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Jingchao Yang

2 accepted papers

2025

HighMATH: Evaluating Math Reasoning of Large Language Models in Breadth and Depth

EMNLP 2025

With the rapid development of large language models (LLMs) in math reasoning, the accuracy of models on existing math benchmarks has gradually approached 90% or even higher. More challenging math benchmarks are hence urgently in need to satisfy the increasing evaluation demands. To bridge this gap,

2022

Seq2Path: Generating Sentiment Tuples as Paths of a Tree

ACL 2022findings

Aspect-based sentiment analysis (ABSA) tasks aim to extract sentiment tuples from a sentence. Recent generative methods such as Seq2Seq models have achieved good performance by formulating the output as a sequence of sentiment tuples. However, the orders between the sentiment tuples do not naturally…

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