Papers by Chenying Li

2 papers
MultiHiertt: Numerical Reasoning over Multi Hierarchical Tabular and Textual Data (2022.acl-long)

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Challenge: Existing benchmarks for numerical reasoning over hybrid data only include a single flat table in each document .
Approach: They propose a new benchmark with QA pairs over multi hierarchical tabular and textual data.
Outcome: The proposed model is more complex and challenging than existing benchmarks and is available on github . it uses facts retrieving to extract relevant facts from both tables and text and symbolic reasoning over retrieved facts.
FinMath: Injecting a Tree-structured Solver for Question Answering over Financial Reports (2022.lrec-1)

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Challenge: Existing models for answering complex questions require multiple-step numerical reasoning.
Approach: They propose a framework that injects a tree-structured neural model into a model to perform multi-step numerical reasoning.
Outcome: The proposed framework improves the previous best model by 8.5% absolute for Exact Match (EM) score and 6.1% absolute for numeracy-focused F1 score.

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