Zobrazeno 1 - 10
of 26 690
pro vyhledávání: '"Awais, A"'
Autor:
Liaquat, Salman, Butt, Faran Awais, Nasir, Faryal Aurooj, Naqvi, Ijaz Haider, Mahyuddin, Nor Muzlifah, Muqaibel, Ali Hussein, Alawsh, Saleh
Metallic materials such as brass, copper, and aluminum are used in numerous applications, including industrial manufacturing. The vibration characteristics of these objects are unique and can be used to identify these objects from a distance. This re
Externí odkaz:
http://arxiv.org/abs/2410.19632
Contrastive learning, a prominent approach to representation learning, traditionally assumes positive pairs are closely related samples (the same image or class) and negative pairs are distinct samples. We challenge this assumption by proposing to le
Externí odkaz:
http://arxiv.org/abs/2410.18200
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:
Awais, Muhammad, Alharthi, Ali Husain Salem Abdulla, Kumar, Amandeep, Cholakkal, Hisham, Anwer, Rao Muhammad
Significant progress has been made in advancing large multimodal conversational models (LMMs), capitalizing on vast repositories of image-text data available online. Despite this progress, these models often encounter substantial domain gaps, hinderi
Externí odkaz:
http://arxiv.org/abs/2410.08405
Autor:
Nawaz, Umair, Awais, Muhammad, Gani, Hanan, Naseer, Muzammal, Khan, Fahad, Khan, Salman, Anwer, Rao Muhammad
Capitalizing on vast amount of image-text data, large-scale vision-language pre-training has demonstrated remarkable zero-shot capabilities and has been utilized in several applications. However, models trained on general everyday web-crawled data of
Externí odkaz:
http://arxiv.org/abs/2410.01407
In most existing multi-view modeling scenarios, cross-view correspondence (CVC) between instances of the same target from different views, like paired image-text data, is a crucial prerequisite for effortlessly deriving a consistent representation. N
Externí odkaz:
http://arxiv.org/abs/2409.14882
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
Autor:
Arif, Samee, Farid, Sualeha, Khan, Aamina Jamal, Abbas, Mustafa, Raza, Agha Ali, Athar, Awais
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
This paper presents a novel methodology for generating synthetic Preference Optimization (PO) datasets using multi-agent workflows. We evaluate the effectiveness and potential of these workflows in automating and enhancing the dataset generation proc
Externí odkaz:
http://arxiv.org/abs/2408.08688
Autor:
Hanif, Asif, Shamshad, Fahad, Awais, Muhammad, Naseer, Muzammal, Khan, Fahad Shahbaz, Nandakumar, Karthik, Khan, Salman, Anwer, Rao Muhammad
Medical foundation models are gaining prominence in the medical community for their ability to derive general representations from extensive collections of medical image-text pairs. Recent research indicates that these models are susceptible to backd
Externí odkaz:
http://arxiv.org/abs/2408.07440