Papers by Wanqiu Long

6 papers
Shallow Discourse Annotation for Chinese TED Talks (2020.lrec-1)

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Challenge: Existing methods to annotate text with discourse properties are limited to newspaper articles and are not available in Chinese.
Approach: They propose to annotate TED talks with Chinese-related properties using the Penn Discourse TreeBank annotation style . they propose to use planned monologues instead of written text to annnotate Chinese-specific properties.
Outcome: The proposed method is able to achieve reliable results in Chinese spoken monologues, and is based on the Penn Discourse TreeBank annotation style.
Evaluating and Improving Graph to Text Generation with Large Language Models (2025.naacl-long)

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Challenge: Recent advances in large language models have revolutionized natural language processing due to their zero-and-short-shot capabilities.
Approach: They propose a tuning-free prompting approach for graph-to-text generation tasks.
Outcome: The proposed approach improves LLMs on graph-to-text generation tasks incrementally.
Facilitating Contrastive Learning of Discourse Relational Senses by Exploiting the Hierarchy of Sense Relations (2022.emnlp-main)

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Challenge: Recent studies on implicit discourse relation recognition have shown great success.
Approach: They incorporate the sense hierarchy into the recognition process and use it to select negative examples.
Outcome: The proposed approach achieves state-of-the-art performance on the task with no additional effort.
TED-CDB: A Large-Scale Chinese Discourse Relation Dataset on TED Talks (2020.emnlp-main)

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Challenge: TED-CDB dataset is a unique corpus of spoken discourse in Chinese . TED is based on the concept that discourse relations are grounded in an identifiable set of discourse connectives or Altlex expressions.
Approach: They have created a dataset that annotates TED talks in Chinese . they propose to adapt the dataset to Chinese news text to improve its performance .
Outcome: The TED-CDB dataset can improve the performance of systems for languages other than Chinese . it is adapted to features that are not present in English and can extract discourse semantic features .
Multi-Label Classification for Implicit Discourse Relation Recognition (2024.findings-acl)

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Challenge: Prior research in discourse relation recognition has treated these instances as separate examples during training, with a gold-standard prediction matching one of the labels considered correct at test time.
Approach: They propose to use multiple labels to annotate an example when multiple relations are believed to hold simultaneously.
Outcome: The proposed frameworks don't depress performance for single-label prediction.
MINTQA: A Multi-Hop Question Answering Benchmark for Evaluating LLMs on New and Long-tail Knowledge (2026.acl-long)

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Challenge: Existing studies have shown that large language models can handle knowledge with varying familiarity.
Approach: They propose a benchmark to evaluate multi-hop question answering on new and tail knowledge . they use RAG to integrate external knowledge into large language models .
Outcome: The proposed benchmark evaluates the multi-hop reasoning ability of large language models . it primarily evaluates their ability to handle knowledge with different levels of familiarity .

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