Papers by Marco Maggini

2 papers
Clue-Instruct: Text-Based Clue Generation for Educational Crossword Puzzles (2024.lrec-main)

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Challenge: Educational crosswords are characterized by less cryptic and more factual clues than traditional puzzles.
Approach: They propose to use a dataset to generate educational clues for Large Language Models (LLMs) they use Wikipedia to gather information associated with relevant keywords and use it to generate clues.
Outcome: The proposed approach generates educational clues from a dataset containing 44,075 examples with text-keyword pairs associated with three distinct crossword clues.
From Graph to Text and Back: Semantic Fidelity in Automated Industrial Knowledge Graphs (2026.acl-industry)

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Challenge: Large Language Models (LLMs) often hallucinate entities or omit relations, posing unacceptable liability.
Approach: They propose a self-supervised round-trip pipeline to enforce strict semantic fidelity in KG-to-text generation.
Outcome: The proposed approach improves triple-extraction accuracy and verbalization faithfulness without manual annotation or massive teacher models.

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