Awesome Affective Computing

🤖 The traditional tasks of Affective Computing

Paper List

1. PRELIMINARY STUDY

1.1 Affective Understanding

1. "A survey of sentiment analysis: Approaches, datasets, and future research". [Paper]
2. "A review on sentiment analysis from social media platforms". [Paper]
3. "Multimodal sentiment analysis: a survey of methods, trends, and challenges" [Paper]
4. "Sentiment analysis in the age of generative ai" [Paper]
5. "Sentiment analysis in the era of large language models: A reality check"
6. "Leveraging chatgpt as text annotation tool for sentiment analysis"
7. "A comparison of chatgpt and fine-tuned open pre-trained transformers (opt) against widely used sentiment analysis tools: Sentiment analysis of covid-19 survey data"
8. "Man vs. machine: An applied study comparing a manmade lexicon, a machine learned lexicon, and openai’s gpt for sentiment analysis."
9. "A wide evaluation of chatgpt on affective computing tasks"
10. "Is chatgpt a good sentiment analyzer? a preliminary study"
11. "Enhancing large language model with decomposed reasoning for emotion cause pair extraction"
12. "Revisiting sentiment analysis for software engineering in the era of large language models. "
13. "Will affective computing emerge from foundation models and general artificial intelligence? a first evaluation of chatgpt"
14. "On prompt sensitivity of chatgpt in affective computing"
15. "Secrets of rlhf in large language models part i: Ppo"
16. "Sentimentanalysis in the age of generative ai"

1.2 Affective Generation

1. "Towards empathetic open-domain conversation models: a new benchmark and dataset,"
2. "Towards emotional support dialog systems"
3. "Is chatgpt equipped with emotional dialogue capabilities?"
4. "Is chatgpt more empathetic than humans?"
5. "Emotional intelligence -- a review and evaluation study"
6. "Measuring emotional intelligence with the msceit v2.0"
7. "Models of emotional intelligence"
8. "Chatgpt outperforms humans in emotional awareness evaluations"
9. "The six emotional dimension (6de) model: A multidimensional approach to analyzing human emotions and unlocking the potential of emotionally intelligent artificial intelligence (ai) via large language models (llm)"
10. "The levels of emotional awareness scale: A cognitive-developmental measure of emotion"
11. "Emotional intelligence of large language models"
12. "An emotional intelligence benchmark for large language models"
13. "Soul: Towards sentiment and opinion understanding of language"

2. INSTRUCTION TUNING

2.1 Affective Understanding

1. "A survey of large language models"
2. "Instruction tuning for large language models: A survey"
3. "Lora technology an overview"
4. "Prefix-tuning: Optimizing continuous prompts for generation"
5. "P-tuning: Prompt tuning can be comparable to fine-tuning across scales and tasks"
6. "Exploring the limits of transfer learning with a unified text-to-text transformer"
7. "Customising general large language models for specialised emotion recognition tasks"
8. "Chatglm: A family of large language models from glm-130b to glm-4 all tools"
9. "Enhancing financial sentiment analysis via retrieval augmented large language models"
10. "Supernaturalinstructions:generalization via declarative in structions on 1600+ tasks"
11. "Instruction tuning for few-shot aspect based sentiment analysis"
12. "Unisa: Unified generative framework for sentiment analysis"
13. "Llama 2: Open foundation and fine-tuned chat models"
14. "MELD: A multimodal multi-party dataset for emotion recognition in conversations"
15. "Emotion detection on tv show transcripts with sequence-based convolutional neural networks"
16. "Dialoguellm: Context and emotion knowledge-tuned llama models for emotion recognition in conversations"
17. "Emollms: A series of emotional large language models and annotation tools for comprehensive affective analysis"
18. "Emotion-cause pair extraction: A new task to emotion analysis in texts"
19. "End-to-end emotion-cause pair extraction based on sliding window multi-label learning"
20. "Effective inter-clause modeling for end-to-end emotion-cause pair extraction"
21. "SemEval-2024 task 3: Multimodal emotion cause analysis in conversations"
22. "Nus-emo at semeval-2024 task 3: Instruction-tuning llm for multimodal emotion-cause analysis in conversations"
23. "Prompting and fine-tuning open-sourced large language models for stance classificatio"
24. "Usa: Universal sentiment analysis model & construction of japanese sentiment text classification and part of speech dataset"
25. "Wisdom: Improving multimodal sentiment analysis by fusing contextual world knowledge"
26. "Instructabsa: Instruction learning for aspect based sentiment analysis"
27. "Unimse: Towards unified multimodal sentiment analysis and emotion recognition"
28. "Ckerc : Joint large language models with commonsense knowledge for emotion recognition in conversation"
29. "Instructerc: Reforming emotion recognition in conversation with a retrieval multi-task llms framework"
30. "Enhancing large language model with decomposed reasoning for emotion cause pair extraction"

2.2 Affective Generation

1. "A review of affective generation models"
2. "Building emotional support chatbots in the era of llms"
3. "Enhancing empathetic and emotion support dialogue generation with prophetic commonsense inference"
4. "Stickerconv: Generating multimodal empathetic responses from scratch"
5. "Self-instruct: Aligning language models with self-generated instructions"
6. "Soulchat: Improving llms’ empathy, listening, and comfort abilities through fine-tuning with multi-turn empathy conversations"
7. "Enhancing empathetic and emotion support dialogue generation with prophetic commonsense inference"
8. "Pica: Unleashing the emotional power of large language model"
9. "Emollm"
10. "Qlora: Efficient finetuning of quantized llms"

2.3 Multi-task of Affective Computing

1. "Mixlora: Enhancing large language models fine-tuning with lora-based mixture of experts"
2. "Both matter: Enhancing the emotional intelligence of large language models without compromising the general intelligence"
3. "Emoada: A multimodal emotion interaction and psychological adaptation system"

3. PROMPT ENGINEERING

3.1 Affective Understanding

1. "Language models are few-shot learners"
2. "Generative agents: Interactive simulacra of human behavior"
3. "Wisdom: Improving multimodal sentiment analysis by fusing contextual world knowledge"
4. "Enhance multi-domain sentiment analysis of review texts through prompting strategies"
5. "Large language models performance comparison of emotion and sentiment classification"
6. "Self-consistent reasoning-based aspect-sentiment quad prediction with extract-then-assign strategy"
7. "A wide evaluation of chatgpt on affective computing tasks"
8. "Large language models understand and can be enhanced by emotional stimuli"
9. "Enhancing empathetic and emotion support dialogue generation with prophetic commonsense inference"
10. "Chain-of-thought prompting elicits reasoning in large language models"
11. "Camel: Communicative agents for" mind" exploration of large language model society"
12. "Autogen: Enabling next-gen llm applications via multi-agent conversation framework"
13. "Stability analysis of chatgpt-based sentiment analysis in ai quality assurance"
14. "Sentiment and interest detection in social media using gpt-based large language models"
15. "Large language model-based emotional speech annotation using context and acoustic feature for speech emotion recognition"
16. "Introducing the lcc metaphor datasets"
17. "Reasoning in conversation: Solving subjective tasks through dialogue simulation for large language models"
18. "Aspect sentiment quad prediction as paraphrase generation"
19. "An empirical study of multimodal entity-based sentiment analysis with chatgpt: Improving in-context learning via entity-aware contrastive learning"
20. "Visual instruction tuning"
21. "mplug-owl2: Revolutionizing multi-modal large language model with modality collaboration"
22. "Depression detection in clinical interviews with llm-empowered structural element graph"
23. "Dialectical behavioral therapy: A cognitive behavioral approach to parasuicide"
24. "Person-centered therapy: A pluralistic perspective"
25. "Using the wdep system of reality therapy to support person-centered treatment planning"
26. "Evolutionary multiobjective optimization of large language model prompts for balancing sentiments"
27. "Ntusdfin: a market sentiment dictionary for financial social media data application"
28. "Llms to the moon? reddit market sentiment analysis with large language models"
29. "Can generative agents predict emotion?"
30. "Designing heterogeneous llm agents for financial sentiment analysis"

3.2 Affective Generation

1. "Investigating the effects of zero-shot chain-of-thought on empathetic dialogue generation"
2. "Emotion-conditioned text generation through automatic prompt optimization"
3. "Prompt your mind: Refine personalized text prompts within your mind"
4. "Sibyl: Sensible empathetic dialogue generation with visionary commonsense knowledge"
5. "Controllable mixed-initiative dialogue generation through prompting"
6. "Can large language models be good emotional supporter? mitigating preference bias on emotional support conversation"
7. "A new dialogue response generation agent for large language models by asking questions to detect user’s intentions"
8. "Prompting and evaluating large language models for proactive dialogues: Clarification, target-guided, and non-collaboration"
9. "Enhancing the emotional generation capability of large language models via emotional chain-of-though"
10. "Escot: Towards interpretable emotional support dialogue system"
11. "Cmdag: A chinese metaphor dataset with annotated grounds as cot for boosting metaphor generation"
12. "Cooper: Coordinating specialized agents towards a complex dialogue goal"
13. "Empathy through multimodality in conversational interfaces"
14. "Llama: Open and efficient foundation language models"

4. BENCHMARK & EVALUATION

4.1 Affective Understanding

1. "Leveraging chatgpt as text annotation tool for sentiment analysis"
2. "Soul: Towards sentiment and opinion understanding of language"
3. "Gpt-4v with emotion: A zero-shot benchmark for generalized emotion recognition,"
4. "Merbench: A unified evaluation benchmark for multimodal emotion recognition"
5. "MELD: A multimodal multi-party dataset for emotion recognition in conversations"
6. "Tensor fusion network for multimodal sentiment analysis"
7. "Multimodal language analysis in the wild: Cmu-mosei dataset and interpretable dynamic fusion graph"
8. "Ch-sims: A chinese multimodal sentiment analysis dataset with fine-grained annotation of modality"
9. "Make acoustic and visual cues matter: Ch-sims v2.0 dataset and av-mixup consistent module"
10. "Towards empathetic open-domain conversation models: A new benchmark and dataset"
11. "Pens: A dataset and generic framework for personalized news headline generation"
12. "Senticap: Generating image descriptions with sentiments"
13. "Microsoft coco: Common objects in context"
14. "Augesc: Dialogue augmentation with large language models for emotional support conversation"
15. "The ability model of emotional intelligence: Principles and updates"
16. "Emotion and intent joint understanding in multimodal conversation: A benchmarking dataset"

4.2 Affective Generation

1. "Eq-bench: An emotional intelligence benchmark for large language model"
2. "Both matter: Enhancing the emotional intelligence of large language models without compromising the general intelligence"
3. "Can large language models be good emotional supporter? mitigating preference bias on emotional support conversation"
4. "Cue-cot: Chain-of-thought prompting for responding to in-depth dialogue questions with llms"
5. "A wide evaluation of chatgpt on affective computing tasks"
6. "Enhancing the emotional generation capability of large language models via emotional chain-of-thought"
7. "Feel: A framework for evaluating emotional support capability with large language models,"
8. "Medic: A multimodal empathy dataset in counseling"
9. "Emotionally numb or empathetic? evaluating how llms feel using emotionbench"
10. "Harnessing the power of large language models for empathetic response generation: Empirical investigations and improvement"
11. "Towards emotional support dialog systems"