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Yuxuan Ye

2 accepted papers

2025

Optimising Factual Consistency in Summarisation via Preference Learning from Multiple Imperfect Metrics

EMNLP 2025

Reinforcement learning with evaluation metrics as rewards is widely used to enhance specific capabilities of language models. However, for tasks such as factually consistent summarisation, existing metrics remain underdeveloped, limiting their effectiveness as signals for shaping model behaviour.Whi

Cited by 0SourcePDFScholar
2025

Quantifying Compositionality of Classic and State-of-the-Art Embeddings

EMNLP 2025

For language models to generalize correctly to novel expressions, it is critical that they exploit access compositional meanings when this is justified. Even if we don’t know what a “pelp” is, we can use our knowledge of numbers to understand that “ten pelps” makes more pelps than “two pelps”. Stati