14 citations · 19 across the 3 of their papers we have counts for
6 papers
CARETS: A Consistency And Robustness Evaluative Test Suite for VQA
Carlos E. Jimenez, Olga Russakovsky, Karthik Narasimhan
We introduce CARETS, a systematic test suite to measure consistency and robustness of modern VQA models through a series of six fine-grained capability tests. In contrast to existi…
Towards Unique and Informative Captioning of Images
Zeyu Wang, Berthy Feng, Karthik Narasimhan +1
Despite considerable progress, state of the art image captioning models produce generic captions, leaving out important image details. Furthermore, these systems may even misrepres…
Evolving Graphical Planner: Contextual Global Planning for Vision-and-Language Navigation
Zhiwei Deng, Karthik Narasimhan, Olga Russakovsky
The ability to perform effective planning is crucial for building an instruction-following agent. When navigating through a new environment, an agent is challenged with (1) connect…
Take the Scenic Route: Improving Generalization in Vision-and-Language Navigation
Felix Yu, Zhiwei Deng, Karthik Narasimhan +1
In the Vision-and-Language Navigation (VLN) task, an agent with egocentric vision navigates to a destination given natural language instructions. The act of manually annotating the…
Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation
Zeyu Wang, Klint Qinami, Ioannis Christos Karakozis +4
Computer vision models learn to perform a task by capturing relevant statistics from training data. It has been shown that models learn spurious age, gender, and race correlations…
Human uncertainty makes classification more robust
Joshua C. Peterson, Ruairidh M. Battleday, Thomas L. Griffiths +1
The classification performance of deep neural networks has begun to asymptote at near-perfect levels. However, their ability to generalize outside the training set and their robust…