Papers by Chenda Zhang

2 papers
Beyond Sentence-level Labels: Integrating Conversational Context and Personal Experience for Natural Emotional Expression (2026.findings-acl)

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Challenge: Existing systems rely on sentence-level labels, which fails to capture the subtle nuances of human affect.
Approach: They propose to use a large-scale, context-aware speech corpus derived from multi-speaker audiobooks to generate a speech that is human-like.
Outcome: The proposed model outperforms existing methods in terms of emotional expression accuracy and naturalness.
Challenging the Assumption of Structure-based embeddings in Few- and Zero-shot Knowledge Graph Completion (2022.lrec-1)

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Challenge: Existing work on Knowledge Graph completion only uses textual descriptive data . knowledge graphs are incomplete because not every relation has been observed at the time of their construction.
Approach: They propose to use textual descriptive data to enrich benchmark data sets for Few- and Zero-shot Knowledge Graph completion tasks.
Outcome: The proposed task improves for Few- and Zero-shot scenarios with up to twofold increase in the Zero- shot setting.

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