1 citations · 1 across the 6 of their papers we have counts for
6 papers
FOCUS: Forcing In-Context Object Localization through Visual Support Constraints and Policy Optimization
Mohammed Asad Karim, Vinay Kumar Verma
In-context localization (ICL) seeks to localize a target object specified by a small set of support examples in a query image, operating on the fly without training or parameter up…
Salient Information Prompting to Steer Content in Prompt-based Abstractive Summarization
Lei Xu, Mohammed Asad Karim, Saket Dingliwal +1
Large language models (LLMs) can generate fluent summaries across domains using prompting techniques, reducing the need to train models for summarization applications. However, cra…
Bridging the Gap: Exploring the Capabilities of Bridge-Architectures for Complex Visual Reasoning Tasks
Kousik Rajesh, Mrigank Raman, Mohammed Asad Karim +1
In recent times there has been a surge of multi-modal architectures based on Large Language Models, which leverage the zero shot generation capabilities of LLMs and project image e…
Attaining Class-level Forgetting in Pretrained Model using Few Samples
Pravendra Singh, Pratik Mazumder, Mohammed Asad Karim
In order to address real-world problems, deep learning models are jointly trained on many classes. However, in the future, some classes may become restricted due to privacy/ethical…
DILF-EN framework for Class-Incremental Learning
Mohammed Asad Karim, Indu Joshi, Pratik Mazumder +1
Deep learning models suffer from catastrophic forgetting of the classes in the older phases as they get trained on the classes introduced in the new phase in the class-incremental…
Knowledge Consolidation based Class Incremental Online Learning with Limited Data
Mohammed Asad Karim, Vinay Kumar Verma, Pravendra Singh +2
We propose a novel approach for class incremental online learning in a limited data setting. This problem setting is challenging because of the following constraints: (1) Classes a…