9 citations · 17 across the 10 of their papers we have counts for
11 papers
Gaussian Splatting for Real-Time Scene Reconstruction: Methods, Systems, and Trade-offs
Ashim Dahal, Rabab Abdelfattah, Nick Rahimi
3D Gaussian Splatting (3DGS) allows for high-quality real-time novel-view synthesis. Since its inception in 2023, its explicit and highly configurable scene representation has been…
MetaSampling: Making Frame Samplers Efficient for Long-Video Question Answering
Ashim Dahal, Bikramjit Banerjee
Frame selection is an important component of long-video question answering (VQA) with Multimodal Large Language Models (MLLMs). Existing frame-selection methods improve over simple…
Does it matter which Gaussians you pick in 4D Gaussian streaming?
Ashim Dahal, Rabab Abdelfattah, Nick Rahimi
Anchor-driven 4D Gaussian streaming methods such as Instant Gaussian Stream (IGS) update a dynamic scene each frame from a compact set of Gaussian anchors, chosen by default with F…
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…
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. As such metrics incre…
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…
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,…
Multi-Lingual Cyber Threat Detection in Tweets/X Using ML, DL, and LLM: A Comparative Analysis
Saydul Akbar Murad, Ashim Dahal, Nick Rahimi
Cyber threat detection has become an important area of focus in today's digital age due to the growing spread of fake information and harmful content on social media platforms such…
Analysis of Zero Day Attack Detection Using MLP and XAI
Ashim Dahal, Prabin Bajgai, Nick Rahimi
Any exploit taking advantage of zero-day is called a zero-day attack. Previous research and social media trends show a massive demand for research in zero-day attack detection. Thi…
Efficiency Bottlenecks of Convolutional Kolmogorov-Arnold Networks: A Comprehensive Scrutiny with ImageNet, AlexNet, LeNet and Tabular Classification
Ashim Dahal, Saydul Akbar Murad, Nick Rahimi
Algorithmic level developments like Convolutional Neural Networks, transformers, attention mechanism, Retrieval Augmented Generation and so on have changed Artificial Intelligence.…
Heuristical Comparison of Vision Transformers Against Convolutional Neural Networks for Semantic Segmentation on Remote Sensing Imagery
Ashim Dahal, Saydul Akbar Murad, Nick Rahimi
Vision Transformers (ViT) have recently brought a new wave of research in the field of computer vision. These models have performed particularly well in image classification and se…