Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions | Paper Citation Record

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This paper cites Society of mind.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Society of mind

Reference 1

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Observation 83c82526-bf1a-4ee5-a186-383f493b7c67 · outbound

This paper cites Emotion recognition in human-computer interaction.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Emotion recognition in human-computer interaction

Reference 2

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This paper cites An overview of emotion in artificial intelligence.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions An overview of emotion in artificial intelligence

Reference 3

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This paper cites Deep facial expression recognition: A survey.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Deep facial expression recognition: A survey

Reference 4

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This paper cites A survey on facial emotion recognition techniques: A state-of-the-art literature review.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions A survey on facial emotion recognition techniques: A state-of-the-art literature review

Reference 5

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Observation a0818c7a-b929-4123-a7ab-abe8debb2fcc · outbound

This paper cites Understanding deep learning techniques for recognition of human emotions using facial expressions: A comprehensive survey.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Understanding deep learning techniques for recognition of human emotions using facial expressions: A comprehensive survey

Reference 6

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This paper cites Facial micro-expressions: An overview.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Facial micro-expressions: An overview

Reference 7

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This paper cites A model of the perception of facial expressions of emotion by humans: Research overview and perspectives.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions A model of the perception of facial expressions of emotion by humans: Research overview and perspectives

Reference 8

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This paper cites Deep learning for human affect recognition: Insights and new developments.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Deep learning for human affect recognition: Insights and new developments

Reference 9

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This paper cites A review of affective computing: From unimodal analysis to multimodal fusion.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions A review of affective computing: From unimodal analysis to multimodal fusion

Reference 10

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Observation a13612c8-151f-425a-bf05-fd6c844a98a8 · outbound

This paper cites An argument for basic emotions.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions An argument for basic emotions

Reference 11

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This paper cites A circumplex model of affect.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions A circumplex model of affect

Reference 12

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Observation b75452e2-5d5f-492f-b21f-126db4a70919 · outbound

This paper cites OV-MER: Towards Open-Vocabulary Multimodal Emotion Recognition.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions OV-MER: Towards Open-Vocabulary Multimodal Emotion Recognition

Reference 13

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Observation 8450f0b3-3ee7-4861-a546-d95f9703d13b · outbound

This paper cites GPT-4o System Card.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions GPT-4o System Card

Reference 14

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This paper cites Self-report captures 27 distinct categories of emotion bridged by continuous gradients.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Self-report captures 27 distinct categories of emotion bridged by continuous gradients

Reference 15

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Observation 8e58cf6f-20f1-4b0b-bed8-4ba023332c5e · outbound

This paper cites The language of emotion.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions The language of emotion

Reference 16

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This paper cites The role of language in emotion: Predictions from psychological constructionism.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions The role of language in emotion: Predictions from psychological constructionism

Reference 17

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This paper cites Describe your facial expressions by linking image encoders and large language models.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Describe your facial expressions by linking image encoders and large language models

Reference 18

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This paper cites Facial affective behavior analysis with instruction tuning.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Facial affective behavior analysis with instruction tuning

Reference 19

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

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Learning transferable visual models from natural language supervision

Reference 20

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This paper cites Emoclip: A vision-language method for zero-shot video facial expression recognition.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Emoclip: A vision-language method for zero-shot video facial expression recognition

Reference 21

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Observation 63b2af78-2d5c-48e6-a36e-d6e31ff541ff · outbound

This paper cites Flip-80m: 80 million visual-linguistic pairs for facial language-image pre-training.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Flip-80m: 80 million visual-linguistic pairs for facial language-image pre-training

Reference 22

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Observation af6ee1a3-6628-434e-8d7d-7bacdc929a0f · outbound

This paper cites Enhancing zero-shot facial expression recognition by llm knowledge transfer.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Enhancing zero-shot facial expression recognition by llm knowledge transfer

Reference 23

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This paper cites Facexbench: Evaluating multimodal llms on face understanding.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Facexbench: Evaluating multimodal llms on face understanding

Reference 24

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This paper cites Face-human-bench: A comprehensive benchmark of face and human understanding for multi-modal assistants.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Face-human-bench: A comprehensive benchmark of face and human understanding for multi-modal assistants

Reference 25

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This paper cites Gpt-4v with emotion: A zero-shot benchmark for generalized emotion recognition.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Gpt-4v with emotion: A zero-shot benchmark for generalized emotion recognition

Reference 26

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This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 27

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This paper cites Occlusion aware facial expression recognition using cnn with attention mechanism.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Occlusion aware facial expression recognition using cnn with attention mechanism

Reference 28

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This paper cites Region attention networks for pose and occlusion robust facial expression recognition.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Region attention networks for pose and occlusion robust facial expression recognition

Reference 29

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This paper cites Learning deep global multi-scale and local attention features for facial expression recognition in the wild.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Learning deep global multi-scale and local attention features for facial expression recognition in the wild

Reference 30

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This paper cites Robust lightweight facial expression recognition network with label distribution training.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Robust lightweight facial expression recognition network with label distribution training

Reference 31

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This paper cites Facial expression recognition with visual transformers and attentional selective fusion.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Facial expression recognition with visual transformers and attentional selective fusion

Reference 32

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This paper cites Transfer: Learning relation-aware facial expression representations with transformers.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Transfer: Learning relation-aware facial expression representations with transformers

Reference 33

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This paper cites Poster: A pyramid cross-fusion transformer network for facial expression recognition.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Poster: A pyramid cross-fusion transformer network for facial expression recognition

Reference 34

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This paper cites Svfap: Self-supervised video facial affect perceiver.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Svfap: Self-supervised video facial affect perceiver

Reference 35

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This paper cites Poster++: A simpler and stronger facial expression recognition network.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Poster++: A simpler and stronger facial expression recognition network

Reference 36

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This paper cites Reliable crowdsourcing and deep locality-preserving learning for expression recognition in the wild.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Reliable crowdsourcing and deep locality-preserving learning for expression recognition in the wild

Reference 37

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This paper cites Suppressing uncertainties for large-scale facial expression recognition.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Suppressing uncertainties for large-scale facial expression recognition

Reference 38

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This paper cites Relative uncertainty learning for facial expression recognition.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Relative uncertainty learning for facial expression recognition

Reference 39

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This paper cites Learning emotion representations from verbal and nonverbal communication.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Learning emotion representations from verbal and nonverbal communication

Reference 40

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This paper cites Collecting large, richly annotated facial-expression databases from movies.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Collecting large, richly annotated facial-expression databases from movies

Reference 41

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This paper cites Training deep networks for facial expression recognition with crowd-sourced label distribution.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Training deep networks for facial expression recognition with crowd-sourced label distribution

Reference 42

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Observation d9730ec3-50fe-4659-b3d4-074cc7ab87f4 · outbound

This paper cites Affectnet: A database for facial expression, valence, and arousal computing in the wild.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Affectnet: A database for facial expression, valence, and arousal computing in the wild

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:28.825975Z

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Observation 2b92e18b-5709-42bd-8711-922081a8989c · outbound

This paper cites Dfew: A large-scale database for recognizing dynamic facial expressions in the wild.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Dfew: A large-scale database for recognizing dynamic facial expressions in the wild

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:28.810550Z

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This paper cites Mafw: A large-scale, multi-modal, compound affective database for dynamic facial expression recognition in the wild.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Mafw: A large-scale, multi-modal, compound affective database for dynamic facial expression recognition in the wild

Reference 45

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This paper cites Ferv39k: A large-scale multi-scene dataset for facial expression recognition in videos.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Ferv39k: A large-scale multi-scene dataset for facial expression recognition in videos

Reference 46

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Observation a6b0f5c3-de36-4929-8dee-e00c386c8737 · outbound

This paper cites Aff-Wild2: Extending the Aff-Wild Database for Affect Recognition.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Aff-Wild2: Extending the Aff-Wild Database for Affect Recognition

Reference 47

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This paper cites Deep affect prediction in-the-wild: Aff-wild database and challenge, deep architectures, and beyond.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Deep affect prediction in-the-wild: Aff-wild database and challenge, deep architectures, and beyond

Reference 48

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Observation 68a872fe-c5e7-4beb-b4dc-a0bd6f360814 · outbound

This paper cites Compound facial expressions of emotion.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Compound facial expressions of emotion

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:28.742804Z

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This paper cites Configural information in facial expression perception.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Configural information in facial expression perception

Reference 50

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Observation 9c4b2c25-bfde-4039-a2a1-ca4eb145d015 · outbound

This paper cites Parts and wholes in expression recognition.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Parts and wholes in expression recognition

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:28.712447Z

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This paper cites Mixed emotions: Holistic and analytic perception of facial expressions.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Mixed emotions: Holistic and analytic perception of facial expressions

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:28.696994Z

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Observation c168dbc8-1d94-4a55-baaf-e90bf4d73d38 · outbound

This paper cites The role of facial movements in emotion recognition.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions The role of facial movements in emotion recognition

Reference 53

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Observation cc17857f-4354-4c3a-afae-b0d9837b3146 · outbound

This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 54

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This paper cites Scaling up visual and vision-language representation learning with noisy text supervision.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Scaling up visual and vision-language representation learning with noisy text supervision

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Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Reproducible scaling laws for contrastive language-image learning

Reference 56

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Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Sigmoid loss for language image pre-training

Reference 57

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Observation a58c779b-930f-4c26-a463-bf3d2c91a56a · outbound

This paper cites EVA-CLIP: Improved Training Techniques for CLIP at Scale.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions EVA-CLIP: Improved Training Techniques for CLIP at Scale

Reference 58

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Observation e367f1a0-e1a6-41ea-b20d-c15f86c97ebf · outbound

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Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Demystifying clip data

Reference 59

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Observation 296cdcf5-98d0-4dd3-a98d-6a1461eba2ee · outbound

This paper cites Dreamlip: Language-image pre-training with long captions.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Dreamlip: Language-image pre-training with long captions

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:28.605700Z

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This paper cites Modeling Caption Diversity in Contrastive Vision-Language Pretraining.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Modeling Caption Diversity in Contrastive Vision-Language Pretraining

Reference 61

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Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Improving fine-grained understand- ing in image-text pre-training

Reference 62

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Observation 2a162f3a-c265-4461-bf56-c969dce59c59 · outbound

This paper cites General facial representation learning in a visual-linguistic manner.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions General facial representation learning in a visual-linguistic manner

Reference 63

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This paper cites GPT-4 Technical Report.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions GPT-4 Technical Report

Reference 64

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This paper cites Visual instruction tuning.Advances in neural information processing systems, 36:34892–34916, 2023.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Visual instruction tuning.Advances in neural information processing systems, 36:34892–34916, 2023

Reference 65

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Observation 18510aaf-16b3-425d-8e0a-92146c5d651d · outbound

This paper cites Minigpt-4: Enhancing vision-language understanding with advanced large language models.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Minigpt-4: Enhancing vision-language understanding with advanced large language models

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:28.553765Z

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Observation a7fe66eb-2834-4485-abe6-a6200aecf3bf · outbound

This paper cites Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks

Reference 67

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Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Qwen Technical Report

Reference 68

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Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Expllm: Towards chain of thought for facial expression recognition

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:28.527127Z

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Observation 91706ae5-009f-4165-9389-758e3f05e0f2 · outbound

This paper cites EMO-LLaMA: Enhancing Facial Emotion Understanding with Instruction Tuning.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions EMO-LLaMA: Enhancing Facial Emotion Understanding with Instruction Tuning

Reference 70

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Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Emotion-llama: Multimodal emotion recognition and reasoning with instruction tuning

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:28.510694Z

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This paper cites AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models

Reference 72

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This paper cites R1-Omni: Explainable Omni-Multimodal Emotion Recognition with Reinforcement Learning.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions R1-Omni: Explainable Omni-Multimodal Emotion Recognition with Reinforcement Learning

Reference 73

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Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Generative adversarial network for text-to-face synthesis and manipulation with pretrained bert model

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:28.493528Z

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Observation d620aab3-8df8-4240-bf39-ae514f932d14 · outbound

This paper cites Tedigan: Text-guided diverse face image generation and manipulation.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Tedigan: Text-guided diverse face image generation and manipulation

Reference 75

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This paper cites Talk-to-edit: Fine-grained facial editing via dialog.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Talk-to-edit: Fine-grained facial editing via dialog

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:28.463190Z

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This paper cites 15M Multimodal Facial Image-Text Dataset.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions 15M Multimodal Facial Image-Text Dataset

Reference 77

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This paper cites Computational Analysis of Stress, Depression and Engagement in Mental Health: A Survey.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Computational Analysis of Stress, Depression and Engagement in Mental Health: A Survey

Reference 78

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This paper cites Recognizing emotion from facial expressions: psychological and neurological mechanisms.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Recognizing emotion from facial expressions: psychological and neurological mechanisms

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:28.447457Z

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Observation c4942f20-be8d-43ad-9381-17fd57fdd3f2 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 80

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This paper cites Attention is all you need.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Attention is all you need

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-06T13:07:27.641491Z

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Observation 316b960e-eb7b-47f3-b8bd-6f6fc7c5b4d3 · outbound

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Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Facial action coding system

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:28.420990Z

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Observation 00c31e87-2361-43ec-9cb8-440841c6c4aa · outbound

This paper cites Softclip: Softer cross-modal alignment makes clip stronger.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Softclip: Softer cross-modal alignment makes clip stronger

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:28.404940Z

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This paper cites Cwcl: Cross-modal transfer with continuously weighted contrastive loss.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Cwcl: Cross-modal transfer with continuously weighted contrastive loss

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:28.388027Z

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Observation c7333be1-82c7-4c11-ab1e-5c7e57932a2d · outbound

This paper cites Generalizable facial expression recognition.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Generalizable facial expression recognition

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:28.371188Z

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This paper cites Flava: A foundational language and vision alignment model.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Flava: A foundational language and vision alignment model

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:28.351256Z

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Observation 37e65246-652e-4bcb-92b5-e08e324a1669 · outbound

This paper cites Face-MLLM: A Large Face Perception Model.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Face-MLLM: A Large Face Perception Model

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-06T13:07:27.675297Z

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Observation 38ee7e1c-45b8-44fe-a6f2-2dbb1596612e · outbound

This paper cites SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-06T13:07:27.680305Z

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Unavailable: canonical work link unavailable.

Observation 4d20077b-717a-4e68-84af-bfacd77fd4f5 · outbound

This paper cites Learn from all: Erasing attention consistency for noisy label facial expression recognition.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Learn from all: Erasing attention consistency for noisy label facial expression recognition

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:28.333222Z

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Observation 0c7ce87b-05cb-44d0-a49c-09dfc5bd7168 · outbound

This paper cites Latent-ofer: Detect, mask, and reconstruct with latent vectors for occluded facial expression recognition.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Latent-ofer: Detect, mask, and reconstruct with latent vectors for occluded facial expression recognition

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:28.314024Z

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Observation 0ddd7f09-5bdb-4044-92eb-3384ca30156a · outbound

This paper cites From static to dynamic: Adapting landmark-aware image models for facial expression recognition in videos.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions From static to dynamic: Adapting landmark-aware image models for facial expression recognition in videos

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:28.295881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 84411ab7-998a-4dea-b93e-156964029dea · outbound

This paper cites Videoclip: Contrastive pre-training for zero-shot video-text understanding.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Videoclip: Contrastive pre-training for zero-shot video-text understanding

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:28.277285Z

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Observation bb9fa76a-8359-49e1-a6b9-59488c37731a · outbound

This paper cites Expanding language-image pretrained models for general video recognition.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Expanding language-image pretrained models for general video recognition

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:28.261598Z

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Observation 30c11dac-bc73-4cf0-8cae-94b246a1bbc4 · outbound

This paper cites Learning to prompt for vision-language models.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions Learning to prompt for vision-language models

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:28.243764Z

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