Papers by Kexiang Wang

3 papers
An Anchor-Based Automatic Evaluation Metric for Document Summarization (2020.coling-main)

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Challenge: Existing reference-based evaluation metrics such as ROUGE have their own drawbacks.
Approach: They propose a protocol for a reference-based automatic evaluation metric that requires the endorsement of source document.
Outcome: The proposed metric is anchored on source document and has higher correlation with human judgments.
A Spectral Method for Unsupervised Multi-Document Summarization (2020.emnlp-main)

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Challenge: a spectral-based hypothesis is proposed for the unsupervised task of multi-document summarization.
Approach: They propose a spectral-based hypothesis that a summary candidate's spectral impact is closely linked to its spectre.
Outcome: The proposed method has a competitive result compared to state-of-the-art systems.
UEGP: Unified Expert-Guided Pre-training for Knowledge Rekindle (2024.findings-naacl)

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Challenge: Existing paradigms for pre-training and fine-tuning have limitations . knowledge rekindle aims to break through performance upper bounds of experts without introducing additional annotated data.
Approach: They propose a new paradigm for pre-training and fine-tuning that aims to re-incorporate the fine- tuned expert model into the training cycle and break through performance upper bounds of experts.
Outcome: The proposed model breaks through performance upper bounds of experts without additional annotated data.

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