Papers by Jingyun Sun

2 papers
A Compliance Checking Framework Based on Retrieval Augmented Generation (2025.coling-main)

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Challenge: Existing text-based compliance checking methods are limited by their flexibility and lack structure.
Approach: They propose a text-based compliance checking framework based on Retrieval-Augmented Generation that integrates a static layer for storing factual knowledge, a dynamic layer for retrieval and reasoning, and an eventic graph to structurally describe regulatory information.
Outcome: The proposed framework consistently achieves state-of-the-art results across various scenarios surpassing baselines.
CDAˆ2: Counterfactual Diffusion Augmentation for Cross-Domain Adaptation in Low-Resource Sentiment Analysis (2025.coling-main)

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Challenge: Domain adaptation is widely employed in cross-domain sentiment analysis, but concerns have been raised regarding their robustness and sensitivity to data distribution shift.
Approach: They propose a framework CDA2 for cross-domain adaptation in low-resource sentiment analysis which employs counterfactual diffusion augmentation.
Outcome: The proposed framework generates high-quality counterfactual target samples and achieves state-of-the-art performance on benchmark datasets.

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