1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.AI2024★ 1 cited
Problem-Solving in Language Model Networks
Ciaran Regan, Alexandre Gournail, Mizuki Oka
To improve the reasoning and question-answering capabilities of Large Language Models (LLMs), several multi-agent approaches have been introduced. While these methods enhance perfo…
cs.NE2024
LLM-POET: Evolving Complex Environments using Large Language Models
Fuma Aki, Riku Ikeda, Takumi Saito +2
Creating systems capable of generating virtually infinite variations of complex and novel behaviour without predetermined goals or limits is a major challenge in the field of AI. T…
cs.AI2024★ 1 cited
Can Generative Agents Predict Emotion?
Ciaran Regan, Nanami Iwahashi, Shogo Tanaka +1
Large Language Models (LLMs) have demonstrated a number of human-like abilities, however the empathic understanding and emotional state of LLMs is yet to be aligned to that of huma…