multi-turn conversations ↔ Large Language Models

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related 2.00 — strongly supporting 3 facts

Large Language Models are the primary technology utilized in multi-turn conversations, as evidenced by their application in automated red teaming [1] and knowledge base question answering [2]. Furthermore, the performance and reliability of these models are specifically evaluated based on their ability to maintain consistency during multi-turn interactions [3].

Facts (3)

Sources

A Survey of Incorporating Psychological Theories in LLMs - arXiv arxiv.org arXiv 1 fact

referenceZhang et al. (2024b) developed a holistic automated red teaming method for large language models that utilizes top-down test case generation and multi-turn interaction, published in the Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing.

LLM Observability: How to Monitor AI When It Thinks in Tokens | TTMS ttms.com TTMS 1 fact

claimIn multi-turn interactions, LLMs may experience inconsistencies and drift, where the model contradicts itself or loses track of context, potentially frustrating users and degrading trust.

Large Language Models Meet Knowledge Graphs for Question ... arxiv.org arXiv 1 fact

referenceGuanming Xiong, Junwei Bao, and Wen Zhao authored 'Interactive-KBQA: Multi-turn interactions for knowledge base question answering with large language models', published in the 2024 ACL proceedings.