Papers with MUC
Triad-based Neural Network for Coreference Resolution (C18-1)
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| Challenge: | Entity coreference resolution aims to identify mentions that refer to the same entity. |
| Approach: | They propose a triad-based neural network system that generates affinity scores between entity mentions for coreference resolution. |
| Outcome: | The proposed system generates affinity scores between mentions for coreference resolution. |
Coreference Resolution in Full Text Articles with BERT and Syntax-based Mention Filtering (D19-57)
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| Challenge: | Existing systems for coreference resolution are difficult because of their long coreferent chains. |
| Approach: | They propose to use an existing span-based neural coreference resolution system as a baseline . they filter noisy mentions based on parse trees and integrate a highly expressive language model into the system . |
| Outcome: | The proposed system outperforms the baseline system on the CRAFT Shared Tasks 2019 task. |
Look Twice before You Leap: A Rational Framework for Localized Adversarial Text Anonymization (2026.findings-acl)
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| Challenge: | Existing LLMs rely on remote API services, which creates privacy paradoxes and suboptimal solutions with severe utility collapse. |
| Approach: | They propose a localized and training-free framework with an Attacker-Arbitrator-Anonymizer architecture that allows attackers to filter out ghost leaks. |
| Outcome: | The proposed framework achieves superior privacy-utility trade-off compared to strong baselines. |