Papers by Dien Dinh

3 papers
Multi-level Community-awareness Graph Neural Networks for Neural Machine Translation (2022.coling-1)

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Challenge: Recent studies have used Graph Neural Networks (GNNs) to encode language knowledge into token embeddings.
Approach: They propose a multi-level community-awareness Graph Neural Network layer to jointly model local and global relationships between words and their linguistic roles in multiple communities.
Outcome: The proposed method reduces time complexity in very long sentences while preserving the original meaning.
ViGLUE: A Vietnamese General Language Understanding Benchmark and Analysis of Vietnamese Language Models (2024.findings-naacl)

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Challenge: Existing benchmarks for natural language understanding have been suggested, but there is a lack of such a benchmark in Vietnamese due to the difficulty in accessing datasets or the scarcity of task-specific datasets.
Approach: They propose to use a benchmark to evaluate Vietnamese language models in a variety of tasks and areas to explore the relationship between specific tasks and the number of shots.
Outcome: The proposed benchmark contains twelve tasks and encompasses over ten areas and subjects, enabling it to evaluate models comprehensively over a broad spectrum of aspects.
ViMedAQA: A Vietnamese Medical Abstractive Question-Answering Dataset and Findings of Large Language Model (2024.acl-srw)

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Challenge: Existing abstractive question-answering datasets in Vietnamese are lacking .
Approach: They propose to introduce a Vietnamese abstractive question-answering corpus to address this gap . they propose to use Vietnamese abstractives to generate answers to questions .
Outcome: The proposed dataset examines the capability of large language models in the Vietnamese medical domain, including reasoning, memorizing and awareness of essential information.

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