional Adversarial Domain Adaptation

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:21.681661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:23:21.681661Z digest=sha256:c329ecd43ae4cc3c9d86febb6d58c862b8880bff7c89db71b214049173b7bbe9

Observation 63472de2-4f4a-43ec-b5cc-4c0d6876bee7 · outbound

This paper cites Maximum classifier discrepancy for unsupervised domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Maximum classifier discrepancy for unsupervised domain adaptation,

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:36.024291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:23:21.826504Z digest=sha256:8630583b6f771c039ee661b2623332b9610a080ac264dbab70aa992d14f38173

Observation b01131e1-f80e-4689-bb73-dd848a552d2f · outbound

This paper cites Bridging theory and algorithm for domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Bridging theory and algorithm for domain adaptation,

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:35.894678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:23:21.929001Z digest=sha256:07aead593267b47303427c22f8b38be7ef1bf30bd5b24f73cf0a9f697523d596

Observation 419c29e1-5e79-4c4f-8208-4df51dc708d0 · outbound

This paper cites Invariant and transportable representations for anti-causal domain shifts,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Invariant and transportable representations for anti-causal domain shifts,

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:35.768253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:23:22.066902Z digest=sha256:acfe0b1381d2b66bd9de23344bc519924e1fcdf060d45fdb7092dbebd1c91a7a

Observation 4ec771a2-aaf2-402b-bc67-8abd1714e880 · outbound

This paper cites Transporting causal mechanisms for unsupervised domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Transporting causal mechanisms for unsupervised domain adaptation,

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:35.606886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:23:22.176935Z digest=sha256:6f27301f175876726a9772e132bf8d5263e32b2b7d3c8734cc569e0d9d7a6547

Observation f0dc2dd6-e687-44f4-a1bf-153704fe1a52 · outbound

This paper cites Connect, not collapse: Explaining contrastive learning for unsupervised domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Connect, not collapse: Explaining contrastive learning for unsupervised domain adaptation,

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:35.482462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:23:22.260673Z digest=sha256:bb28684e805aecc3ae6a4d29b66658dfb86b63c47caeb8cc5e62c3a9e3284bda

Observation c1a70b59-30dc-4077-898e-5e28d61b6707 · outbound

This paper cites Identifiability conditions for domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Identifiability conditions for domain adaptation,

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:35.361878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:23:22.313649Z digest=sha256:37a69d2829d18afb91c1ebe4ac9cd8ab401f298f2b15b85ee3076c084d64abad

Observation 17ef19a4-6640-4248-9a97-19c4c1937b40 · outbound

This paper cites Partial disentanglement for domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Partial disentanglement for domain adaptation,

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:35.222855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:23:22.371773Z digest=sha256:a6e7adf7ecfe82ed195110ca929632c9798e5487c6d8b0b8f47b138634e0d7db

Observation 69b035a6-f214-4f8f-85d3-bd8744ad17ce · outbound

This paper cites Dcan: Dual channel-wise alignment networks for unsupervised scene adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Dcan: Dual channel-wise alignment networks for unsupervised scene adaptation,

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:35.080962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:23:22.428471Z digest=sha256:72ec60e43db28cd3023b8aaefe1ad76fdd3e2dfe02381aad43fdff271eeeaa51

Observation 9efccba9-a412-4b83-9613-be7dd65e1547 · outbound

This paper cites Unsupervised domain adaptation for semantic segmentation via class-balanced self-training,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Unsupervised domain adaptation for semantic segmentation via class-balanced self-training,

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:34.927638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:23:22.482749Z digest=sha256:5c17133d3fdb42b50dbe9b2af89330301da466070c9138009f98047a431e0cf7

Observation adc2c211-fbb8-4528-8d99-410c2e7332a0 · outbound

This paper cites Advent: Adversarial entropy minimization for domain adaptation in semantic segmentation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Advent: Adversarial entropy minimization for domain adaptation in semantic segmentation,

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:34.734884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:23:22.573222Z digest=sha256:6cb50f8627479514bb72d4d511fc21d99c443731bbd66635274c6ef6437d508d

Observation 654694d5-ea3c-43ad-8c78-de46fb024107 · outbound

This paper cites Semantic-transferable weakly- supervised endoscopic lesions segmentation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Semantic-transferable weakly- supervised endoscopic lesions segmentation,

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:34.556569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:23:22.722213Z digest=sha256:b095e5838766e0f682d443ba582c41b00fa203dcbcc6fdcf8a3a30a0f45b2445

Observation d8587d87-10d8-4d16-abe6-ae83fafa59d0 · outbound

This paper cites Domain adaptation for semantic segmentation with maximum squares loss,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Domain adaptation for semantic segmentation with maximum squares loss,

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:34.443577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:23:22.834099Z digest=sha256:2e0d997ba437223acad007abc2c1284177aad598294c1e4ef14fa67c3f0f1af6

Observation 5c096186-6826-48f3-9488-df065c8caa16 · outbound

This paper cites Constructing self-motivated pyramid curriculums for cross-domain semantic segmentation: A non- adversarial approach,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Constructing self-motivated pyramid curriculums for cross-domain semantic segmentation: A non- adversarial approach,

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:34.229174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:23:22.919224Z digest=sha256:70b3586b6ac31afc9977f297b8b39d3f98d14cce67811da4287d7288e80d9768

Observation 2b7cacaa-d361-4703-86d6-9fde7a04dd73 · outbound

This paper cites Contextual-relation consistent domain adaptation for semantic segmentation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Contextual-relation consistent domain adaptation for semantic segmentation,

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:34.048457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:23:23.031684Z digest=sha256:bc92aaa2ca1a44d95aedf156f072147ab956f3434689fb480fe3a9491bec0b55

Observation 6b9e06fb-3125-4960-bdc6-6abf1608caca · outbound

This paper cites Cscl: Critical semantic- consistent learning for unsupervised domain adaptation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Cscl: Critical semantic- consistent learning for unsupervised domain adaptation,

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:33.791211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:23:23.165456Z digest=sha256:3a2c4dae21927376f82b9133a8b6e725a99e2502c7348a99e9bed89414d2d29c

Observation d25c845a-da95-4892-b3c5-802c6a794ee6 · outbound

This paper cites Learning from scale-invariant examples for domain adaptation in semantic segmentation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Learning from scale-invariant examples for domain adaptation in semantic segmentation,

Reference 96

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:33.643766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:23:23.266980Z digest=sha256:c174be8e10c8de2c1a6ba9e6ba5c37ce320434c033e007b315f690ffdff341bf

Observation 9dca9ad7-0c57-4f6c-bb7b-47479e374dfb · outbound

This paper cites Classes matter: A fine-grained adversarial approach to cross-domain semantic segmentation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Classes matter: A fine-grained adversarial approach to cross-domain semantic segmentation,

Reference 97

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:33.394440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:23:23.388971Z digest=sha256:8e4c7df45f4421ba7c8503f5cafea9d65a0907bda1bd1451db7308aa585a3771

Observation bc42c79d-7a61-4789-9b98-676050187d55 · outbound

This paper cites Unsupervised intra- domain adaptation for semantic segmentation through self-supervision,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Unsupervised intra- domain adaptation for semantic segmentation through self-supervision,

Reference 98

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:33.093334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:23:23.493085Z digest=sha256:685e63b4804ecbee587a3e2b14d22057893016b8871ba765a770921316c00dd5

Observation e7522d86-50ae-4799-8e2a-6111e8bf5f30 · outbound

This paper cites Cross-domain semantic segmenta- tion via domain-invariant interactive relation transfer,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Cross-domain semantic segmenta- tion via domain-invariant interactive relation transfer,

Reference 99

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:32.791741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:23:23.629319Z digest=sha256:142b86b9d3e225856bb1f708a4d72b8b12684c332eb6695a4672035d7909bf18

Observation 79082ff3-4ca4-4ca1-9d93-0c9bb215b6be · outbound

This paper cites What can be transferred: Unsupervised domain adaptation for endoscopic lesions segmentation,.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation What can be transferred: Unsupervised domain adaptation for endoscopic lesions segmentation,

Reference 100

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:32.567992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T13:23:23.738084Z digest=sha256:e184a4b8194ad2f84523059015607a353e2b43cb514e6d4b57aeb9a26c005c97

Pith citing papers

No inbound Pith citation observations are available.