Papers with creators

2 papers
Quality Estimation for Partially Subjective Classification Tasks via Crowdsourcing (2020.lrec-1)

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Challenge: a common approach to quality estimation is to ask multiple reviewers to evaluate the same artifacts.
Approach: They propose a probabilistic model for subjective classification tasks that incorporates the qualities of artifacts as well as the abilities and biases of creators and reviewers as latent variables to be jointly inferred.
Outcome: The proposed model estimates the quality of speech more effectively than a vote aggregation, measured by correlation with a fine-grained classification by experts.
Roleplay-doh: Enabling Domain-Experts to Create LLM-simulated Patients via Eliciting and Adhering to Principles (2024.emnlp-main)

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Challenge: Existing methods for improving LLMs in simulations are limited due to privacy concerns and limited domain knowledge.
Approach: They propose a pipeline that elicits qualitative feedback from a domain-expert and transforms it into a set of principles that govern an LLM-prompted roleplay.
Outcome: The proposed pipeline shows a 30% improvement in response quality and principle following for the downstream task.

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