Zobrazeno 1 - 10
of 683
pro vyhledávání: '"Züfle A"'
Autor:
Züfle, Maike, Niehues, Jan
Large language models (LLMs) excel in natural language processing but adapting these LLMs to speech processing tasks efficiently is not straightforward. Direct task-specific fine-tuning is limited by overfitting risks, data requirements, and computat
Externí odkaz:
http://arxiv.org/abs/2412.15712
Autor:
Seshagiri, Vishwanath, Balyan, Siddharth, Anand, Vaastav, Dhole, Kaustubh, Sharma, Ishan, Wildani, Avani, Cambronero, José, Züfle, Andreas
Logging is a critical function in modern distributed applications, but the lack of standardization in log query languages and formats creates significant challenges. Developers currently must write ad hoc queries in platform-specific languages, requi
Externí odkaz:
http://arxiv.org/abs/2412.03612
Reranking a list of candidates from a machine translation system with an external scoring model and returning the highest-scoring candidate remains a simple and effective method for improving the overall output quality. Translation scoring models con
Externí odkaz:
http://arxiv.org/abs/2411.09694
Autor:
Kennedy, Lance, Züfle, Andreas
Historically, much of the research in understanding, modeling, and mining human trajectory data has focused on where an individual stays. Thus, the focus of existing research has been on where a user goes. On the other hand, the study of how a user m
Externí odkaz:
http://arxiv.org/abs/2409.19136
Human trajectory anomaly detection has become increasingly important across a wide range of applications, including security surveillance and public health. However, existing trajectory anomaly detection methods are primarily focused on vehicle-level
Externí odkaz:
http://arxiv.org/abs/2409.18427
Source localization aims to locate information diffusion sources only given the diffusion observation, which has attracted extensive attention in the past few years. Existing methods are mostly tailored for single networks and may not be generalized
Externí odkaz:
http://arxiv.org/abs/2404.14668
Autor:
Gupta, Shrey, Park, Yongbee, Bi, Jianzhao, Gupta, Suyash, Züfle, Andreas, Wildani, Avani, Liu, Yang
Air pollution, especially particulate matter 2.5 (PM2.5), is a pressing concern for public health and is difficult to estimate in developing countries (data-poor regions) due to a lack of ground sensors. Transfer learning models can be leveraged to s
Externí odkaz:
http://arxiv.org/abs/2404.07308
With the ever-growing presence of social media platforms comes the increased spread of harmful content and the need for robust hate speech detection systems. Such systems easily overfit to specific targets and keywords, and evaluating them without co
Externí odkaz:
http://arxiv.org/abs/2311.10236
Publikováno v:
Computational Urban Science, Vol 4, Iss 1, Pp 1-20 (2024)
Abstract Urban settings require a thorough understanding of traffic patterns to best manage traffic, be prepared for emergency scenarios and to guide future infrastructure investments. In addition to analyzing collected traffic data, traffic modeling
Externí odkaz:
https://doaj.org/article/2add884956af423fb454f4dfcde04eac
Identifying anomalous human spatial trajectory patterns can indicate dynamic changes in mobility behavior with applications in domains like infectious disease monitoring and elderly care. Recent advancements in large language models (LLMs) have demon
Externí odkaz:
http://arxiv.org/abs/2310.04942