Papers by Andrej Švec

2 papers
Prompterator: Iterate Efficiently towards More Effective Prompts (2023.emnlp-demo)

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Challenge: Large Language Models (LLMs) use a process known as prompting to solve arbitrary language tasks. prompting is a non-trivial task that requires experimentation in order to arrive at a prompt that solves a specific task.
Approach: They propose a tool that helps users iterate over different potential prompts and choose the best performing one based on human feedback.
Outcome: The proposed tool is open source and easily extensible.
Cost-effective Deployment of BERT Models in Serverless Environment (2021.naacl-industry)

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Challenge: a large upfront infrastructure investment makes machine learning models difficult to deploy . however, serverless architectures have strict limits on the size of the deployment package .
Approach: They propose to fine-tune BERT-style models on proprietary datasets for tasks . they use knowledge distillation to obtain models that are tuned for a specific domain .
Outcome: The proposed model deployments report acceptable latency levels and cost-effectiveness without infrastructure overhead.

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