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of 1 481
pro vyhledávání: '"Wang, jiachen"'
Forecasting weather and climate events is crucial for making appropriate measures to mitigate environmental hazards and minimize associated losses. Previous research on environmental forecasting focuses on predicting numerical meteorological variable
Externí odkaz:
http://arxiv.org/abs/2409.19058
The integration of Large Language Models (LLMs), especially ChatGPT, into education is poised to revolutionize students' learning experiences by introducing innovative conversational learning methodologies. To empower students to fully leverage the c
Externí odkaz:
http://arxiv.org/abs/2407.12423
Data Shapley provides a principled framework for attributing data's contribution within machine learning contexts. However, existing approaches require re-training models on different data subsets, which is computationally intensive, foreclosing thei
Externí odkaz:
http://arxiv.org/abs/2406.11011
Data Shapley provides a principled approach to data valuation and plays a crucial role in data-centric machine learning (ML) research. Data selection is considered a standard application of Data Shapley. However, its data selection performance has sh
Externí odkaz:
http://arxiv.org/abs/2405.03875
Industrial Internet of Things (IIoT) technologies have revolutionized industrial processes, enabling smart automation, real-time data analytics, and improved operational efficiency across diverse industry sectors. IIoT testbeds play a critical role i
Externí odkaz:
http://arxiv.org/abs/2404.17485
Generative artificial intelligence (AI) systems are trained on large data corpora to generate new pieces of text, images, videos, and other media. There is growing concern that such systems may infringe on the copyright interests of training data con
Externí odkaz:
http://arxiv.org/abs/2404.13964
Autor:
Chevalier, Alexis, Geng, Jiayi, Wettig, Alexander, Chen, Howard, Mizera, Sebastian, Annala, Toni, Aragon, Max Jameson, Fanlo, Arturo Rodríguez, Frieder, Simon, Machado, Simon, Prabhakar, Akshara, Thieu, Ellie, Wang, Jiachen T., Wang, Zirui, Wu, Xindi, Xia, Mengzhou, Xia, Wenhan, Yu, Jiatong, Zhu, Jun-Jie, Ren, Zhiyong Jason, Arora, Sanjeev, Chen, Danqi
NLP has recently made exciting progress toward training language models (LMs) with strong scientific problem-solving skills. However, model development has not focused on real-life use-cases of LMs for science, including applications in education tha
Externí odkaz:
http://arxiv.org/abs/2402.11111
This work aims to address an open problem in data valuation literature concerning the efficient computation of Data Shapley for weighted $K$ nearest neighbor algorithm (WKNN-Shapley). By considering the accuracy of hard-label KNN with discretized wei
Externí odkaz:
http://arxiv.org/abs/2401.11103
Large Language Models (LLMs) have emerged as dominant tools for various tasks, particularly when tailored for a specific target by prompt tuning. Nevertheless, concerns surrounding data privacy present obstacles due to the tuned prompts' dependency o
Externí odkaz:
http://arxiv.org/abs/2312.03724
Data valuation, a critical aspect of data-centric ML research, aims to quantify the usefulness of individual data sources in training machine learning (ML) models. However, data valuation faces significant yet frequently overlooked privacy challenges
Externí odkaz:
http://arxiv.org/abs/2308.15709