ETI lets LLM agents infer and track partners' psychological traits (warmth and competence) from histories, cutting payoff loss 45-77% in games and boosting performance 3-29% on MultiAgentBench versus CoT baselines.
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2 Pith papers cite this work. Polarity classification is still indexing.
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BlossomPsy combines multi-turn LLM dialogue, photo-based items, a multi-head classifier, modified UCB, and PID-tuned confidence scaling for adaptive MBTI assessment with preliminary human and LLM evaluation.
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Explicit Trait Inference for Multi-Agent Coordination
ETI lets LLM agents infer and track partners' psychological traits (warmth and competence) from histories, cutting payoff loss 45-77% in games and boosting performance 3-29% on MultiAgentBench versus CoT baselines.
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BlossomPsy: A User-Centric AI System for Adaptive and Engaging MBTI Personality Assessments
BlossomPsy combines multi-turn LLM dialogue, photo-based items, a multi-head classifier, modified UCB, and PID-tuned confidence scaling for adaptive MBTI assessment with preliminary human and LLM evaluation.