The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning | Paper Citation Record

Observation b3bc631b-bfac-45f9-928e-1c8743aca8ba · outbound

This paper cites Multi-Label Learning from Single Positive Labels.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Multi-Label Learning from Single Positive Labels

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-05T14:00:29.689840Z

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This paper cites A survey of robust adversarial training in pattern recognition: Fundamental, theory, and methodologies,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning A survey of robust adversarial training in pattern recognition: Fundamental, theory, and methodologies,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:00:36.724724Z

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This paper cites Explaining and Harnessing Adversarial Examples.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Explaining and Harnessing Adversarial Examples

Reference 3

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This paper cites Towards Deep Learning Models Resistant to Adversarial Attacks.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 4

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This paper cites Generative adversarial nets,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Generative adversarial nets,

Reference 5

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This paper cites Gandef: A gan based adversarial training defense for neural network classifier,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Gandef: A gan based adversarial training defense for neural network classifier,

Reference 6

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This paper cites Denoising diffusion probabilistic models,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Denoising diffusion probabilistic models,

Reference 7

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This paper cites Weakly supervised multi-label learning via label enhancement.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Weakly supervised multi-label learning via label enhancement

Reference 8

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Observation eb0fced3-2392-449b-854f-e64658ab683e · outbound

This paper cites Multi-label learning from single positive labels,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Multi-label learning from single positive labels,

Reference 9

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This paper cites When does label smoothing help?.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning When does label smoothing help?

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:00:36.106608Z

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This paper cites Simple and Robust Loss Design for Multi-Label Learning with Missing Labels.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Simple and Robust Loss Design for Multi-Label Learning with Missing Labels

Reference 11

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This paper cites Large loss matters in weakly supervised multi-label classification,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Large loss matters in weakly supervised multi-label classification,

Reference 12

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This paper cites Bridging the gap between model explanations in partially annotated multi-label classification,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Bridging the gap between model explanations in partially annotated multi-label classification,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:00:35.781148Z

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Observation fe4af609-53e3-4c13-8ebf-81d4d64da884 · outbound

This paper cites Exploring structured semantic prior for multi label recognition with incomplete labels,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Exploring structured semantic prior for multi label recognition with incomplete labels,

Reference 14

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This paper cites Revisiting pseudo-label for single- positive multi-label learning,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Revisiting pseudo-label for single- positive multi-label learning,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:00:35.462034Z

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This paper cites Hierarchical prompt learning using clip for multi-label classification with single positive labels,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Hierarchical prompt learning using clip for multi-label classification with single positive labels,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:00:35.316036Z

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This paper cites Clipsitu: Effectively leveraging clip for conditional predictions in situation recognition,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Clipsitu: Effectively leveraging clip for conditional predictions in situation recognition,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:00:35.137717Z

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This paper cites Clip-event: Connecting text and images with event structures,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Clip-event: Connecting text and images with event structures,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:00:34.936670Z

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Observation a0af5346-40a3-41f0-bc98-dcecb3eba770 · outbound

This paper cites Recurrent models for situation recognition,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Recurrent models for situation recognition,

Reference 19

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This paper cites Situation recognition with graph neural networks,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Situation recognition with graph neural networks,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:00:34.367688Z

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This paper cites Mixture-kernel graph attention network for situation recognition,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Mixture-kernel graph attention network for situation recognition,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:00:34.166410Z

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This paper cites Attention-based context aware reasoning for situation recognition,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Attention-based context aware reasoning for situation recognition,

Reference 22

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This paper cites Collaborative transformers for grounded situation recognition,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Collaborative transformers for grounded situation recognition,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:00:33.654292Z

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This paper cites Ambiguous images with human judgments for robust visual event classification,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Ambiguous images with human judgments for robust visual event classification,

Reference 24

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This paper cites Situation recognition: Visual semantic role labeling for image understanding,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Situation recognition: Visual semantic role labeling for image understanding,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:00:33.232424Z

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Observation f51a0f79-625b-46e6-b489-b8f1558be31f · outbound

This paper cites Grounded situation recognition,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Grounded situation recognition,

Reference 26

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This paper cites an unresolved cited work.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Unresolved cited work

Reference 27

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This paper cites Grounded Situation Recognition with Transformers.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Grounded Situation Recognition with Transformers

Reference 28

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This paper cites Visualizing data using t-sne.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Visualizing data using t-sne

Reference 29

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This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Semi-Supervised Classification with Graph Convolutional Networks

Reference 30

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

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Learning transferable visual models from natural language supervision,

Reference 31

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This paper cites The framenet database and software tools.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning The framenet database and software tools

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:00:32.252720Z

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This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 33

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This paper cites Focal loss for dense object detection,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Focal loss for dense object detection,

Reference 34

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This paper cites Learning deep features for discriminative localization,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Learning deep features for discriminative localization,

Reference 35

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Observation acabd923-a3ed-412d-b848-3f91743aac51 · outbound

This paper cites The cityscapes dataset for semantic urban scene understanding,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning The cityscapes dataset for semantic urban scene understanding,

Reference 36

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This paper cites Activitynet: A large-scale video benchmark for human activity under- standing,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Activitynet: A large-scale video benchmark for human activity under- standing,

Reference 37

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This paper cites A survey on deep learning-driven remote sensing image scene understanding: Scene classification, scene retrieval and scene-guided object detection,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning A survey on deep learning-driven remote sensing image scene understanding: Scene classification, scene retrieval and scene-guided object detection,

Reference 38

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This paper cites Learning and understanding dynamic scene activity: a review,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Learning and understanding dynamic scene activity: a review,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:00:31.164875Z

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This paper cites Acknowledging the unknown for multi-label learning with single positive labels,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Acknowledging the unknown for multi-label learning with single positive labels,

Reference 40

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This paper cites One positive label is sufficient: Single-positive multi-label learning with label enhance- ment,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning One positive label is sufficient: Single-positive multi-label learning with label enhance- ment,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:00:30.632068Z

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This paper cites Qwen2.5-VL Technical Report.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Qwen2.5-VL Technical Report

Reference 42

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This paper cites DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding

Reference 43

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This paper cites Deepseek-v3 technical report,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Deepseek-v3 technical report,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:00:30.323236Z

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This paper cites Co-pseudo labeling and active selection for fundus single-positive multi-label learning,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Co-pseudo labeling and active selection for fundus single-positive multi-label learning,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:00:29.943608Z

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Observation eaecc5f3-beec-4f6c-9783-53e8c9bd079b · outbound

This paper cites Semantic-guided Representation Learning for Multi-Label Recognition.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Semantic-guided Representation Learning for Multi-Label Recognition

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-08-05T14:00:29.188657Z

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Observation 48e8089d-8b49-4bff-a60d-ec15099a1401 · outbound

This paper cites Splicemix: A cross-scale and semantic blending augmentation strategy for multi-label image classification,.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning Splicemix: A cross-scale and semantic blending augmentation strategy for multi-label image classification,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:00:29.825348Z

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Observation 5c5c8a58-0add-4302-af60-35d174c29280 · outbound

This paper cites DeepSeek-V3 Technical Report.

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning DeepSeek-V3 Technical Report

Reference 2025

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