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20242026
most citedAnalysis of Zero Day Attack Detection Using MLP and XAI

9 citations · 17 across the 16 of their papers we have counts for

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9 papers · 1 filter

cs.CL2025

A Unified BERT-CNN-BiLSTM Framework for Simultaneous Headline Classification and Sentiment Analysis of Bangla News

Mirza Raquib, Munazer Montasir Akash, Tawhid Ahmed +5

In our daily lives, newspapers are an essential information source that impacts how the public talks about present-day issues. However, effectively navigating the vast amount of ne…

cs.CV2025

POVQA: Preference-Optimized Video Question Answering with Rationales for Data Efficiency

Ashim Dahal, Ankit Ghimire, Saydul Akbar Murad +1

Long-video multimodal question answering requires structured reasoning over visual evidence and dialogue, but Large Vision-Language Models (LVLMs) are constrained by context-window…

cs.CR2025

Adversarial Machine Learning for Robust Password Strength Estimation

Pappu Jha, Hanzla Hamid, Oluseyi Olukola +2

Passwords remain one of the most common methods for securing sensitive data in the digital age. However, weak password choices continue to pose significant risks to data security a…

cs.CV2025

Redemption Score: A Multi-Modal Evaluation Framework for Image Captioning via Distributional, Perceptual, and Linguistic Signal Triangulation

Ashim Dahal, Ankit Ghimire, Saydul Akbar Murad +1

Evaluating image captions requires cohesive assessment of both visual semantics and language pragmatics, which is often not entirely captured by most metrics. We introduce Redempti…

cs.CL2025

EEG-to-Text Translation: A Model for Deciphering Human Brain Activity

Saydul Akbar Murad, Ashim Dahal, Nick Rahimi

With the rapid advancement of large language models like Gemini, GPT, and others, bridging the gap between the human brain and language processing has become an important area of f…

cs.CV2025

Embedding Shift Dissection on CLIP: Effects of Augmentations on VLM's Representation Learning

Ashim Dahal, Saydul Akbar Murad, Nick Rahimi

Understanding the representation shift on Vision Language Models like CLIP under different augmentations provides valuable insights on Mechanistic Interpretability. In this study,…