@inproceedings{jokinen-2024-need,
    title = "The Need for Grounding in {LLM}-based Dialogue Systems",
    author = "Jokinen, Kristiina",
    editor = "Dong, Tiansi  and
      Hinrichs, Erhard  and
      Han, Zhen  and
      Liu, Kang  and
      Song, Yangqiu  and
      Cao, Yixin  and
      Hempelmann, Christian F.  and
      Sifa, Rafet",
    booktitle = "Proceedings of the Workshop: Bridging Neurons and Symbols for Natural Language Processing and Knowledge Graphs Reasoning (NeusymBridge) @ LREC-COLING-2024",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.neusymbridge-1.5",
    pages = "45--52",
    abstract = "Grounding is a pertinent part of the design of LLM-based dialogue systems. Although research on grounding has a long tradition, the paradigm shift caused by LLMs has brought the concept onto the foreground, in particular in the context of cognitive robotics. To avoid generation of irrelevant or false information, the system needs to ground its utterances into real-world events, and to avoid the statistical parrot effect, the system needs to construct shared understanding of the dialogue context and of the partner{'}s intents. Grounding and construction of the shared context enables cooperation between the participants, and thus supports trustworthy interaction. This paper discusses grounding using neural LLM technology. It aims to bridge neural and symbolic computing on the cognitive architecture level, so as to contribute to a better understanding of how conversational reasoning and collaboration can be linked to LLM implementations to support trustworthy and flexible interaction.",
}

Grounding is a pertinent part of the design of LLM-based dialogue systems. Although research on grounding has a long tradition, the paradigm shift caused by LLMs has brought the concept onto the foreground, in particular in the context of cognitive robotics. To avoid generation of irrelevant or false information, the system needs to ground its utterances into real-world events, and to avoid the statistical parrot effect, the system needs to construct shared understanding of the dialogue context and of the partner{'}s intents. Grounding and construction of the shared context enables cooperation between the participants, and thus supports trustworthy interaction. This paper discusses grounding using neural LLM technology. It aims to bridge neural and symbolic computing on the cognitive architecture level, so as to contribute to a better understanding of how conversational reasoning and collaboration can be linked to LLM implementations to support trustworthy and flexible interaction.
Jokinen, Kristiina
The Need for Grounding in LLM-based Dialogue Systems