Papers by Zhuoer Feng

2 papers
LOT: A Story-Centric Benchmark for Evaluating Chinese Long Text Understanding and Generation (2022.tacl-1)

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Challenge: Existing benchmarks for natural language processing focus on understanding or generating short texts . lack of standardized benchmarks makes it difficult to assess and compare models .
Approach: They propose a story-centric benchmark for Chinese long text modeling that aggregates two understanding tasks and two generation tasks.
Outcome: The proposed model outperforms similar-sized models on understanding and generation tasks.
OpenMEVA: A Benchmark for Evaluating Open-ended Story Generation Metrics (2021.acl-long)

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Challenge: Existing automatic metrics are observed to correlate poorly with human evaluation.
Approach: They propose to use OpenMEVA to evaluate open-ended story generation metrics.
Outcome: The proposed test suite assesses the capabilities of open-ended story generation metrics on annotated stories and auto-constructed test examples.

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