2 citations · 2 across the 4 of their papers we have counts for
4 papers · 1 filter
Exploring and Controlling Diversity in LLM-Agent Conversation
KuanChao Chu, Yi-Pei Chen, Hideki Nakayama
Controlling diversity in LLM-agent simulations is essential for balancing stability in structured tasks with variability in open-ended interactions. However, we observe that dialog…
Cohesive Conversations: Enhancing Authenticity in Multi-Agent Simulated Dialogues
KuanChao Chu, Yi-Pei Chen, Hideki Nakayama
This paper investigates the quality of multi-agent dialogues in simulations powered by Large Language Models (LLMs). Analyzing dialogues and memory over multiple sessions revealed…
A Better LLM Evaluator for Text Generation: The Impact of Prompt Output Sequencing and Optimization
KuanChao Chu, Yi-Pei Chen, Hideki Nakayama
This research investigates prompt designs of evaluating generated texts using large language models (LLMs). While LLMs are increasingly used for scoring various inputs, creating ef…
LLM as a Scorer: The Impact of Output Order on Dialogue Evaluation
Yi-Pei Chen, KuanChao Chu, Hideki Nakayama
This research investigates the effect of prompt design on dialogue evaluation using large language models (LLMs). While LLMs are increasingly used for scoring various inputs, creat…