Papers with real-world models

2 papers
ENTYFI: A System for Fine-grained Entity Typing in Fictional Texts (2020.emnlp-demos)

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Challenge: ENTYFI is a web-based system for fine-grained typing of entity mentions in fictional texts.
Approach: They propose a web-based system for fine-grained typing of entity mentions in fictional texts . entity types are a core building block of current knowledge bases .
Outcome: The proposed system builds on 205 automatically induced high-quality type systems for popular fictional domains and provides recommendations towards reference type systems.
Merge Hijacking: Backdoor Attacks to Model Merging of Large Language Models (2025.acl-long)

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Challenge: Existing research on model merging focuses on optimizing model performance and minimizing backdoors.
Approach: They propose a backdoor attack targeting model merging in Large Language Models that creates a unified model for multi-domain tasks.
Outcome: The proposed attack is effective across models, merging algorithms, and tasks while maintaining utility across tasks.

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