SOTAVerified

Emotional Intelligence

Emotional Intelligence (EI) is a measure of "The ability to monitor one’s own and others’ feelings, to discriminate among them, and to use this information to guide one’s thinking and action." (Salovey and Mayer, 1990). EI is further broken down into four branches: perceiving, using, understanding and managing emotions (Mayer & Salovey, 1997). Of particular relevance to language models that operate exclusively in the text modality is emotional understanding (EU). This is defined as the ability to interpret and analyse the language of emotions, to comprehend complex emotional states, and understand how these emotions can influence behaviour and decision-making.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 26–50 of 77 papers

TitleStatusHype
Empirical Interpretation of the Relationship Between Speech Acoustic Context and Emotion Recognition—0
Enhancing AI-Driven Psychological Consultation: Layered Prompts with Large Language Models—0
Enhancing Human-Like Responses in Large Language Models—0
Enhancing Emotional Generation Capability of Large Language Models via Emotional Chain-of-Thought—0
Exponential Shift: Humans Adapt to AI Economies—0
Fuzzy Approach for Audio-Video Emotion Recognition in Computer Games for Children—0
Generative AI and Its Impact on Personalized Intelligent Tutoring Systems—0
Generative Technology for Human Emotion Recognition: A Scope Review—0
HICEM: A High-Coverage Emotion Model for Artificial Emotional Intelligence—0
Human-In-The-Loop Machine Learning for Safe and Ethical Autonomous Vehicles: Principles, Challenges, and Opportunities—0
Identity-free Artificial Emotional Intelligence via Micro-Gesture Understanding—0
Investigating Audio, Video, and Text Fusion Methods for End-to-End Automatic Personality Prediction—0
Deep Multi-Facial patches Aggregation Network for Expression Classification from Face Images—0
Investigating Audio, Visual, and Text Fusion Methods for End-to-End Automatic Personality Prediction—0
AER-LLM: Ambiguity-aware Emotion Recognition Leveraging Large Language Models—0
Affective Image Content Analysis: Two Decades Review and New Perspectives—0
An Appraisal-Based Chain-Of-Emotion Architecture for Affective Language Model Game Agents—0
Appraisal-Guided Proximal Policy Optimization: Modeling Psychological Disorders in Dynamic Grid World—0
A Practice of Post-Training on Llama-3 70B with Optimal Selection of Additional Language Mixture Ratio—0
A Survey on Human-Centric LLMs—0
Can Large Language Models be Good Emotional Supporter? Mitigating Preference Bias on Emotional Support Conversation—0
Challenges of Artificial Intelligence -- From Machine Learning and Computer Vision to Emotional Intelligence—0
Continuing Pre-trained Model with Multiple Training Strategies for Emotional Classification—0
Reevaluating Data Partitioning for Emotion Detection in EmoWOZ—0
Research on emotionally intelligent dialogue generation based on automatic dialogue system—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1OpenAI gpt-4-0613EQ-Bench Score62.52—Unverified
2migtissera/SynthIA-70B-v1.5EQ-Bench Score54.83—Unverified
3OpenAI gpt-4-0314EQ-Bench Score53.39—Unverified
4Qwen/Qwen-72B-ChatEQ-Bench Score52.44—Unverified
5Anthropic Claude2EQ-Bench Score52.14—Unverified
6meta-llama/Llama-2-70b-chat-hfEQ-Bench Score51.56—Unverified
701-ai/Yi-34B-ChatEQ-Bench Score51.03—Unverified
8OpenAI gpt-3.5-0613EQ-Bench Score49.17—Unverified
9OpenAI gpt-3.5-turbo-0301EQ-Bench Score47.61—Unverified
10Open-Orca/Mistral-7B-OpenOrcaEQ-Bench Score44.4—Unverified