Papers by Siyao Liu

5 papers
Guiding the Growth: Difficulty-Controllable Question Generation through Step-by-Step Rewriting (2021.acl-long)

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Challenge: Existing QG systems perform substantially worse in answering multi-hop questions than single-hop ones.
Approach: They propose a framework that progressively increases question difficulty through step-by-step rewriting under the guidance of an extracted reasoning chain.
Outcome: The proposed framework increases question difficulty through step-by-step rewriting under the guidance of an extracted reasoning chain.
GCDT: A Chinese RST Treebank for Multigenre and Multilingual Discourse Parsing (2022.aacl-short)

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Challenge: GCDT is the largest hierarchical discourse treebank for Mandarin Chinese in the framework of Rhetorical Structure Theory (RST).
Approach: They propose to use a Chinese hierarchical discourse treebank to parse Mandarin Chinese using relation inventory and a multilingual training program.
Outcome: The proposed dataset includes state-of-the-art scores for Chinese RST parsing and RST Parsing on the English GUM dataset, using cross-lingual training in Chinese and English with multilingual embeddings.
CodeContests+: High-Quality Test Case Generation for Competitive Programming (2025.findings-emnlp)

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Challenge: Competitive programming has become a key task for training and evaluating large language models . but test cases of competitive programming problems are often difficult to obtain .
Approach: They propose an LLM-based agent system that creates high-quality test cases for competitive programming problems.
Outcome: The proposed system improves code tests on a CodeContests dataset with pass/fail labels.
A Corpus of Adpositional Supersenses for Mandarin Chinese (2020.lrec-1)

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Challenge: Adpositions are frequent markers of semantic relations, but they are highly ambiguous and vary significantly from language to language.
Approach: They propose to annotate Chinese adpositions in a corpus with all aforementioned supersenses . they adapt a framework that defined a set of supersens according to ostensibly language-independent criteria .
Outcome: The proposed corpus is the first to be broadly annotated with adposition semantics in Chinese . it shows that the supersense categories are well-suited to Chinese adepositions despite syntactic differences from English .
AMALGUM – A Free, Balanced, Multilayer English Web Corpus (2020.lrec-1)

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Challenge: a corpus of 4M tokens is available online with a large number of high-quality annotation layers.
Approach: They propose to use a genre-balanced English web corpus with multiple annotation layers . they harness knowledge from multiple annotation layer to achieve a "better than NLP" benchmark .
Outcome: The proposed corpus is genre-balanced and features high-quality automatic annotation layers.

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