More than Chit-Chat: Developing Robots for Small-Talk Interactions
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Abstract (arXiv)
Beyond mere formality, small talk plays a pivotal role in social dynamics, serving as a verbal handshake for building rapport and understanding. For conversational AI and social robots, the ability to engage in small talk enhances their perceived sociability, leading to more comfortable and natural user interactions. In this study, we evaluate the capacity of current Large Language Models (LLMs) to drive the small talk of a social robot and identify key areas for improvement. We introduce a novel method that autonomously generates feedback and ensures LLM-generated responses align with small talk conventions. Through several evaluations -- involving chatbot interactions and human-robot interactions -- we demonstrate the system's effectiveness in guiding LLM-generated responses toward realistic, human-like, and natural small-talk exchanges.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 4 of its 43 references that are in the map. First posted on arXiv 23 Dec 2024.
Builds on
4 of 43 references.
References · 4
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2020Language Models are Few-Shot Learnerscited by 32,419
- 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 13,028
- 2023Gemini: A Family of Highly Capable Multimodal Modelscited by 872
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Citing papers per year: 2026: 1.
1 paper.