Papers by Mi Wen

3 papers
A Dialogue-based Information Extraction System for Medical Insurance Assessment (2021.findings-acl)

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Challenge: a new system that integrates advanced NLP technologies for medical insurance assessment is proposed . the average time cost of the procedure is reduced from 55 minutes to 35 minutes .
Approach: They propose a dialogue-based information extraction system that integrates advanced NLP technologies for medical insurance assessment.
Outcome: The proposed system reduces the time cost of the procedure from 55 minutes to 35 minutes and saves 30% human resources cost compared with the previous offline procedure.
R2D2: Recursive Transformer based on Differentiable Tree for Interpretable Hierarchical Language Modeling (2021.acl-long)

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Challenge: Existing models with stacked layers do not explicitly model hierarchical structure of language understanding.
Approach: They propose a recursive Transformer model based on differentiable CKY style binary trees to emulate hierarchical composition process.
Outcome: The proposed model can predict words given their left and right abstraction nodes.
ReasoningGuard: Safeguarding Large Reasoning Models with Inference-time Safety Aha Moments (2026.acl-long)

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Challenge: Existing defenses for Large Reasoning Models (LRMs) depend on costly fine-tuning and additional expert knowledge, which limits their scalability.
Approach: They propose an inference-time safeguard for Large Reasoning Models that injects safety aha moments into the reasoning process to guide the model towards harmless yet helpful reasoning.
Outcome: The proposed safeguard outperforms nine existing safeguards while avoiding common exaggerated safety issues.

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