Papers by Jie Sui
Towards Fine-grained Text Sentiment Transfer (P19-1)
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| Challenge: | Existing methods for fine-grained text sentiment transfer only reverse the sentiment polarity of text, but they lack a robust and parallel learning algorithm. |
| Approach: | They propose a novel fine-grained text sentiment transfer task that revises a sequence to satisfy a given sentiment intensity while preserving the original semantic content. |
| Outcome: | The proposed model outperforms existing methods by a large margin in automatic evaluation and human evaluation. |
Deconstruct, Diagnose, and Deliberate: A Protocol-Adaptive Role-Specific Multi-Agent Framework for Fake News Detection (2026.findings-acl)
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| Challenge: | Existing methods for fake news detection rely on monolithic verification methods . Existing approaches often yield ambiguous verdicts due to superficial processing . |
| Approach: | They propose a protocol-adaptive role-specific multi-agent framework that decomposes verification into factual, logical, and contextual dimensions. |
| Outcome: | The proposed framework outperforms baseline methods in both predictive accuracy and explanatory quality. |