Papers by Hichem Ammar Khodja

2 papers
Factual Knowledge Assessment of Language Models Using Distractors (2025.coling-main)

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Challenge: Language models encode extensive factual knowledge within their parameters.
Approach: They propose a new interpretable knowledge assessment method that leverages distractors to provide incorrect alternatives to the correct answer.
Outcome: The proposed method shows that it is aligned with human judgment and stronger robustness to verbalization artifacts.
WikiFactDiff: A Large, Realistic, and Temporally Adaptable Dataset for Atomic Factual Knowledge Update in Causal Language Models (2024.lrec-main)

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Challenge: Factual update is a task of inserting, replacing, or removing facts in large language models.
Approach: They present a dataset that describes the evolution of factual knowledge between two dates as a collection of simple facts divided into three categories: new, obsolete, and static.
Outcome: The proposed dataset compares the state of the Wikidata knowledge base at 4 January 2021 and 27 February 2023.

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