Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Query-Reduction Networks for Question Answering
In this paper, we study the problem of question answering when reasoning over multiple facts is required. We propose Query-Reduction Network (QRN), a variant of Recurrent Neural Network (RNN) that…
See the Glass Half Full: Reasoning about Liquid Containers, their Volume and Content
Humans have rich understanding of liquid containers and their contents; for example, we can effortlessly pour water from a pitcher to a cup. Doing so requires estimating the volume of the cup,…
Should Artificial Intelligence Be Regulated?
New technologies often spur public anxiety, but the intensity of concern about the implications of advances in artificial intelligence (AI) is particularly noteworthy. Several respected scholars and…
Target-driven visual navigation in indoor scenes using deep reinforcement learning
Two less addressed issues of deep reinforcement learning are (1) lack of generalization capability to new goals, and (2) data inefficiency, i.e., the model requires several (and often costly)…
Tell Me Why: Using Question Answering as Distant Supervision for Answer Justification
For many applications of question answering (QA), being able to explain why a given model chose an answer is critical. However, the lack of labeled data for answer justifications makes learning this…
The AI2 system at SemEval-2017 Task 10 (ScienceIE): semi-supervised end-to-end entity and relation extraction
This paper describes our submission for the ScienceIE shared task (SemEval-2017 Task 10) on entity and relation extraction from scientific papers. Our model is based on the end-to-end relation…
The Effect of Different Writing Tasks on Linguistic Style: A Case Study of the ROC Story Cloze Task
A writer’s style depends not just on personal traits but also on her intent and mental state. In this paper, we show how variants of the same writing task can lead to measurable differences in…
Visual Semantic Planning using Deep Successor Representations
A crucial capability of real-world intelligent agents is their ability to plan a sequence of actions to achieve their goals in the visual world. In this work, we address the problem of visual…
YOLO9000: Better, Faster, Stronger
We introduce YOLO9000, a state-of-the-art, real-time object detection system that can detect over 9000 object categories. First we propose various improvements to the YOLO detection method, both…
Verb Physics: Relative Physical Knowledge of Actions and Objects
Learning commonsense knowledge from natural language text is nontrivial due to reporting bias: people rarely state the obvious, e.g., “My house is bigger than me.” However, while rarely stated…