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Membership Inference Attacks against Fine-tuned Large Language Models via Self-prompt Calibration
Membership Inference Attacks (MIA) aim to infer whether a target data record has been utilized for model training or not.
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- Europe > Austria > Vienna (0.14)
- North America > Canada > Quebec > Montreal (0.04)
- Asia > Middle East > UAE > Abu Dhabi Emirate > Abu Dhabi (0.04)
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- Research Report > Experimental Study (1.00)
- Research Report > New Finding (0.92)
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- Information Technology > Artificial Intelligence > Natural Language > Large Language Model (1.00)
- Information Technology > Artificial Intelligence > Natural Language > Chatbot (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Performance Analysis > Accuracy (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (1.00)
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- North America > United States > Pennsylvania > Philadelphia County > Philadelphia (0.04)
- Asia > Taiwan > Taiwan Province > Taipei (0.04)
- Asia > Japan > Honshū > Kantō > Tokyo Metropolis Prefecture > Tokyo (0.04)
Technology:
- Information Technology > Artificial Intelligence > Vision (1.00)
- Information Technology > Artificial Intelligence > Natural Language (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (0.68)
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- Oceania > New Zealand (0.04)
- Asia > India (0.04)
- Asia > Bangladesh (0.04)
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- Government (0.68)
- Leisure & Entertainment (0.45)
- Health & Medicine (0.45)
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- North America > United States > Pennsylvania > Philadelphia County > Philadelphia (0.04)
- North America > United States > Maryland > Baltimore (0.04)
- North America > United States > Florida > Broward County > Fort Lauderdale (0.04)
Technology:
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- South America > Chile > Santiago Metropolitan Region > Santiago Province > Santiago (0.04)
- North America > United States > Washington > King County > Seattle (0.04)
- North America > United States > Pennsylvania > Philadelphia County > Philadelphia (0.04)
- Europe > Spain > Catalonia > Barcelona Province > Barcelona (0.04)
Industry:
- Leisure & Entertainment (1.00)
- Media > Music (0.93)
Technology:
DASpeech: Directed Acyclic Transformer for Fast and High-quality Speech-to-Speech Translation Qingkai Fang 1,2, Y an Zhou 1,2, Y ang Feng 1,2 1
In this paper, we propose DASpeech, a non-autoregressive direct S2ST model which realizes both fast and high-quality S2ST.
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- Europe > Austria > Vienna (0.14)
- Asia > South Korea > Incheon > Incheon (0.04)
- North America > Canada > British Columbia > Vancouver (0.04)
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- Information Technology > Artificial Intelligence > Speech > Speech Recognition (1.00)
- Information Technology > Artificial Intelligence > Representation & Reasoning (1.00)
- Information Technology > Artificial Intelligence > Natural Language > Machine Translation (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (0.93)
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- North America > Canada > Quebec > Montreal (0.04)
- Europe > Italy > Calabria > Catanzaro Province > Catanzaro (0.04)
- North America > United States > Pennsylvania > Philadelphia County > Philadelphia (0.04)
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- Research Report > Experimental Study (1.00)
- Research Report > New Finding (0.68)
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- North America > United States > Minnesota > Hennepin County > Minneapolis (0.14)
- Europe > Austria > Vienna (0.14)
- Europe > Germany > Rhineland-Palatinate > Kaiserslautern (0.04)
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- North America > United States > California > San Diego County > San Diego (0.04)
- Europe > Netherlands > Drenthe > Assen (0.04)
- North America > United States > Pennsylvania > Philadelphia County > Philadelphia (0.04)
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Technology:
- Information Technology > Artificial Intelligence > Vision (1.00)
- Information Technology > Artificial Intelligence > Representation & Reasoning (1.00)
- Information Technology > Artificial Intelligence > Robots (0.93)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (0.68)
Simple, Scalable and Effective Clustering via One-Dimensional Projections
In large-scale applications, datasets often contain billions of high-dimensional points. Grouping similar data points into clusters is crucial for understanding and organizing datasets.
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- Europe > Austria > Vienna (0.14)
- North America > United States > California > San Francisco County > San Francisco (0.14)
- Asia > Afghanistan > Parwan Province > Charikar (0.04)
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