arXiv subjects

Syed Muhammad Ali

Publications and source records attributed to Syed Muhammad Ali.

3 recordsLinked to original sources

arXiv2026

UrduLM: A Resource-Efficient Monolingual Urdu Language Model

Urdu, spoken by 230 million people worldwide, lacks dedicated transformer-based language models and curated corpora. While multilingual models provide limited Urdu support, they suffer from poor performance, high computational costs, and cultural inaccuracies due to insufficient training data. To address these challenges, we present UrduLM, a pretrained Urdu monolingual language model trained in low-resource settings. We curate a 33GB Urdu corpus from diverse sources, develop a custom BPE tokenizer that reduces tokenization overhead by atleast 20-30% compared to multilingual alternatives, and pretrain a 100M-parameter decoder-only model. In few-shot evaluations, UrduLM achieves competitive performance with multilingual models up to 30x its size, reaching 66.6% accuracy on sentiment classification and BLEU scores exceeding 30 on grammar correction tasks. The complete methodology -- including corpus, tokenizer, model weights, and evaluation benchmarks -- is released openly to establish a baseline for Urdu NLP research and provide a scalable framework for other underrepresented languages.

cs.CL↗

arXiv2024

Analysis of Different Algorithmic Design Techniques for Seam Carving

Seam carving, a content-aware image resizing technique, has garnered significant attention for its ability to resize images while preserving important content. In this paper, we conduct a comprehensive analysis of four algorithmic design techniques for seam carving: brute-force, greedy, dynamic programming, and GPU-based parallel algorithms. We begin by presenting a theoretical overview of each technique, discussing their underlying principles and computational complexities. Subsequently, we delve into empirical evaluations, comparing the performance of these algorithms in terms of runtime efficiency. Our experimental results provide insights into the theoretical complexities of the design techniques.

math.NA↗

arXiv2023

On the Analysis of AoI-Reliability Tradeoff in Heterogeneous IIoT Networks

Age of information (AoI) and reliability are two critical metrics to support real-time applications in Industrial Internet of Things (IIoT). These metrics reflect different concepts of timely delivery of sensor information. Monitoring traffic serves to maintain fresh status updates, expressed in a low AoI, which is important for proper control and actuation actions. On the other hand, safety-critical information, e.g., emergency alarms, is generated sporadically and must be delivered with high reliability within a predefined deadline. In this work, we investigate the AoI-reliability trade-off in a real-time monitoring scenario that supports two traffic flows, namely AoI-oriented traffic and deadline-oriented traffic. Both traffic flows are transmitted to a central controller over an unreliable shared channel. We derive expressions of the average AoI for the AoI-oriented traffic and reliability, represented by Packet Loss Probability (PLP), for the deadline-oriented traffic using Discrete-Time Markov Chain (DTMC). We also conduct discrete-event simulations in MATLAB to validate the analytical results and evaluate the interaction between the two types of traffic flows. The results clearly demonstrate the tradeoff between the AoI and PLP in such heterogeneous IIoT networks and give insights on how to configure the network to achieve a target pair of AoI and PLP.

cs.NI↗