Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Islam, Md. Mofijul"'
Autor:
Ahasan, Md Mubtasim, Fahim, Md, Mohiuddin, Tasnim, Rahman, A K M Mahbubur, Chadha, Aman, Iqbal, Tariq, Amin, M Ashraful, Islam, Md Mofijul, Ali, Amin Ahsan
Recent advancements in speech-language models have yielded significant improvements in speech tokenization and synthesis. However, effectively mapping the complex, multidimensional attributes of speech into discrete tokens remains challenging. This p
Externí odkaz:
http://arxiv.org/abs/2410.15017
Autor:
Gladstone, Alexi, Nanduru, Ganesh, Islam, Md Mofijul, Chadha, Aman, Li, Jundong, Iqbal, Tariq
One of the predominant methods for training world models is autoregressive prediction in the output space of the next element of a sequence. In Natural Language Processing (NLP), this takes the form of Large Language Models (LLMs) predicting the next
Externí odkaz:
http://arxiv.org/abs/2406.08862
Autor:
Chowdhury, Arijit Ghosh, Islam, Md Mofijul, Kumar, Vaibhav, Shezan, Faysal Hossain, Jain, Vinija, Chadha, Aman
Large Language Models (LLMs) have become a cornerstone in the field of Natural Language Processing (NLP), offering transformative capabilities in understanding and generating human-like text. However, with their rising prominence, the security and vu
Externí odkaz:
http://arxiv.org/abs/2403.04786
Autor:
Islam, Riashat, Zang, Hongyu, Tomar, Manan, Didolkar, Aniket, Islam, Md Mofijul, Arnob, Samin Yeasar, Iqbal, Tariq, Li, Xin, Goyal, Anirudh, Heess, Nicolas, Lamb, Alex
Several self-supervised representation learning methods have been proposed for reinforcement learning (RL) with rich observations. For real-world applications of RL, recovering underlying latent states is crucial, particularly when sensory inputs con
Externí odkaz:
http://arxiv.org/abs/2212.13835
Autor:
Islam, Md Mofijul, Aguilar, Gustavo, Ponnusamy, Pragaash, Mathialagan, Clint Solomon, Ma, Chengyuan, Guo, Chenlei
Publikováno v:
ACL 2022 Workshop on Representation Learning for NLP
Subword tokenization is a commonly used input pre-processing step in most recent NLP models. However, it limits the models' ability to leverage end-to-end task learning. Its frequency-based vocabulary creation compromises tokenization in low-resource
Externí odkaz:
http://arxiv.org/abs/2204.10815
Autor:
Islam, Md. Mofijul, Das, Partha, Samanta, Indranil, Roy, Barun, Mukherjee, Ayan, Mondal, Tousif
Publikováno v:
In The Microbe June 2024 3
Autor:
Islam, Md Mofijul, Iqbal, Tariq
Publikováno v:
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2020
To fluently collaborate with people, robots need the ability to recognize human activities accurately. Although modern robots are equipped with various sensors, robust human activity recognition (HAR) still remains a challenging task for robots due t
Externí odkaz:
http://arxiv.org/abs/2008.01148
With the advancement of technology, devices, which are considered non-traditional in terms of internet capabilities, are now being embedded in microprocessors to communicate and these devices are known as IoT devices. This technology has enabled hous
Externí odkaz:
http://arxiv.org/abs/1910.13625
In order to stay up to date with world issues and cutting-edge technol-ogies, the newspaper plays a crucial role. However, collecting news is not a very easy task. Currently, news publishers are collecting news from their correspond-ents through soci
Externí odkaz:
http://arxiv.org/abs/1904.00184
Autor:
Islam, Md Mofijul, Debnath, Amar, Sayeed, Tahsin Al, Setu, Jyotirmay Nag, Rahman, Md Mahmudur, Sakib, Md Sadman, Razzaque, Md Abdur, Khan, Md. Mosaddek, Shatabda, Swakkhar
Deep Learning algorithms are often used as black box type learning and they are too complex to understand. The widespread usability of Deep Learning algorithms to solve various machine learning problems demands deep and transparent understanding of t
Externí odkaz:
http://arxiv.org/abs/1811.08374