Papers by Jianyong Yuan

2 papers
Prompt Tuning for Discriminative Pre-trained Language Models (2022.findings-acl)

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Challenge: Recent studies have shown promising results of prompt tuning in stimulating pre-trained language models (PLMs) for natural language processing tasks.
Approach: They propose a prompt tuning framework that reformulates NLP tasks into a discriminative language modeling problem.
Outcome: The proposed framework improves on text classification and question answering tasks and prevents unstable tuning problems in low-resource settings.
EpiGEN: An Efficient Multi-Api Code GENeration Framework under Enterprise Scenario (2024.lrec-main)

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Challenge: Existing approaches to large language models fail to meet expectations for code generation tasks . existing approaches are faced with drawbacks of high resource consumption and inadequate handling of multi-API tasks.
Approach: They propose an Efficient multi-Api code GENeration framework that uses private APIs to pre-train LLMs.
Outcome: The proposed framework shows good acceptability and readability on single-GPU tasks compared to fully fine-tuned LLMs with a larger number of parameters.

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