Papers by Lenhart Schubert

2 papers
We Are What We Repeatedly Do: Inducing and Deploying Habitual Schemas in Persona-Based Responses (2023.emnlp-main)

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Challenge: a variety of personas can be elicited from large language models, but they are opaque and unpredictable.
Approach: They propose an approach to dialogue generation that retrieves relevant schemas to condition a large language model to generate persona-based responses.
Outcome: The proposed method captures habitual knowledge and generates persona-based responses from a large language model.
Mining Logical Event Schemas From Pre-Trained Language Models (2022.acl-srw)

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Challenge: a pre-trained language model is induced into acting as a distribution over stories, a new system is proposed . NESL is a neural event schema learning system that combines large language models, FrameNet parsing, and simple behavioral schemas to bootstrap the learning process.
Approach: They propose a neural event schema learning system that bootstraps the learning process by parsing pre-trained language models into simple behavioral schemas.
Outcome: The proposed system combines large language models, a powerful logical representation of language, and simple behavioral schemas to bootstrap the learning process.

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