Zobrazeno 1 - 10
of 29 207
pro vyhledávání: '"Raza, P."'
This paper presents an analysis of biases in open-source Large Language Models (LLMs) across various genders, religions, and races. We introduce a methodology for generating a bias detection dataset using seven bias triggers: General Debate, Position
Externí odkaz:
http://arxiv.org/abs/2410.12499
Autor:
Girelli, Anita, Bin, Maddalena, Filianina, Mariia, Dargasz, Michelle, Anthuparambil, Nimmi Das, Möller, Johannes, Zozulya, Alexey, Andronis, Iason, Timmermann, Sonja, Berkowicz, Sharon, Retzbach, Sebastian, Reiser, Mario, Raza, Agha Mohammad, Kowalski, Marvin, Akhundzadeh, Mohammad Sayed, Schrage, Jenny, Woo, Chang Hee, Senft, Maximilian D., Reichart, Lara Franziska, Leonau, Aliaksandr, Rajaiah, Prince Prabhu, Chèvremont, William, Seydel, Tilo, Hallmann, Jörg, Rodriguez-Fernandez, Angel, Pudell, Jan-Etienne, Brausse, Felix, Boesenberg, Ulrike, Wrigley, James, Youssef, Mohamed, Lu, Wei, Jo, Wonhyuk, Shayduk, Roman, Madsen, Anders, Lehmkühler, Felix, Paulus, Michael, Zhang, Fajun, Schreiber, Frank, Gutt, Christian, Perakis, Fivos
Understanding protein motion within the cell is crucial for predicting reaction rates and macromolecular transport in the cytoplasm. A key question is how crowded environments affect protein dynamics through hydrodynamic and direct interactions at mo
Externí odkaz:
http://arxiv.org/abs/2410.08873
Active learning (AL) optimizes data labeling efficiency by selecting the most informative instances for annotation. A key component in this procedure is an acquisition function that guides the selection process and identifies the suitable instances f
Externí odkaz:
http://arxiv.org/abs/2410.04275
Advancements in generative modeling are pushing the state-of-the-art in synthetic medical image generation. These synthetic images can serve as an effective data augmentation method to aid the development of more accurate machine learning models for
Externí odkaz:
http://arxiv.org/abs/2409.19436
Autor:
Chowdhury, Talal Ahmed, Izubuchi, Taku, Kamruzzaman, Methun, Karthik, Nikhil, Khan, Tanjib, Liu, Tianbo, Paul, Arpon, Schoenleber, Jakob, Sufian, Raza Sabbir
Lattice quantum chromodynamics (QCD) calculations share a defining challenge by requiring a small finite range of spatial separation $z$ between quark/gluon bilinears for controllable power corrections in the perturbative QCD factorization, and a lar
Externí odkaz:
http://arxiv.org/abs/2409.17234
Autor:
Arif, Samee, Arif, Taimoor, Haroon, Muhammad Saad, Khan, Aamina Jamal, Raza, Agha Ali, Athar, Awais
This paper introduces the concept of an education tool that utilizes Generative Artificial Intelligence (GenAI) to enhance storytelling for children. The system combines GenAI-driven narrative co-creation, text-to-speech conversion, and text-to-video
Externí odkaz:
http://arxiv.org/abs/2409.11261
This paper presents a comprehensive evaluation of Urdu Automatic Speech Recognition (ASR) models. We analyze the performance of three ASR model families: Whisper, MMS, and Seamless-M4T using Word Error Rate (WER), along with a detailed examination of
Externí odkaz:
http://arxiv.org/abs/2409.11252
Autor:
Mirza, Ali Raza, Al-Khalili, Jim
We investigate the role of non-selective measurement on the estimation of system-environment parameters. Projective measurement is the popular method of initial state preparation which always prepares a pure state. However, in various physical situat
Externí odkaz:
http://arxiv.org/abs/2409.09134
In medical image classification, supervised learning is challenging due to the lack of labeled medical images. Contrary to the traditional \textit{modus operandi} of pre-training followed by fine-tuning, this work leverages the visual-textual alignme
Externí odkaz:
http://arxiv.org/abs/2409.02729
We introduce Spurfies, a novel method for sparse-view surface reconstruction that disentangles appearance and geometry information to utilize local geometry priors trained on synthetic data. Recent research heavily focuses on 3D reconstruction using
Externí odkaz:
http://arxiv.org/abs/2408.16544