Papers by Xingyu Peng

3 papers
Rumor Detection on Social Media with Temporal Propagation Structure Optimization (2025.coling-main)

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Challenge: Existing methods for detecting rumors on social media neglect the temporal aspect of rumor propagation.
Approach: They propose a method that incorporates temporal information by building a weighted propagation tree and a coding tree.
Outcome: The proposed approach preserves essential structure of rumor propagation while reducing noise.
Hierarchical Information Matters: Text Classification via Tree Based Graph Neural Network (2022.coling-1)

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Challenge: Text classification is a primary task in natural language processing (NLP).
Approach: They propose a graph neural network (HINT) that makes full use of hierarchical information contained in the text for the task of text classification.
Outcome: The proposed method outperforms the state-of-the-art methods on popular benchmarks while having a simple structure and few parameters.
MetaBench: A Multi-task Benchmark for Assessing LLMs in Metabolomics (2026.acl-long)

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Challenge: Large Language Models (LLMs) have demonstrated remarkable capabilities on general text, but their proficiency in specialized scientific domains remains uncharacterized.
Approach: They evaluate the capabilities of large language models in metabolomics research using MetaBench . they found that models perform well on text generation tasks, but cross-database identifier grounding remains challenging .
Outcome: The evaluation of 25 open- and closed-source LLMs reveals distinct performance patterns across metabolomics tasks.

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