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Weekly Research Newsletter - KIIT - Issue #14

Weekly Research Newsletter - KIIT - Issue #14
6th June 2021,
We are excited to share this week’s picks for the research newsletter. We hope you’ll enjoy reading them over the weekend.

Towards General Purpose Vision Systems
By Tanmay Gupta, Amita Kamath, Aniruddha Kembhavi, Derek Hoiem
A special purpose learning system assumes knowledge of admissible tasks at design time. Adapting such a system to unforeseen tasks requires architecture manipulation such as adding an output head for each new task or dataset. In this work, we propose a task-agnostic vision-language system that accepts an image and a natural language task description and outputs bounding boxes, confidences, and text. The system supports a wide range of vision tasks such as classification, localization, question answering, captioning, and more. We evaluate the system’s ability to learn multiple skills simultaneously, to perform tasks with novel skill-concept combinations, and to learn new skills efficiently and without forgetting.
Special thanks to Sounak Mukherjee for recommending the this paper.
Cause and Effect: Concept-based Explanation of Neural Networks
By Mohammad Nokhbeh Zaeem, Majid Komeili
In many scenarios, human decisions are explained based on some high-level concepts. In this work, we take a step in the interpretability of neural networks by examining their internal representation or neuron’s activations against concepts. A concept is characterized by a set of samples that have specific features in common. We propose a framework to check the existence of a causal relationship between a concept (or its negation) and task classes. While the previous methods focus on the importance of a concept to a task class, we go further and introduce four measures to quantitatively determine the order of causality. Through experiments, we demonstrate the effectiveness of the proposed method in explaining the relationship between a concept and the predictive behaviour of a neural network.
Did you enjoy this issue?
Priyansi, Junaid Rahim and Biswaroop Bhattacharjee

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