Can Large Language Models Reason About Emotions Like Humans Research

Can Large Language Models Reason About Emotions Like Humans Research Emotional intelligence helps humans navigate complex social worlds—but can machines do the same? our new paper examines how well large language models such as chatgpt, claude, gemini, or deepseek understand, interpret, and generate emotional content. Modern language models are trained in multiple stages. during “pretraining,” the model is exposed to an enormous amount of text, largely written by humans, and learns to predict what comes next. to do this well, the model needs some grasp of emotional dynamics.

Can Large Language Models Reason About Emotions Like Humans Research Our results support that the current level of whether the closed source model's empathy ability or the open source model's empathy ability is still significantly lower than that of humans in both cognitive and affective dimensions, and the gap is more significant in the affective dimension. The human level performance of large language models (llms) across various tasks has raised expectations for the potential of artificial intelligence (ai) to possess emotions someday. This study comprehensively explores whether there actually exist “emotion neurons” within large language models (llms) that selectively process and express certain emotions, and what functional role they play. The prior iteration of the large language model from openai, chatgpt 3.5, demonstrated an advanced capacity to interpret emotions from textual data, surpassing human benchmarks.

Can Large Language Models Reason About Emotions Like Humans Research This study comprehensively explores whether there actually exist “emotion neurons” within large language models (llms) that selectively process and express certain emotions, and what functional role they play. The prior iteration of the large language model from openai, chatgpt 3.5, demonstrated an advanced capacity to interpret emotions from textual data, surpassing human benchmarks. This project, conducted in collaboration with shiro kumano and hiromi narimatsu at nippon telegraph and telephone (ntt), and funded by ntt, investigates whether large language models (llms) can serve as proxies in emotion research by estimating human emotional states from multi modal responses. in. With a reference frame constructed from over 500 adults, we tested a variety of mainstream llms. most achieved above average emotional quotient (eq) scores, with gpt 4 exceeding 89% of human participants with an eq of 117. Large language models (llms) demonstrate expertise across diverse domains, yet their capacity for emotional intelligence remains uncertain. this research examined whether llms can solve. This review synthesizes insights from a diverse peer reviewed research articles that delve into methodologies, benchmarks, datasets, and fine tuning techniques in furthering the emotional understanding of llms, its affective recognition, and empathetic responsiveness.

Can Large Language Models Reason About Emotions Like Humans Research This project, conducted in collaboration with shiro kumano and hiromi narimatsu at nippon telegraph and telephone (ntt), and funded by ntt, investigates whether large language models (llms) can serve as proxies in emotion research by estimating human emotional states from multi modal responses. in. With a reference frame constructed from over 500 adults, we tested a variety of mainstream llms. most achieved above average emotional quotient (eq) scores, with gpt 4 exceeding 89% of human participants with an eq of 117. Large language models (llms) demonstrate expertise across diverse domains, yet their capacity for emotional intelligence remains uncertain. this research examined whether llms can solve. This review synthesizes insights from a diverse peer reviewed research articles that delve into methodologies, benchmarks, datasets, and fine tuning techniques in furthering the emotional understanding of llms, its affective recognition, and empathetic responsiveness.

Can Large Language Models Truly Think Like Humans Pdf Large language models (llms) demonstrate expertise across diverse domains, yet their capacity for emotional intelligence remains uncertain. this research examined whether llms can solve. This review synthesizes insights from a diverse peer reviewed research articles that delve into methodologies, benchmarks, datasets, and fine tuning techniques in furthering the emotional understanding of llms, its affective recognition, and empathetic responsiveness.