105 citations · 108 across the 6 of their papers we have counts for
8 papers
Think in English, Answer in Korean: Efficient Adaptation of Multilingual Tool-Using Agents
Utsav Garg, Sungjin Hong, Jason Jung +6
We present LuckyStar 111B, a 111B-parameter hybrid reasoning model developed through a collaboration between Cohere and LG CNS for Korean-English enterprise agents under practical…
Command A: An Enterprise-Ready Large Language Model
Team Cohere, :, Aakanksha +227
In this report we describe the development of Command A, a powerful large language model purpose-built to excel at real-world enterprise use cases. Command A is an agent-optimised…
Let's Go Shopping (LGS) -- Web-Scale Image-Text Dataset for Visual Concept Understanding
Yatong Bai, Utsav Garg, Apaar Shanker +10
Vision and vision-language applications of neural networks, such as image classification and captioning, rely on large-scale annotated datasets that require non-trivial data-collec…
On the Performance of Multimodal Language Models
Utsav Garg, Erhan Bas
Instruction-tuned large language models (LLMs) have demonstrated promising zero-shot generalization capabilities across various downstream tasks. Recent research has introduced mul…
Fabrik: An Online Collaborative Neural Network Editor
Utsav Garg, Viraj Prabhu, Deshraj Yadav +3
We present Fabrik, an online neural network editor that provides tools to visualize, edit, and share neural networks from within a browser. Fabrik provides a simple and intuitive G…
NAG: Network for Adversary Generation
Konda Reddy Mopuri, Utkarsh Ojha, Utsav Garg +1
Adversarial perturbations can pose a serious threat for deploying machine learning systems. Recent works have shown existence of image-agnostic perturbations that can fool classifi…
CNN Fixations: An unraveling approach to visualize the discriminative image regions
Konda Reddy Mopuri, Utsav Garg, R. Venkatesh Babu
Deep convolutional neural networks (CNN) have revolutionized various fields of vision research and have seen unprecedented adoption for multiple tasks such as classification, detec…
Fast Feature Fool: A data independent approach to universal adversarial perturbations
Konda Reddy Mopuri, Utsav Garg, R. Venkatesh Babu
State-of-the-art object recognition Convolutional Neural Networks (CNNs) are shown to be fooled by image agnostic perturbations, called universal adversarial perturbations. It is a…