Search Results for author:
Found 7 papers, 2 papers with code
MGDoc: Pre-training with Multi-granular Hierarchy for Document Image Understanding
In contrast, region-level models attempt to encode regions corresponding to paragraphs or text blocks into a single embedding, but they perform worse with additional word-level features.
User-Entity Differential Privacy in Learning Natural Language Models
In this paper, we introduce a novel concept of user-entity differential privacy (UeDP) to provide formal privacy protection simultaneously to both sensitive entities in textual data and data owners in learning natural language models (NLMs).
Unified Pretraining Framework for Document Understanding
Document intelligence automates the extraction of information from documents and supports many business applications.
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UniDoc: Unified Pretraining Framework for Document Understanding
Document intelligence automates the extraction of information from documents and supports many business applications.
Bit-aware Randomized Response for Local Differential Privacy in Federated Learning
In this paper, we develop BitRand, a bit-aware randomized response algorithm, to preserve local differential privacy (LDP) in federated learning (FL).
RPCL: A Framework for Improving Cross-Domain Detection with Auxiliary Tasks
Contrasted with prior work, this paper provides a complementary solution to align domains by learning the same auxiliary tasks in both domains simultaneously.
Cross-Domain Document Object Detection: Benchmark Suite and Method
We establish a benchmark suite consisting of different types of PDF document datasets that can be utilized for cross-domain DOD model training and evaluation.
