activity
20212024
most citedRobust Deep Reinforcement Learning for Extractive Legal Summarization

26 citations · 28 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2024★ 1 cited

Automatic Prompt Selection for Large Language Models

Viet-Tung Do, Van-Khanh Hoang, Duy-Hung Nguyen +5

Large Language Models (LLMs) can perform various natural language processing tasks with suitable instruction prompts. However, designing effective prompts manually is challenging a…

cs.LG2023★ 1 cited

Universal Graph Continual Learning

Thanh Duc Hoang, Do Viet Tung, Duy-Hung Nguyen +3

We address catastrophic forgetting issues in graph learning as incoming data transits from one to another graph distribution. Whereas prior studies primarily tackle one setting of…

cs.CL2023

When Giant Language Brains Just Aren't Enough! Domain Pizzazz with Knowledge Sparkle Dust

Minh-Tien Nguyen, Duy-Hung Nguyen, Shahab Sabahi +3

Large language models (LLMs) have significantly advanced the field of natural language processing, with GPT models at the forefront. While their remarkable performance spans a rang…

cs.AI2022

Make The Most of Prior Data: A Solution for Interactive Text Summarization with Preference Feedback

Duy-Hung Nguyen, Nguyen Viet Dung Nghiem, Bao-Sinh Nguyen +4

For summarization, human preference is critical to tame outputs of the summarizer in favor of human interests, as ground-truth summaries are scarce and ambiguous. Practical setting…

cs.CL2021★ 26 cited

Robust Deep Reinforcement Learning for Extractive Legal Summarization

Duy-Hung Nguyen, Bao-Sinh Nguyen, Nguyen Viet Dung Nghiem +4

Automatic summarization of legal texts is an important and still a challenging task since legal documents are often long and complicated with unusual structures and styles. Recent…