2 citations · 4 across the 14 of their papers we have counts for
6 papers · 1 filter
Decompose, Mix, Adapt: A Unified Framework for Parameter-Efficient Neural Network Recombination and Compression
Nazia Tasnim, Shrimai Prabhumoye, Bryan A. Plummer
Parameter Recombination (PR) methods aim to efficiently compose the weights of a neural network for applications like Parameter-Efficient FineTuning (PEFT) and Model Compression (M…
Seeing Isn't Orienting: A Cognitively Grounded Benchmark Reveals Systematic Orientation Failures in MLLMs Supplementary
Nazia Tasnim, Keanu Nichols, Yuting Yang +4
Humans learn object orientation progressively, from recognizing which way an object faces, to mentally rotating it, to reasoning about orientations between objects. Current vision-…
Seeing Isn't Orienting: A Cognitively Informed Hierarchical Benchmark for Object Orientation in MLLMs
Nazia Tasnim, Keanu Nichols, Yuting Yan +4
Humans develop object orientation understanding progressively, from recognizing which way an object faces to reasoning about orientations across multiple objects. Yet existing visi…
RECAST: Reparameterized, Compact weight Adaptation for Sequential Tasks
Nazia Tasnim, Bryan A. Plummer
Incremental learning aims to adapt to new sets of categories over time with minimal computational overhead. Prior work often addresses this task by training efficient task-specific…
Vision-LLMs Can Fool Themselves with Self-Generated Typographic Attacks
Maan Qraitem, Nazia Tasnim, Piotr Teterwak +2
Typographic attacks, adding misleading text to images, can deceive vision-language models (LVLMs). The susceptibility of recent large LVLMs like GPT4-V to such attacks is understud…
VISTA: Vision Transformer enhanced by U-Net and Image Colorfulness Frame Filtration for Automatic Retail Checkout
Md. Istiak Hossain Shihab, Nazia Tasnim, Hasib Zunair +2
Multi-class product counting and recognition identifies product items from images or videos for automated retail checkout. The task is challenging due to the real-world scenario of…