Persona-driven generations by LLMs in MCQA tasks exhibit instability that differs systematically by model family, size, domain, and prompt format.
arXiv preprint arXiv:2404.13066 , year=
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UNVERDICTED 3representative citing papers
TEA Nets extracts agents, events, and targets from text to reveal emotional and semantic patterns in conspiracy theories and psychotherapy transcripts from humans and LLMs.
UniReason-Med introduces a unified framework for 2D and 3D medical VQA with shared grounded reasoning, trained on a 220K dataset, claiming that joint 2D+3D supervision improves 3D performance over 3D-only training.
citing papers explorer
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Persona Non Grata: LLM Persona-Driven Generations in MCQA are Unstable in Distinct Dimensions
Persona-driven generations by LLMs in MCQA tasks exhibit instability that differs systematically by model family, size, domain, and prompt format.
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The TEA Nets framework combines AI and cognitive network science to model targets, events and actors in text
TEA Nets extracts agents, events, and targets from text to reveal emotional and semantic patterns in conspiracy theories and psychotherapy transcripts from humans and LLMs.
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UniReason-Med: A Shared Grounded Reasoning Interface for 2D-to-3D Transfer in Medical VQA
UniReason-Med introduces a unified framework for 2D and 3D medical VQA with shared grounded reasoning, trained on a 220K dataset, claiming that joint 2D+3D supervision improves 3D performance over 3D-only training.