Papers by Zejie Liu

3 papers
Code Generation From Flowcharts with Texts: A Benchmark Dataset and An Approach (2022.findings-emnlp)

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Challenge: Currently, researchers focus on generating codes from requirement documents.
Approach: They propose to generate source code from flowcharts with texts instead of directly translating requirements into codes.
Outcome: The proposed model improves on the baselines by transforming flowcharts into pseudo-code . the proposed model is based on 320 flowchartes with their corresponding source codes .
Complicate Then Simplify: A Novel Way to Explore Pre-trained Models for Text Classification (2022.coling-1)

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Challenge: Existing frameworks for text classification employing pre-trained models are constrained by the difficulty of the task.
Approach: They propose a framework which implements a two-stage training strategy to fully exploit the knowledge in pre-trained models.
Outcome: The proposed framework outperforms state-of-the-art classification models on six text classification corpora.
G3R: A Graph-Guided Generate-and-Rerank Framework for Complex and Cross-domain Text-to-SQL Generation (2023.findings-acl)

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Challenge: Existing approaches to complex and cross-domain Text-to-SQL generation lack domain knowledge . domain knowledge is not incorporated to enhance their ability to generalise to unseen databases.
Approach: They propose a framework called G3R for complex and cross-domain Text-to-SQL generation . they propose re-ranking SQL queries based on domain knowledge and a graph-guided SQL generator .
Outcome: The proposed framework achieves state-of-the-art results on the Spider and Spider-DK benchmarks.

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