When LLMs Team Up: The Emergence of Collaborative Affective Computing | Paper Citation Record

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This paper cites Toward machine emotional intelligence: Analysis of affective physiological state,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Toward machine emotional intelligence: Analysis of affective physiological state,

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This paper cites A circumplex model of affect.

When LLMs Team Up: The Emergence of Collaborative Affective Computing A circumplex model of affect

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This paper cites Defining affect in relation to cognition: A re- sponse to susan mcleod,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Defining affect in relation to cognition: A re- sponse to susan mcleod,

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This paper cites Editorial: The social nature of emotions,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Editorial: The social nature of emotions,

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This paper cites Affective computing and sentiment analysis,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Affective computing and sentiment analysis,

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This paper cites A systematic review on affective computing: emotion models, databases, and recent advances,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing A systematic review on affective computing: emotion models, databases, and recent advances,

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This paper cites A comprehensive survey on affective computing: Challenges, trends, applications, and future directions,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing A comprehensive survey on affective computing: Challenges, trends, applications, and future directions,

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This paper cites Affective computing: A review,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Affective computing: A review,

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This paper cites A survey of autonomous human affect detection methods for social robots engaged in natural hri,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing A survey of autonomous human affect detection methods for social robots engaged in natural hri,

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This paper cites The affect dilemma for artificial agents: Should we develop affective artificial agents?.

When LLMs Team Up: The Emergence of Collaborative Affective Computing The affect dilemma for artificial agents: Should we develop affective artificial agents?

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This paper cites Affective computing in the era of large language models: A survey from the nlp perspective,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Affective computing in the era of large language models: A survey from the nlp perspective,

Reference 12

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This paper cites Is chatgpt equipped with emotional dialogue capabilities?.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Is chatgpt equipped with emotional dialogue capabilities?

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This paper cites Affective computing: Recent advances, challenges, and future trends,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Affective computing: Recent advances, challenges, and future trends,

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This paper cites Rvisa: Reasoning and verifica- tion for implicit sentiment analysis,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Rvisa: Reasoning and verifica- tion for implicit sentiment analysis,

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This paper cites Sentiment analysis in the era of large language models: A reality check,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Sentiment analysis in the era of large language models: A reality check,

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This paper cites A wide evaluation of chatgpt on affective computing tasks,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing A wide evaluation of chatgpt on affective computing tasks,

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This paper cites New approach in quantification of emotional intensity from the speech signal: emotional temperature,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing New approach in quantification of emotional intensity from the speech signal: emotional temperature,

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This paper cites CEM: commonsense-aware empathetic response generation,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing CEM: commonsense-aware empathetic response generation,

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This paper cites Emotion-aware and intent-controlled empathetic response generation using hierarchical transformer network,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Emotion-aware and intent-controlled empathetic response generation using hierarchical transformer network,

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This paper cites Sequential models for sentiment analysis: A comparative study,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Sequential models for sentiment analysis: A comparative study,

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This paper cites Empmff: A multi-factor sequence fusion framework for empathetic re- sponse generation,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Empmff: A multi-factor sequence fusion framework for empathetic re- sponse generation,

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This paper cites Control globally, understand locally: A global-to-local hierarchical graph network for emotional support conversation,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Control globally, understand locally: A global-to-local hierarchical graph network for emotional support conversation,

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This paper cites Towards empathetic open-domain conversation models: A new benchmark and dataset,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Towards empathetic open-domain conversation models: A new benchmark and dataset,

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This paper cites Empathetic dialogue generation via sensitive emotion recogni- tion and sensible knowledge selection,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Empathetic dialogue generation via sensitive emotion recogni- tion and sensible knowledge selection,

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This paper cites Large language models are zero-shot reasoners,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Large language models are zero-shot reasoners,

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When LLMs Team Up: The Emergence of Collaborative Affective Computing Finetuned language models are zero- shot learners,

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This paper cites Unifiedabsa: A unified absa frame- work based on multi-task instruction tuning,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Unifiedabsa: A unified absa frame- work based on multi-task instruction tuning,

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This paper cites UniMSE: Towards unified multimodal sentiment analysis and emotion recognition,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing UniMSE: Towards unified multimodal sentiment analysis and emotion recognition,

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When LLMs Team Up: The Emergence of Collaborative Affective Computing LEGO-ABSA: A prompt-based task assemblable unified genera- tive framework for multi-task aspect-based sentiment analysis,

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When LLMs Team Up: The Emergence of Collaborative Affective Computing Self-refine: Iterative refinement with self-feedback,

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This paper cites When can llms Actually correct their own mistakes? A critical survey of self- correction of llms,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing When can llms Actually correct their own mistakes? A critical survey of self- correction of llms,

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When LLMs Team Up: The Emergence of Collaborative Affective Computing Can large language model agents simulate human trust behavior?

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When LLMs Team Up: The Emergence of Collaborative Affective Computing Multi-agent collaboration mechanisms: A survey of llms,

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When LLMs Team Up: The Emergence of Collaborative Affective Computing Towards measuring and modeling

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When LLMs Team Up: The Emergence of Collaborative Affective Computing Culturellm: Incorporating cultural differences into large language models,

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When LLMs Team Up: The Emergence of Collaborative Affective Computing Siren’s song in the ai ocean: A survey on hallucination in large language models,

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When LLMs Team Up: The Emergence of Collaborative Affective Computing A survey on the honesty of large language models,

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This paper cites Kahneman, Thinking, fast and slow.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Kahneman, Thinking, fast and slow

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When LLMs Team Up: The Emergence of Collaborative Affective Computing Collaborative intelligence: A scoping review of current appli- cations,

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When LLMs Team Up: The Emergence of Collaborative Affective Computing Ai and the future of collaborative work: Group ideation with an llm in a virtual canvas,

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When LLMs Team Up: The Emergence of Collaborative Affective Computing Collaborative ai in sentiment analysis: System architecture, data prediction and deployment strategies,

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When LLMs Team Up: The Emergence of Collaborative Affective Computing What is the role of small models in the llm era: A survey,

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When LLMs Team Up: The Emergence of Collaborative Affective Computing A comprehensive survey of small language models in the era of large language models: Techniques, enhancements, applications, collaboration with llms, and trustworthiness,

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When LLMs Team Up: The Emergence of Collaborative Affective Computing Marcus, W

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When LLMs Team Up: The Emergence of Collaborative Affective Computing Enhancing empathetic response generation by augmenting llms with small-scale empathetic models,

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When LLMs Team Up: The Emergence of Collaborative Affective Computing Artificial social intelligence in teamwork: How team traits influence human-ai dynamics in complex tasks

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When LLMs Team Up: The Emergence of Collaborative Affective Computing A survey on llm-based multi-agent systems: workflow, infrastructure, and challenges,

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When LLMs Team Up: The Emergence of Collaborative Affective Computing Large language model based multi- agents: A survey of progress and challenges,

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This paper cites Can small language models help large language models reason better?: LM-guided chain-of-thought,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Can small language models help large language models reason better?: LM-guided chain-of-thought,

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When LLMs Team Up: The Emergence of Collaborative Affective Computing Survey on sentiment analysis: evolution of research methods and topics,

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When LLMs Team Up: The Emergence of Collaborative Affective Computing Multimodal sentiment analysis: A survey of methods, trends, and challenges,

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When LLMs Team Up: The Emergence of Collaborative Affective Computing A survey on aspect-based sentiment analysis: Tasks, methods, and chal- lenges,

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When LLMs Team Up: The Emergence of Collaborative Affective Computing Sentiment analysis through llm negotiations,

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This paper cites Large language models performance comparison of emotion and sentiment classification,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Large language models performance comparison of emotion and sentiment classification,

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When LLMs Team Up: The Emergence of Collaborative Affective Computing Mvp: Multi-view prompting improves aspect sentiment tuple prediction,

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When LLMs Team Up: The Emergence of Collaborative Affective Computing Star: Stepwise task augmenta- tion and relation learning for aspect sentiment quad prediction,

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When LLMs Team Up: The Emergence of Collaborative Affective Computing Instructabsa: Instruction learning for aspect based sentiment analysis,

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When LLMs Team Up: The Emergence of Collaborative Affective Computing Aspect-based senti- ment analysis using bert,

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This paper cites WRIME: A new dataset for emotional intensity estimation with subjective and objective annotations,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing WRIME: A new dataset for emotional intensity estimation with subjective and objective annotations,

Reference 60

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Observation 603628b3-396b-4230-ba1e-0da3ec97608e · outbound

This paper cites Improving representation with hier- archical contrastive learning for emotion-cause pair extraction,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Improving representation with hier- archical contrastive learning for emotion-cause pair extraction,

Reference 61

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Observation fa74818d-87c5-45d3-8f33-7fa7b1cfbefa · outbound

This paper cites A reinforcement learning based two-stage model for emotion cause pair extraction,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing A reinforcement learning based two-stage model for emotion cause pair extraction,

Reference 62

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Observation a67f0794-525f-45fb-812d-161a4b69d666 · outbound

This paper cites Emoprompt-ecpe: Emotion knowledge-aware prompt- tuning for emotion-cause pair extraction,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Emoprompt-ecpe: Emotion knowledge-aware prompt- tuning for emotion-cause pair extraction,

Reference 63

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Observation bf407685-f952-41ea-9c3a-ae5c4fc8c914 · outbound

This paper cites Liu, Sentiment Analysis - Mining Opinions, Sentiments, and Emotions.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Liu, Sentiment Analysis - Mining Opinions, Sentiments, and Emotions

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:55.953595Z

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Observation fb9485bd-eb63-47bf-8e9a-028571daf05d · outbound

This paper cites Beneath the tip of the iceberg: Current challenges and new directions in sentiment analysis research,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Beneath the tip of the iceberg: Current challenges and new directions in sentiment analysis research,

Reference 65

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Observation 2d4b2a97-cab5-41dc-bdf1-ff6857785cee · outbound

This paper cites Sarcasm detection using news headlines dataset,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Sarcasm detection using news headlines dataset,

Reference 66

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Observation f0b31ce2-89fd-4213-9853-ca4631c759c8 · outbound

This paper cites Is sarcasm detection a step- by-step reasoning process in large language models?.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Is sarcasm detection a step- by-step reasoning process in large language models?

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:57.688397Z

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Observation 85eaa86b-ecd7-4c35-b108-65988ff05aeb · outbound

This paper cites Sentiment analysis and sarcasm detection using deep multi-task learning: Sentiment analysis and sarcasm detection,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Sentiment analysis and sarcasm detection using deep multi-task learning: Sentiment analysis and sarcasm detection,

Reference 68

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Observation 3914d650-6b28-4a45-a759-3c5789d0730c · outbound

This paper cites Topic- oriented sarcasm detection via entity knowledge-based prompt learning,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Topic- oriented sarcasm detection via entity knowledge-based prompt learning,

Reference 69

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Observation a4981922-0c23-4d2a-876d-3df4c463e0f3 · outbound

This paper cites Instructerc: Reforming emotion recognition in conversation with multi-task retrieval-augmented large language models,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Instructerc: Reforming emotion recognition in conversation with multi-task retrieval-augmented large language models,

Reference 70

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Observation 1b942edd-a894-4ece-b199-26a3b14d3368 · outbound

This paper cites Zhang, M.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Zhang, M

Reference 71

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This paper cites Language models are few-shot learners,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Language models are few-shot learners,

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:57.906484Z

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Observation 8489aaac-65fb-478e-9616-3f1cd25bc2b9 · outbound

This paper cites Self-consistency improves chain of thought reasoning in language models,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Self-consistency improves chain of thought reasoning in language models,

Reference 73

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Observation a6ebf9b8-a0e9-4bc2-ae55-4712e2053822 · outbound

This paper cites Complexity- based prompting for multi-step reasoning,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Complexity- based prompting for multi-step reasoning,

Reference 74

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This paper cites Automatic chain of thought prompting in large language models,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Automatic chain of thought prompting in large language models,

Reference 75

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Observation 9e8c6c0d-cc68-49cb-8a10-a71fdb12ff34 · outbound

This paper cites Prompted opinion sum- marization with GPT-3.5,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Prompted opinion sum- marization with GPT-3.5,

Reference 76

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Observation 01c4f5a7-1e98-4544-a9a8-93f604bca7bd · outbound

This paper cites An iterative associative memory model for empathetic response generation,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing An iterative associative memory model for empathetic response generation,

Reference 77

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Observation d6093ed2-cf13-4035-90aa-55fd986f3554 · outbound

This paper cites EmpCRL: Controllable empathetic response generation via in-context commonsense rea- soning and reinforcement learning,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing EmpCRL: Controllable empathetic response generation via in-context commonsense rea- soning and reinforcement learning,

Reference 78

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Observation 424a33c3-bdc3-4d3c-981e-38f997c92ae1 · outbound

This paper cites CASE: aligning coarse-to-fine cognition and affection for empathetic response generation,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing CASE: aligning coarse-to-fine cognition and affection for empathetic response generation,

Reference 79

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Observation ba93a804-1cac-4d0b-8fa5-01f4d5bd96f5 · outbound

This paper cites Control globally, understand locally: A global-to-local hierarchical graph network for emotional support conversation,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Control globally, understand locally: A global-to-local hierarchical graph network for emotional support conversation,

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:21.683447Z

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Observation 006a4d7b-b470-4e07-bd83-3a4d380f6a89 · outbound

This paper cites Augesc: Dialogue augmentation with large language models for emo- tional support conversation,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Augesc: Dialogue augmentation with large language models for emo- tional support conversation,

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:21.665367Z

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Observation 3975d57b-84cf-47b7-b44a-46992383e626 · outbound

This paper cites Towards emotional support dialog systems,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Towards emotional support dialog systems,

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:21.648686Z

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Observation d4efd2c3-3ec2-4317-acda-5c97b08da5de · outbound

This paper cites Towards mul- timodal emotional support conversation systems,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Towards mul- timodal emotional support conversation systems,

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:21.630535Z

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Observation 0255a9cd-0c3b-4485-bc75-03e4f3e9ac4f · outbound

This paper cites Knowledge-enhanced mixed-initiative dialogue system for emotional support conver- sations,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Knowledge-enhanced mixed-initiative dialogue system for emotional support conver- sations,

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:21.612928Z

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Observation 92e7fb40-5dc0-44e7-93e9-35f16d9be97e · outbound

This paper cites Pal: Persona-augmented emotional support conversation genera- tion,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Pal: Persona-augmented emotional support conversation genera- tion,

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:21.596933Z

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Observation 0bc84ee2-3942-4448-9568-23a7dadb73b3 · outbound

This paper cites Iteratively calibrat- ing prompts for unsupervised diverse opinion summarization,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Iteratively calibrat- ing prompts for unsupervised diverse opinion summarization,

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:21.579154Z

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Observation c821f0a5-6b69-48ed-a94c-173a3a78f071 · outbound

This paper cites Hierarchical indexing for retrieval-augmented opinion summarization,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Hierarchical indexing for retrieval-augmented opinion summarization,

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:21.558863Z

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Observation 9d779a3f-beb9-401a-9e38-68894778534d · outbound

This paper cites Product description and qa assisted self-supervised opinion summarization,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Product description and qa assisted self-supervised opinion summarization,

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:21.540617Z

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Observation 165c3da2-dfe2-44c0-a410-5e4681f298ec · outbound

This paper cites Improving multi-turn emotional support dialogue generation with lookahead strategy planning,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Improving multi-turn emotional support dialogue generation with lookahead strategy planning,

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:21.523053Z

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Observation aa481f48-8e69-4edf-9474-75a8a9971cb0 · outbound

This paper cites Emotionally intelligent chatbots: A systematic literature review,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Emotionally intelligent chatbots: A systematic literature review,

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:21.506724Z

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Observation 510ba9ab-0590-4943-bcdc-c69fc553575e · outbound

This paper cites Self-chats from large language models make small emotional support chatbot better,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Self-chats from large language models make small emotional support chatbot better,

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:21.488374Z

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Observation d1fc876b-fee2-4dee-b88e-ac3e9442a952 · outbound

This paper cites Can large language models be good emotional supporter? mitigating preference bias on emotional support conversation,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Can large language models be good emotional supporter? mitigating preference bias on emotional support conversation,

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:21.470138Z

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Observation 04d3cc96-9f0f-4070-bab6-e9ba4c4842c2 · outbound

This paper cites Llama: Open and efficient foundation language models,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Llama: Open and efficient foundation language models,

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:21.451493Z

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Observation 50446934-945c-4b00-8b6d-756630e9253d · outbound

This paper cites ESC-eval: Evaluating emotion support conversations in large language models,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing ESC-eval: Evaluating emotion support conversations in large language models,

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:21.433377Z

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Observation ef37ffa1-8782-40b9-8da5-b7a85d7cfe37 · outbound

This paper cites Make your LLM fully utilize the context,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Make your LLM fully utilize the context,

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:21.408946Z

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Observation 12654c74-d126-473e-8c2b-f10b94e9644b · outbound

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

When LLMs Team Up: The Emergence of Collaborative Affective Computing Chain-of-thought prompting elicits reasoning in large language models,

Reference 96

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Observation ba2f3a3f-c09e-45ff-80a5-3d07b9875834 · outbound

This paper cites Ds 2-absa: Dual-stream data synthesis with label refinement for few-shot aspect-based sentiment analysis,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Ds 2-absa: Dual-stream data synthesis with label refinement for few-shot aspect-based sentiment analysis,

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:21.379071Z

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Observation a0e0efa0-6a1e-4581-a6de-f75b3b510f30 · outbound

This paper cites Two heads are better than one: Zero-shot cognitive reasoning via multi-llm knowledge fusion,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Two heads are better than one: Zero-shot cognitive reasoning via multi-llm knowledge fusion,

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:21.361278Z

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Observation b80baf73-c61d-4aa9-bbb0-f6b663932c8c · outbound

This paper cites Attention is all you need,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Attention is all you need,

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:21.341741Z

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Observation 6ed2e609-7902-4db8-82ca-c5bf75a84dd8 · outbound

This paper cites Bert: Pre- training of deep bidirectional transformers for language under- standing,.

When LLMs Team Up: The Emergence of Collaborative Affective Computing Bert: Pre- training of deep bidirectional transformers for language under- standing,

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:41:21.321323Z

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