FRCL-MNER: A Finer Grained Rank-Based Contrastive Learning Framework for Multimodal NER [0.03%]
FRCL-MNER:一种多模态命名实体识别的更细粒度的基于排序的对比学习框架
Tianwei Yan,Shan Zhao,Wentao Ma et al.
Tianwei Yan et al.
Multimodal named entity recognition (MNER) is an emerging field that aims to automatically detect named entities and classify their categories, utilizing input text and auxiliary resources such as images. While previous studies have leverag...
Persistent Excitation of Improved RBF Neural Networks: Neuron Dynamic-Growing Strategy [0.03%]
改进的RBF神经网络的持续激励：神经元动态增长策略
Min Wang,Mingyu Wang,Chenguang Yang
Min Wang
This brief proposes a novel neuron dynamic-growing (NDG) strategy for radial basis function neural networks (RBF NNs). Only one neuron is selected in advance relying on the system initial states, and other neurons are dynamically generated ...
Mingxiang Liao,Fang Wan,Zonghao Guo et al.
Mingxiang Liao et al.
Pointly supervised instance segmentation (PSIS) remains a challenging task when appearance variances across object parts cause semantic inconsistency. In this article, we propose a hierarchical AttentionShift approach, to solve the semantic...
Bin Sun,Zuxiang Long,Ziyu Ma et al.
Bin Sun et al.
Knowledge distillation (KD) improves the performance of a compact student network by transferring learned knowledge from a cumbersome teacher network. In the existing approaches, the multiscale feature knowledge is transferred via densely c...
Backdoor Attacks and Countermeasures in Natural Language Processing Models: A Comprehensive Security Review [0.03%]
自然语言处理模型中的后门攻击及其对策：一项全面的安全审查
Pengzhou Cheng,Zongru Wu,Wei Du et al.
Pengzhou Cheng et al.
Language models (LMs) are becoming increasingly popular in real-world applications. Outsourcing model training and data hosting to third-party platforms has become a standard method for reducing costs. In such a situation, the attacker can ...
Meta Learning Task Representation in Multiagent Reinforcement Learning: From Global Inference to Local Inference [0.03%]
多智能体强化学习中的元学习任务表示：从全局推断到局部推断
Zijie Zhao,Yuqian Fu,Jiajun Chai et al.
Zijie Zhao et al.
Multiagent meta reinforcement learning (MAMRL) enables multiagent systems (MASs) to adapt to multiple tasks. However, partial observability poses a significant challenge by hindering efficient task inference from agents' limited local exper...
Sajjad Kachuee,Mohammad Sharifkhani
Sajjad Kachuee
Adjusting the latency, power, and accuracy of natural language understanding models is a desirable objective of an efficient architecture. This article proposes an efficient Transformer architecture that adjusts the inference computational ...
Random Orthogonal Additive Filters: A Solution to the Vanishing/Exploding Gradient of Deep Neural Networks [0.03%]
随机正交相加滤波器：解决深层神经网络的消失/爆炸梯度问题
Andrea Ceni
Andrea Ceni
Since the recognition in the early 1990s of the vanishing/exploding (V/E) gradient issue plaguing the training of neural networks (NNs), significant efforts have been exerted to overcome this obstacle. However, a clear solution to the V/E i...
Changtian Ying,Qi Li,Chen Wang et al.
Changtian Ying et al.
Graph neural networks (GNNs) have significantly advanced our ability to mine structured data, playing a central role in areas such as social networks and recommendation systems. However, while most GNN-based methods focus on learning node r...
When Heterophily Meets Heterogeneous Graphs: Latent Graphs Guided Unsupervised Representation Learning [0.03%]
当异质性遇到异构图：潜图引导的无监督表示学习
Zhixiang Shen,Zhao Kang
Zhixiang Shen
Unsupervised heterogeneous graph representation learning (UHGRL) has gained increasing attention due to its significance in handling practical graphs without labels. However, heterophily has been largely ignored, despite its ubiquitous pres...