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Batch-in-Batch: a new adversarial training framework for initial perturbation and sample selection

Autor: Wu, Yinting, Peng, Pai, Cai, Bo, Li, Le

Adversarial training methods commonly generate independent initial perturbation for adversarial samples from a simple uniform distribution, and obtain the training batch for the classifier without selection. In this work, we propose a simple yet effe

Externí odkaz: http://arxiv.org/abs/2406.04070

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Akademický článek

Genome-wide enhancer RNA profiling adds molecular links between genetic variation and human cancers

Publikováno v: Military Medical Research, Vol 11, Iss 1, Pp 1-24 (2024)

Abstract Background Dysregulation of enhancer transcription occurs in multiple cancers. Enhancer RNAs (eRNAs) are transcribed products from enhancers that play critical roles in transcriptional control. Characterizing the genetic basis of eRNA expres

Externí odkaz: https://doaj.org/article/27381517e57f4c8cbe32281a2abf9fc7

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Entity-centered Cross-document Relation Extraction

Autor: Wang, Fengqi, Li, Fei, Fei, Hao, Li, Jingye, Wu, Shengqiong, Su, Fangfang, Shi, Wenxuan, Ji, Donghong, Cai, Bo

Relation Extraction (RE) is a fundamental task of information extraction, which has attracted a large amount of research attention. Previous studies focus on extracting the relations within a sentence or document, while currently researchers begin to

Externí odkaz: http://arxiv.org/abs/2210.16541

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CSSAM:Code Search via Attention Matching of Code Semantics and Structures

Autor: Hu, Yi, Cai, Bo, Yu, Yaoxiang

Despite the continuous efforts in improving both the effectiveness and efficiency of code search, two issues remained unsolved. First, programming languages have inherent strong structural linkages, and feature mining of code as text form would omit

Externí odkaz: http://arxiv.org/abs/2208.03922

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