108 citations · 126 across the 11 of their papers we have counts for
11 papers
Numerical Instability and Chaos: Quantifying the Unpredictability of Large Language Models
Chashi Mahiul Islam, Alan Villarreal, Mao Nishino +2
As Large Language Models (LLMs) are increasingly integrated into agentic workflows, their unpredictability stemming from numerical instability has emerged as a critical reliability…
Are Vision Transformer Representations Semantically Meaningful? A Case Study in Medical Imaging
Montasir Shams, Chashi Mahiul Islam, Shaeke Salman +2
Vision transformers (ViTs) have rapidly gained prominence in medical imaging tasks such as disease classification, segmentation, and detection due to their superior accuracy compar…
Malicious Path Manipulations via Exploitation of Representation Vulnerabilities of Vision-Language Navigation Systems
Chashi Mahiul Islam, Shaeke Salman, Montasir Shams +2
Building on the unprecedented capabilities of large language models for command understanding and zero-shot recognition of multi-modal vision-language transformers, visual language…
Unaligning Everything: Or Aligning Any Text to Any Image in Multimodal Models
Shaeke Salman, Md Montasir Bin Shams, Xiuwen Liu
Utilizing a shared embedding space, emerging multimodal models exhibit unprecedented zero-shot capabilities. However, the shared embedding space could lead to new vulnerabilities i…
Intriguing Differences Between Zero-Shot and Systematic Evaluations of Vision-Language Transformer Models
Shaeke Salman, Md Montasir Bin Shams, Xiuwen Liu +1
Transformer-based models have dominated natural language processing and other areas in the last few years due to their superior (zero-shot) performance on benchmark datasets. Howev…
Intriguing Equivalence Structures of the Embedding Space of Vision Transformers
Shaeke Salman, Md Montasir Bin Shams, Xiuwen Liu
Pre-trained large foundation models play a central role in the recent surge of artificial intelligence, resulting in fine-tuned models with remarkable abilities when measured on be…
Improved Stock Price Movement Classification Using News Articles Based on Embeddings and Label Smoothing
Luis Villamil, Ryan Bausback, Shaeke Salman +3
Stock price movement prediction is a challenging and essential problem in finance. While it is well established in modern behavioral finance that the share prices of related stocks…
IoT Device Identification Based on Network Traffic Characteristics
Md Mainuddin, Zhenhai Duan, Yingfei Dong +2
IoT device identification plays an important role in monitoring and improving the performance and security of IoT devices. Compared to traditional non-IoT devices, IoT devices prov…
Towards Quantifying Intrinsic Generalization of Deep ReLU Networks
Shaeke Salman, Canlin Zhang, Xiuwen Liu +1
Understanding the underlying mechanisms that enable the empirical successes of deep neural networks is essential for further improving their performance and explaining such network…
Consensus-based Interpretable Deep Neural Networks with Application to Mortality Prediction
Shaeke Salman, Seyedeh Neelufar Payrovnaziri, Xiuwen Liu +2
Deep neural networks have achieved remarkable success in various challenging tasks. However, the black-box nature of such networks is not acceptable to critical applications, such…
Overfitting Mechanism and Avoidance in Deep Neural Networks
Shaeke Salman, Xiuwen Liu
Assisted by the availability of data and high performance computing, deep learning techniques have achieved breakthroughs and surpassed human performance empirically in difficult t…