32 citations · 99 across the 14 of their papers we have counts for
24 papers
Can Rationalization Improve Robustness?
Howard Chen, Jacqueline He, Karthik Narasimhan +1
A growing line of work has investigated the development of neural NLP models that can produce rationales--subsets of input that can explain their model predictions. In this paper,…
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…
Revelio: ML-Generated Debugging Queries for Distributed Systems
Pradeep Dogga, Karthik Narasimhan, Anirudh Sivaraman +3
A major difficulty in debugging distributed systems lies in manually determining which of the many available debugging tools to use and how to query its logs. Our own study of a pr…
Reading and Acting while Blindfolded: The Need for Semantics in Text Game Agents
Shunyu Yao, Karthik Narasimhan, Matthew Hausknecht
Text-based games simulate worlds and interact with players using natural language. Recent work has used them as a testbed for autonomous language-understanding agents, with the mot…
Grounding Language to Entities and Dynamics for Generalization in Reinforcement Learning
Austin W. Hanjie, Victor Zhong, Karthik Narasimhan
We investigate the use of natural language to drive the generalization of control policies and introduce the new multi-task environment Messenger with free-form text manuals descri…
Connecting Context-specific Adaptation in Humans to Meta-learning
Rachit Dubey, Erin Grant, Michael Luo +2
Cognitive control, the ability of a system to adapt to the demands of a task, is an integral part of cognition. A widely accepted fact about cognitive control is that it is context…