Papers by Qiwang Hu

2 papers
Extracting Military Event Temporal Relations via Relative Event Time Prediction and Virtual Adversarial Training (2025.findings-naacl)

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Challenge: Existing models for extracting event temporal relations typically compare the relative times of events directly, neglecting the contextual information between event pairs.
Approach: They propose a temporal relationship extraction model based on relative event time prediction and virtual adversarial training, MFRV.
Outcome: The proposed model can capture and infer temporal relationships and can be generalized by generating adversarial samples.
EventRelBench: A Comprehensive Benchmark for Evaluating Event Relation Understanding in Large Language Models (2025.findings-emnlp)

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Challenge: Existing LLMs fail to capture event relationships, despite advances in NLP . a new benchmark is being developed to assess LLM's ability to extract event relationships .
Approach: They propose a benchmark to assess LLMs' ability to extract event relations . EventRelBench comprises 35K diverse event relation questions .
Outcome: The benchmark EventRelBench measures the performance of large language models on event relation extraction tasks.

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