Zobrazeno 1 - 10
of 627
pro vyhledávání: '"Nejdl, Wolfgang"'
Autor:
Rasekh, Ali, Heidari, Reza, Rezaie, Amir Hosein Haji Mohammad, Sedeh, Parsa Sharifi, Ahmadi, Zahra, Mitra, Prasenjit, Nejdl, Wolfgang
With the increasing availability of diverse data types, particularly images and time series data from medical experiments, there is a growing demand for techniques designed to combine various modalities of data effectively. Our motivation comes from
Externí odkaz:
http://arxiv.org/abs/2405.15442
Publikováno v:
LREC-COLING 2024
The absence of explicitly tailored, accessible annotated datasets for educational purposes presents a notable obstacle for NLP tasks in languages with limited resources.This study initially explores the feasibility of using machine translation (MT) t
Externí odkaz:
http://arxiv.org/abs/2404.17194
Autor:
Roy, Soumyadeep, Khatua, Aparup, Ghoochani, Fatemeh, Hadler, Uwe, Nejdl, Wolfgang, Ganguly, Niloy
GPT-4 demonstrates high accuracy in medical QA tasks, leading with an accuracy of 86.70%, followed by Med-PaLM 2 at 86.50%. However, around 14% of errors remain. Additionally, current works use GPT-4 to only predict the correct option without providi
Externí odkaz:
http://arxiv.org/abs/2404.13307
Large Vision Language Models (VLMs), such as CLIP, have significantly contributed to various computer vision tasks, including object recognition and object detection. Their open vocabulary feature enhances their value. However, their black-box nature
Externí odkaz:
http://arxiv.org/abs/2404.12839
Identifying a biclique with the maximum number of edges bears considerable implications for numerous fields of application, such as detecting anomalies in E-commerce transactions, discerning protein-protein interactions in biology, and refining the e
Externí odkaz:
http://arxiv.org/abs/2309.04503
Publikováno v:
Frontiers in Artificial Intelligence and Applications, Volume 372: ECAI 2023
Large-scale language models such as DNABert and LOGO aim to learn optimal gene representations and are trained on the entire Human Reference Genome. However, standard tokenization schemes involve a simple sliding window of tokens like k-mers that do
Externí odkaz:
http://arxiv.org/abs/2307.15933
Continuous-time models such as Neural ODEs and Neural Flows have shown promising results in analyzing irregularly sampled time series frequently encountered in electronic health records. Based on these models, time series are typically processed with
Externí odkaz:
http://arxiv.org/abs/2305.06741
Autor:
Ganguly, Niloy, Fazlija, Dren, Badar, Maryam, Fisichella, Marco, Sikdar, Sandipan, Schrader, Johanna, Wallat, Jonas, Rudra, Koustav, Koubarakis, Manolis, Patro, Gourab K., Amri, Wadhah Zai El, Nejdl, Wolfgang
State-of-the-art AI models largely lack an understanding of the cause-effect relationship that governs human understanding of the real world. Consequently, these models do not generalize to unseen data, often produce unfair results, and are difficult
Externí odkaz:
http://arxiv.org/abs/2302.06975
Fairness-aware mining of massive data streams is a growing and challenging concern in the contemporary domain of machine learning. Many stream learning algorithms are used to replace humans at critical decision-making points e.g., hiring staff, asses
Externí odkaz:
http://arxiv.org/abs/2211.04812
Climate change has become one of the biggest challenges of our time. Social media platforms such as Twitter play an important role in raising public awareness and spreading knowledge about the dangers of the current climate crisis. With the increasin
Externí odkaz:
http://arxiv.org/abs/2211.03533