Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
From Recognition to Cognition: Visual Commonsense Reasoning
Visual understanding goes well beyond object recognition. With one glance at an image, we can effortlessly imagine the world beyond the pixels: for instance, we can infer people’s actions, goals,…
Video Relationship Reasoning using Gated Spatio-Temporal Energy Graph
Visual relationship reasoning is a crucial yet challenging task for understanding rich interactions across visual concepts. For example, a relationship \{man, open, door\} involves a complex…
Assisted Excitation of Activations: A Learning Technique to Improve Object Detectors
We present a simple and effective learning technique that significantly improves mAP of YOLO object detectors without compromising their speed. During network training, we carefully feed in…
Sentence Mover's Similarity: Automatic Evaluation for Multi-Sentence Texts
For evaluating machine-generated texts, automatic methods hold the promise of avoiding collection of human judgments, which can be expensive and time-consuming. The most common automatic metrics,…
Barack's Wife Hillary: Using Knowledge Graphs for Fact-Aware Language Modeling
Modeling human language requires the ability to not only generate fluent text but also encode factual knowledge. However, traditional language models are only capable of remembering facts seen at…
Is Attention Interpretable?
Attention mechanisms have recently boosted performance on a range of NLP tasks. Because attention layers explicitly weight input components' representations, it is also often assumed that attention…
Conversing by Reading: Contentful Neural Conversation with On-demand Machine Reading
Although neural conversational models are effective in learning how to produce fluent responses, their primary challenge lies in knowing what to say to make the conversation contentful and…
SemEval-2019 Task 10: Math Question Answering
We report on the SemEval 2019 task on math question answering. We provided a question set derived from Math SAT practice exams, including 2778 training questions and 1082 test questions. For a…
Variational Pretraining for Semi-supervised Text Classification
We introduce VAMPIRE, a lightweight pretraining framework for effective text classification when data and computing resources are limited. We pretrain a unigram document model as a variational…
Be Consistent! Improving Procedural Text Comprehension using Label Consistency
Our goal is procedural text comprehension, namely tracking how the properties of entities (e.g., their location) change with time given a procedural text (e.g., a paragraph about photosynthesis, a…