Papers by Tuan-Phong Nguyen

2 papers
Enabling LLM Knowledge Analysis via Extensive Materialization (2025.acl-long)

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Challenge: Large language models (LLMs) have majorly advanced NLP and AI, and a major success factor is their internalized factual knowledge.
Approach: They propose a method to comprehensively materialize an LLM’s factual knowledge through recursive querying and result consolidation.
Outcome: The proposed method provides constructive insights into the scope and structure of LLM knowledge (or beliefs) it provides scale, accuracy, bias, cutoff and consistency at the same time.
Inside ASCENT: Exploring a Deep Commonsense Knowledge Base and its Usage in Question Answering (2021.acl-demo)

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Challenge: Structured knowledge bases (KBs) are a great way to explain and interpret outputs of systems leveraging the resources.
Approach: They propose a web portal that allows users to understand its construction process and explore its content.
Outcome: The proposed framework allows users to understand its construction process, explore its content, and observe its impact in the use case of question answering.

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