Paper Citation Record · LEDGER

Interpretable Zero-shot Learning with Infinite Class Concepts

As of 17 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2505.03361.

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

pith.paper-citation-record.v1
2505.03361 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:58:00.111855Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

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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

47 of 47 outbound references displayed

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External citation measurements

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Outbound references

Observation 3a7a64a0-84f1-4a86-99fc-942d3004161f · outbound

This paper cites GPT-4 Technical Report.

Interpretable Zero-shot Learning with Infinite Class Concepts GPT-4 Technical Report

Reference 1

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Observation 99d0b48f-b8fc-4dda-a663-18be6f3738db · outbound

This paper cites k-means++: The advantages of careful seeding.

Interpretable Zero-shot Learning with Infinite Class Concepts k-means++: The advantages of careful seeding

Reference 2

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Observation a54dc62d-5d8b-46f6-a040-8cb5df8faa40 · outbound

This paper cites Can we open the black box of ai? Nature News, 538(7623):20, 2016.

Interpretable Zero-shot Learning with Infinite Class Concepts Can we open the black box of ai? Nature News, 538(7623):20, 2016

Reference 3

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Observation 4a913dfa-43d9-4231-b778-38884573eab8 · outbound

This paper cites Transzero++: Cross attribute-guided transformer for zero-shot learning.

Interpretable Zero-shot Learning with Infinite Class Concepts Transzero++: Cross attribute-guided transformer for zero-shot learning

Reference 4

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Observation a29c04b0-a583-45fa-bb67-65565487780a · outbound

This paper cites Transzero: Attribute-guided transformer for zero-shot learning.

Interpretable Zero-shot Learning with Infinite Class Concepts Transzero: Attribute-guided transformer for zero-shot learning

Reference 5

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Observation 4b86c121-2c5f-4f17-9d31-c3f52b46dbf3 · outbound

This paper cites Evolving semantic prototype improves generative zero-shot learning.

Interpretable Zero-shot Learning with Infinite Class Concepts Evolving semantic prototype improves generative zero-shot learning

Reference 6

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Observation 91c24e28-d466-4e82-8c64-829446ac398e · outbound

This paper cites Progressive semantic- guided vision transformer for zero-shot learning.

Interpretable Zero-shot Learning with Infinite Class Concepts Progressive semantic- guided vision transformer for zero-shot learning

Reference 7

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Observation 71d1d0fb-e819-4347-82e1-1b436fd9a01c · outbound

This paper cites Hsva: Hierarchical semantic-visual adaptation for zero-shot learning.

Interpretable Zero-shot Learning with Infinite Class Concepts Hsva: Hierarchical semantic-visual adaptation for zero-shot learning

Reference 8

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This paper cites Duet: Cross-modal semantic grounding for contrastive zero-shot learning.

Interpretable Zero-shot Learning with Infinite Class Concepts Duet: Cross-modal semantic grounding for contrastive zero-shot learning

Reference 9

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Observation 5d63fd4d-8be7-4f6b-a48b-d132e6506251 · outbound

This paper cites Imagenet: A large- scale hierarchical image database.

Interpretable Zero-shot Learning with Infinite Class Concepts Imagenet: A large- scale hierarchical image database

Reference 10

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Observation 94aa1dcd-955e-4903-8b01-c9b853317b3f · outbound

This paper cites Detecting hallucinations in large language models using semantic entropy.

Interpretable Zero-shot Learning with Infinite Class Concepts Detecting hallucinations in large language models using semantic entropy

Reference 11

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Observation 5edd11f5-568c-400f-9aa2-29df28ae5ca0 · outbound

This paper cites Controlled Hallucinations: Learning to Generate Faithfully from Noisy Data.

Interpretable Zero-shot Learning with Infinite Class Concepts Controlled Hallucinations: Learning to Generate Faithfully from Noisy Data

Reference 12

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Observation 5904ce0a-5b2d-4bbd-9fb2-958a6473540e · outbound

This paper cites Visual-augmented dynamic semantic prototype for generative zero-shot learning.

Interpretable Zero-shot Learning with Infinite Class Concepts Visual-augmented dynamic semantic prototype for generative zero-shot learning

Reference 13

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Observation 86725fb5-f402-4960-92e0-2d0528ef9b66 · outbound

This paper cites Survey of hallucination in natural language generation.

Interpretable Zero-shot Learning with Infinite Class Concepts Survey of hallucination in natural language generation

Reference 14

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Observation 639ab8b8-3ab8-479f-bc0b-e62cab76c6c7 · outbound

This paper cites Evaluating open-domain question answering in the era of large language models.

Interpretable Zero-shot Learning with Infinite Class Concepts Evaluating open-domain question answering in the era of large language models

Reference 15

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Observation 42036427-6d88-486a-8dca-4255197fc026 · outbound

This paper cites Goal- oriented gaze estimation for zero-shot learning.

Interpretable Zero-shot Learning with Infinite Class Concepts Goal- oriented gaze estimation for zero-shot learning

Reference 16

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Observation 45bfc418-280d-433b-80a6-2aeb18014d42 · outbound

This paper cites On Faithfulness and Factuality in Abstractive Summarization.

Interpretable Zero-shot Learning with Infinite Class Concepts On Faithfulness and Factuality in Abstractive Summarization

Reference 17

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Observation cc23be94-f5e7-4801-980c-bb4b1be43505 · outbound

This paper cites Distributed repre- sentations of words and phrases and their compositionality.

Interpretable Zero-shot Learning with Infinite Class Concepts Distributed repre- sentations of words and phrases and their compositionality

Reference 18

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This paper cites Domain-aware visual bias eliminating for generalized zero-shot learning.

Interpretable Zero-shot Learning with Infinite Class Concepts Domain-aware visual bias eliminating for generalized zero-shot learning

Reference 19

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This paper cites I2mvformer: Large language model generated multi-view document supervision for zero-shot image classification.

Interpretable Zero-shot Learning with Infinite Class Concepts I2mvformer: Large language model generated multi-view document supervision for zero-shot image classification

Reference 20

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Observation 83f8ef5a-ee06-425b-8720-6c531cc09b33 · outbound

This paper cites I2dformer: Learning image to document attention for zero-shot image classification.

Interpretable Zero-shot Learning with Infinite Class Concepts I2dformer: Learning image to document attention for zero-shot image classification

Reference 21

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Observation ba8eb47b-a803-4075-bb2d-b6ab424fc7a5 · outbound

This paper cites Sun attribute database: Discovering, annotating, and recognizing scene attributes.

Interpretable Zero-shot Learning with Infinite Class Concepts Sun attribute database: Discovering, annotating, and recognizing scene attributes

Reference 22

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This paper cites The human imagination: the cognitive neuroscience of visual mental imagery.

Interpretable Zero-shot Learning with Infinite Class Concepts The human imagination: the cognitive neuroscience of visual mental imagery

Reference 23

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This paper cites Glove: Global vectors for word representation.

Interpretable Zero-shot Learning with Infinite Class Concepts Glove: Global vectors for word representation

Reference 24

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This paper cites Less is more: zero-shot learning from online textual documents with noise suppression.

Interpretable Zero-shot Learning with Infinite Class Concepts Less is more: zero-shot learning from online textual documents with noise suppression

Reference 25

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This paper cites Visual-semantic decomposition and partial alignment for document-based zero-shot learning.

Interpretable Zero-shot Learning with Infinite Class Concepts Visual-semantic decomposition and partial alignment for document-based zero-shot learning

Reference 26

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This paper cites Learning transferable visual models from natural language supervision.

Interpretable Zero-shot Learning with Infinite Class Concepts Learning transferable visual models from natural language supervision

Reference 27

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This paper cites Generating descriptions with grounded and co-referenced people.

Interpretable Zero-shot Learning with Infinite Class Concepts Generating descriptions with grounded and co-referenced people

Reference 28

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This paper cites Term-weighting approaches in automatic text retrieval.

Interpretable Zero-shot Learning with Infinite Class Concepts Term-weighting approaches in automatic text retrieval

Reference 29

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This paper cites Reinforcement learning from human feedback: Progress and challenges.

Interpretable Zero-shot Learning with Infinite Class Concepts Reinforcement learning from human feedback: Progress and challenges

Reference 30

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This paper cites Incremental residual concept bottleneck models.

Interpretable Zero-shot Learning with Infinite Class Concepts Incremental residual concept bottleneck models

Reference 31

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This paper cites Selective zero-shot classification with augmented attributes.

Interpretable Zero-shot Learning with Infinite Class Concepts Selective zero-shot classification with augmented attributes

Reference 32

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This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Interpretable Zero-shot Learning with Infinite Class Concepts Gemini: A Family of Highly Capable Multimodal Models

Reference 33

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This paper cites The caltech-ucsd birds-200-2011 dataset.

Interpretable Zero-shot Learning with Infinite Class Concepts The caltech-ucsd birds-200-2011 dataset

Reference 34

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This paper cites Chain-of-thought prompting elicits reasoning in large language models.

Interpretable Zero-shot Learning with Infinite Class Concepts Chain-of-thought prompting elicits reasoning in large language models

Reference 35

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This paper cites Zero-shot learning—a comprehensive evaluation of the good, the bad and the ugly.

Interpretable Zero-shot Learning with Infinite Class Concepts Zero-shot learning—a comprehensive evaluation of the good, the bad and the ugly

Reference 36

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This paper cites Feature generating networks for zero-shot learning.

Interpretable Zero-shot Learning with Infinite Class Concepts Feature generating networks for zero-shot learning

Reference 37

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This paper cites On hallucination and predictive uncertainty in conditional language generation.

Interpretable Zero-shot Learning with Infinite Class Concepts On hallucination and predictive uncertainty in conditional language generation

Reference 38

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This paper cites Attribute prototype network for zero-shot learning.

Interpretable Zero-shot Learning with Infinite Class Concepts Attribute prototype network for zero-shot learning

Reference 39

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This paper cites Vgse: Visually- grounded semantic embeddings for zero-shot learning.

Interpretable Zero-shot Learning with Infinite Class Concepts Vgse: Visually- grounded semantic embeddings for zero-shot learning

Reference 40

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Observation 6cc6a6d8-e5ff-4e70-88b7-12783fe95326 · outbound

This paper cites Language in a bottle: Language model guided concept bottlenecks for interpretable image classification.

Interpretable Zero-shot Learning with Infinite Class Concepts Language in a bottle: Language model guided concept bottlenecks for interpretable image classification

Reference 41

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This paper cites ZeroDiff: Solidified Visual-Semantic Correlation in Zero-Shot Learning.

Interpretable Zero-shot Learning with Infinite Class Concepts ZeroDiff: Solidified Visual-Semantic Correlation in Zero-Shot Learning

Reference 42

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This paper cites Rebalanced zero-shot learning.

Interpretable Zero-shot Learning with Infinite Class Concepts Rebalanced zero-shot learning

Reference 43

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Interpretable Zero-shot Learning with Infinite Class Concepts Designing category-level attributes for discriminative visual recognition

Reference 44

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This paper cites Benchmarking large language models for news summarization.

Interpretable Zero-shot Learning with Infinite Class Concepts Benchmarking large language models for news summarization

Reference 45

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This paper cites Grounded video description.

Interpretable Zero-shot Learning with Infinite Class Concepts Grounded video description

Reference 46

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This paper cites Inference.

Interpretable Zero-shot Learning with Infinite Class Concepts Inference

Reference 47

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Source-reported events for the cited work

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Pith citing papers

No inbound Pith citation observations are available.