Zobrazeno 1 - 10
of 100 935
pro vyhledávání: '"Benchmark datasets"'
Hierarchical Text Classification (HTC) is a natural language processing task with the objective to classify text documents into a set of classes from a structured class hierarchy. Many HTC approaches have been proposed which attempt to leverage the c
Externí odkaz:
http://arxiv.org/abs/2411.19119
Autor:
Geissler, Daniel, Nshimyimana, Dominique, Rey, Vitor Fortes, Suh, Sungho, Zhou, Bo, Lukowicz, Paul
The research of machine learning (ML) algorithms for human activity recognition (HAR) has made significant progress with publicly available datasets. However, most research prioritizes statistical metrics over examining negative sample details. While
Externí odkaz:
http://arxiv.org/abs/2412.09037
Autor:
Gupta, Vipul, Ross, Candace, Pantoja, David, Passonneau, Rebecca J., Ung, Megan, Williams, Adina
One of the most challenging problems facing NLP today is evaluation. Some of the most pressing issues pertain to benchmark saturation, data contamination, and diversity in the quality of test examples. To address these concerns, we propose Selection
Externí odkaz:
http://arxiv.org/abs/2410.20245
This paper explores the impact of occlusions in video action detection. We facilitate this study by introducing five new benchmark datasets namely O-UCF and O-JHMDB consisting of synthetically controlled static/dynamic occlusions, OVIS-UCF and OVIS-J
Externí odkaz:
http://arxiv.org/abs/2410.19553
Autor:
Farhansyah, Mohammad Rifqi, Johari, Muhammad Zuhdi Fikri, Amiral, Afinzaki, Purwarianti, Ayu, Yuana, Kumara Ari, Wijaya, Derry Tanti
Indonesia is one of the most diverse countries linguistically. However, despite this linguistic diversity, Indonesian languages remain underrepresented in Natural Language Processing (NLP) research and technologies. In the past two years, several eff
Externí odkaz:
http://arxiv.org/abs/2411.09318
Autor:
Li, Xin, Chen, Weize, Chu, Qizhi, Li, Haopeng, Sun, Zhaojun, Li, Ran, Qian, Chen, Wei, Yiwei, Liu, Zhiyuan, Shi, Chuan, Sun, Maosong, Yang, Cheng
The need to analyze graphs is ubiquitous across various fields, from social networks to biological research and recommendation systems. Therefore, enabling the ability of large language models (LLMs) to process graphs is an important step toward more
Externí odkaz:
http://arxiv.org/abs/2409.19667
Classical point process models, such as the epidemic-type aftershock sequence (ETAS) model, have been widely used for forecasting the event times and locations of earthquakes for decades. Recent advances have led to Neural Point Processes (NPPs), whi
Externí odkaz:
http://arxiv.org/abs/2410.08226
Autor:
Sourlos, Nikos1,2 (AUTHOR), Vliegenthart, Rozemarijn1,2 (AUTHOR), Santinha, Joao3 (AUTHOR), Klontzas, Michail E.4,5 (AUTHOR), Cuocolo, Renato6 (AUTHOR), Huisman, Merel7 (AUTHOR), van Ooijen, Peter2,8 (AUTHOR) p.m.a.van.ooijen@umcg.nl
Publikováno v:
Insights into Imaging. 10/14/2024, Vol. 15 Issue 1, p1-12. 12p.
Knowledge Graph Completion (KGC) attempts to predict missing facts in a Knowledge Graph (KG). Recently, there's been an increased focus on designing KGC methods that can excel in the {\it inductive setting}, where a portion or all of the entities and
Externí odkaz:
http://arxiv.org/abs/2406.11898
Autor:
Wang, Junxiang, Zhao, Liang
We introduce GraphSL, a new library for studying the graph source localization problem. graph diffusion and graph source localization are inverse problems in nature: graph diffusion predicts information diffusions from information sources, while grap
Externí odkaz:
http://arxiv.org/abs/2405.03724