Title: Conversational Alignment with Artificial Intelligence in Context Show Chinese title

Title: 上下文中与人工智能的对话一致性

Abstract: The development of sophisticated artificial intelligence (AI) conversational agents based on large language models raises important questions about the relationship between human norms, values, and practices and AI design and performance. This article explores what it means for AI agents to be conversationally aligned to human communicative norms and practices for handling context and common ground and proposes a new framework for evaluating developers' design choices. We begin by drawing on the philosophical and linguistic literature on conversational pragmatics to motivate a set of desiderata, which we call the CONTEXT-ALIGN framework, for conversational alignment with human communicative practices. We then suggest that current large language model (LLM) architectures, constraints, and affordances may impose fundamental limitations on achieving full conversational alignment. Show Chinese abstract

Abstract: 基于大型语言模型的复杂人工智能（AI）对话代理的发展引发了关于人类规范、价值观和实践与AI设计和性能之间关系的重要问题。 本文探讨了AI代理在处理上下文和共同背景时与人类沟通规范和实践保持会话一致性的意义，并提出了一个评估开发人员设计选择的新框架。 我们首先借鉴会话语用学的哲学和语言学文献，提出一组理想特性，我们称之为CONTEXT-ALIGN框架，以实现与人类沟通实践的会话一致性。 然后我们建议，当前的大规模语言模型（LLM）架构、约束和功能可能对实现完全的会话一致性施加了根本性的限制。