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Multi-News: a Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical Model
TLDR
This paper introduces Multi-News, the first large-scale MDS news dataset, and proposes an end-to-end model which incorporates a traditional extractive summarization model with a standard SDS model and achieves competitive results on MDS datasets. Expand
SParC: Cross-Domain Semantic Parsing in Context
TLDR
An in-depth analysis of SParC is provided and it is shown that it introduces new challenges compared to existing datasets and requires generalization to unseen domains due to its cross-domain nature and the unseen databases at test time. Expand
CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases
TLDR
CoSQL is presented, a corpus for building cross-domain, general-purpose database (DB) querying dialogue systems that includes SQL-grounded dialogue state tracking, response generation from query results, and user dialogue act prediction and a set of strong baselines are evaluated. Expand
Learning to Detect Malicious Clients for Robust Federated Learning
TLDR
This work proposes a new framework for robust federated learning where the central server learns to detect and remove the malicious model updates using a powerful detection model, leading to targeted defense. Expand
BatchCrypt: Efficient Homomorphic Encryption for Cross-Silo Federated Learning
TLDR
BatchCrypt is presented, a system solution for cross-silo FL that substantially reduces the encryption and communication overhead caused by HE, and develops new quantization and encoding schemes along with a novel gradient clipping technique. Expand
Abnormal Client Behavior Detection in Federated Learning
TLDR
This work generates low-dimensional surrogates of model weight vectors and uses them to perform anomaly detection at the server side, and shows that the proposed detection-based approach significantly outperforms the conventional defense-based methods. Expand