5 papers
Test-Time Consistency in Vision Language Models
Shih-Han Chou, Shivam Chandhok, James J. Little +1
Vision-Language Models (VLMs) have achieved impressive performance across a wide range of multimodal tasks, yet they often exhibit inconsistent behavior when faced with semanticall…
MM-R: On (In-)Consistency of Vision-Language Models (VLMs)
Shih-Han Chou, Shivam Chandhok, James J. Little +1
With the advent of LLMs and variants, a flurry of research has emerged, analyzing the performance of such models across an array of tasks. While most studies focus on evaluating th…
The Power of One: A Single Example is All it Takes for Segmentation in VLMs
Mir Rayat Imtiaz Hossain, Mennatullah Siam, Leonid Sigal +1
Large-scale vision-language models (VLMs), trained on extensive datasets of image-text pairs, exhibit strong multimodal understanding capabilities by implicitly learning associatio…
Visual Prompting for Generalized Few-shot Segmentation: A Multi-scale Approach
Mir Rayat Imtiaz Hossain, Mennatullah Siam, Leonid Sigal +1
The emergence of attention-based transformer models has led to their extensive use in various tasks, due to their superior generalization and transfer properties. Recent research h…
Framework-agnostic Semantically-aware Global Reasoning for Segmentation
Mir Rayat Imtiaz Hossain, Leonid Sigal, James J. Little
Recent advances in pixel-level tasks (e.g. segmentation) illustrate the benefit of of long-range interactions between aggregated region-based representations that can enhance local…