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Hits 121 – 140 of 2.974

121
Scaling Within Document Coreference to Long Texts ...
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122
How to Split: the Effect of Word Segmentation on Gender Bias in Speech Translation ...
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123
Low-Resource Dialogue Summarization with Domain-Agnostic Multi-Source Pretraining ...
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124
Prefix-Tuning: Optimizing Continuous Prompts for Generation ...
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125
HittER: Hierarchical Transformers for Knowledge Graph Embeddings ...
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126
Ara-Women-Hate: The first Arabic Hate Speech corpus regarding Women ...
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127
Chase: A Large-Scale and Pragmatic Chinese Dataset for Cross-Database Context-Dependent Text-to-SQL ...
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128
15D: Summarization #2 ...
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129
Detecting Gender Bias using Explainability ...
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130
Explanations for CommonsenseQA: New Dataset and Models ...
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131
Societal Biases in Language Generation: Progress and Challenges ...
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132
HETFORMER: Heterogeneous Transformer with Sparse Attention for Long-Text Extractive Summarization ...
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133
Blindness to Modality Helps Entailment Graph Mining ...
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134
Efficient-FedRec: Efficient Federated Learning Framework for Privacy-Preserving News Recommendation ...
Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.223/ Abstract: News recommendation is critical for personalized news access. Most existing news recommendation methods rely on centralized storage of users' historical news click behavior data, which may lead to privacy concerns and hazards. Federated Learning is a privacy-preserving framework for multiple clients to collaboratively train models without sharing their private data. However, the computation and communication cost of directly learning many existing news recommendation models in a federated way are unacceptable for user clients. In this paper, we propose an efficient federated learning framework for privacy-preserving news recommendation. Instead of training and communicating the whole model, we decompose the news recommendation model into a large news model maintained in the server and a light-weight user model shared on both server and clients, where news representations and user model are communicated between server and clients. ...
Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing
URL: https://dx.doi.org/10.48448/y05k-v407
https://underline.io/lecture/37627-efficient-fedrec-efficient-federated-learning-framework-for-privacy-preserving-news-recommendation
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135
UserAdapter: Few-Shot User Learning in Sentiment Analysis ...
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136
9C: Question Answering #2 ...
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137
Characterizing Test Anxiety on Social Media ...
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138
Not All Negatives are Equal: Label-Aware Contrastive Loss for Fine-grained Text Classification ...
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139
GEM: Natural Language Generation, Evaluation, and Metrics - Part 2 ...
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140
Improving Graph-based Sentence Ordering with Iteratively Predicted Pairwise Orderings ...
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