MIT built an AI that predicts what you’ll say next… before you open your mouth. In the research paper titled “Before You Say It: Anticipating Verbal Behavior from Longitudinal Everyday Conversations with LLMs,” researchers set out to test whether Large Language Models (LLMs) can build this same level of intuitive, person-specific understanding.

In this AI Research Roundup episode, Alex discusses the paper: ‘Before You Say It: Anticipating Verbal Behavior from Longitudinal Everyday Conversations with LLMs’ Understanding an individual deeply requires anticipating how they will likely react and communicate across different real-world situations. In this paper, the authors introduce an LLM-based predictive behavioral modeling framework designed to forecast personal verbal behavior from everyday conversational interactions. The researchers collected over 1,000 hours of naturalistic speech from 14 participants using wearable smartwatches and evaluated LLM predictions against actual recorded behaviors. Semi-structured interviews further explored user perceptions and identified promising directions for proactive behavioral assistance. Ultimately, the study demonstrates that longitudinal conversation data enables person-specific behavioral anticipation for future personalized assistive systems. Paper URL: https://arxiv.org/pdf/2608.13454 #AI #MachineLearning #DeepLearning #LLM #ConversationalAI #BehavioralModeling #WearableTech