A multi-agent system with finite state machine for therapeutic stages was perceived as significantly more natural and human-like than single-agent or unguided LLM versions in an RCT with 66 participants.
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XTransplant empirically shows that cross-lingual latent transplantation yields mutual benefits for multilingual capability and cultural adaptability in LLMs, especially low-resource ones, while revealing underutilized model potential.
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Structure Matters: Evaluating Multi-Agents Orchestration in Generative Therapeutic Chatbots
A multi-agent system with finite state machine for therapeutic stages was perceived as significantly more natural and human-like than single-agent or unguided LLM versions in an RCT with 66 participants.
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Exploring Cross-lingual Latent Transplantation: Mutual Opportunities and Open Challenges
XTransplant empirically shows that cross-lingual latent transplantation yields mutual benefits for multilingual capability and cultural adaptability in LLMs, especially low-resource ones, while revealing underutilized model potential.