Papers by Dung Nguyen

3 papers
Continual Safety Alignment via Gradient-Based Sample Selection (2026.findings-acl)

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Challenge: Large language models require continuous adaptation to new domains, tasks, and evolving requirements.
Approach: They propose a gradient-based sample selection method that filters high-gradient samples during fine-tuning.
Outcome: The proposed method significantly improves alignment preservation while maintaining competitive task performance on continual domain tasks.
The Vault: A Comprehensive Multilingual Dataset for Advancing Code Understanding and Generation (2023.findings-emnlp)

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Challenge: Open-source dataset of code-text pairs for training large language models to understand code is outperforms other datasets for code generation and understanding tasks.
Approach: They propose to extract high-quality code-text pairs from a dataset of 43 million pairs . they use rules and deep learning to ensure that the code-sampled samples contain high-quality pairs a .
Outcome: The Vault dataset outperforms existing models on common coding tasks . authors hope the results will propel AI research and software development forward .
Towards Safer Operations: An Expert-involved Dataset of High-Pressure Gas Incidents for Preventing Future Failures (2023.emnlp-industry)

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Challenge: Existing datasets for incident management tasks are labor-intensive and time-consuming.
Approach: They propose a new IncidentAI dataset for safety prevention that includes three tasks . they argue that NLP techniques are beneficial for analyzing incident reports .
Outcome: The proposed dataset shows that NLP techniques are beneficial for analyzing incident reports to prevent future failures.

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