Papers by Kejun Wu

2 papers
TeleMelody: Lyric-to-Melody Generation with a Template-Based Two-Stage Method (2022.emnlp-main)

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Challenge: a new lyric-to-melody generation system bridges the gap between lyrics and melodies . previous generation systems lack paired data and lack of control on generated melodie.
Approach: They develop a lyric-to-melody generation system with music template to bridge the gap between lyrics and melodies.
Outcome: The proposed system bridges the gap between lyrics and melodies by using music template.
CaDRL: Document-level Relation Extraction via Context-aware Differentiable Rule Learning (2025.coling-main)

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Challenge: Existing methods for document-level relation extraction (DocRE) lack logic and transparency.
Approach: They propose a Context-aware differentiable rule learning framework that learns the doc-specific logical rule to avoid suboptimal constraints.
Outcome: The proposed framework outperforms existing rule-based frameworks on three DocRE datasets.

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