6 citations · 21 across the 13 of their papers we have counts for
4 papers · 1 filter
StyleChat: Learning Recitation-Augmented Memory in LLMs for Stylized Dialogue Generation
Jinpeng Li, Zekai Zhang, Quan Tu +3
Large Language Models (LLMs) demonstrate superior performance in generative scenarios and have attracted widespread attention. Among them, stylized dialogue generation is essential…
StreamingDialogue: Prolonged Dialogue Learning via Long Context Compression with Minimal Losses
Jia-Nan Li, Quan Tu, Cunli Mao +3
Standard Large Language Models (LLMs) struggle with handling dialogues with long contexts due to efficiency and consistency issues. According to our observation, dialogue contexts…
"In Dialogues We Learn": Towards Personalized Dialogue Without Pre-defined Profiles through In-Dialogue Learning
Chuanqi Cheng, Quan Tu, Shuo Shang +4
Personalized dialogue systems have gained significant attention in recent years for their ability to generate responses in alignment with different personas. However, most existing…
CharacterEval: A Chinese Benchmark for Role-Playing Conversational Agent Evaluation
Quan Tu, Shilong Fan, Zihang Tian +1
Recently, the advent of large language models (LLMs) has revolutionized generative agents. Among them, Role-Playing Conversational Agents (RPCAs) attract considerable attention due…