195 citations · 327 across the 19 of their papers we have counts for
6 papers · 1 filter
ERNIE 3.0 Titan: Exploring Larger-scale Knowledge Enhanced Pre-training for Language Understanding and Generation
Shuohuan Wang, Yu Sun, Yang Xiang +26
Pre-trained language models have achieved state-of-the-art results in various Natural Language Processing (NLP) tasks. GPT-3 has shown that scaling up pre-trained language models c…
Generalization Techniques Empirically Outperform Differential Privacy against Membership Inference
Jiaxiang Liu, Simon Oya, Florian Kerschbaum
Differentially private training algorithms provide protection against one of the most popular attacks in machine learning: the membership inference attack. However, these privacy a…
ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation
Yu Sun, Shuohuan Wang, Shikun Feng +19
Pre-trained models have achieved state-of-the-art results in various Natural Language Processing (NLP) tasks. Recent works such as T5 and GPT-3 have shown that scaling up pre-train…
ERNIE-Tiny : A Progressive Distillation Framework for Pretrained Transformer Compression
Weiyue Su, Xuyi Chen, Shikun Feng +6
Pretrained language models (PLMs) such as BERT adopt a training paradigm which first pretrain the model in general data and then finetune the model on task-specific data, and have…
Pre-trained Language Model for Web-scale Retrieval in Baidu Search
Yiding Liu, Guan Huang, Jiaxiang Liu +7
Retrieval is a crucial stage in web search that identifies a small set of query-relevant candidates from a billion-scale corpus. Discovering more semantically-related candidates in…
Pose Discrepancy Spatial Transformer Based Feature Disentangling for Partial Aspect Angles SAR Target Recognition
Zaidao Wen, Jiaxiang Liu, Zhunga Liu +1
This letter presents a novel framework termed DistSTN for the task of synthetic aperture radar (SAR) automatic target recognition (ATR). In contrast to the conventional SAR ATR alg…