Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
AdaWISH: Faster Discrete Integration via Adaptive Quantiles
Discrete integration in a high dimensional space of $n$ variables poses fundamental challenges. The WISH algorithm reduces the intractable discrete integration problem into $n$ optimization queries…
Approximating the Permanent by Sampling from Adaptive Partitions
Computing the permanent of a non-negative matrix is a core problem with practical applications ranging from target tracking to statistical thermodynamics. However, this problem is also #P-complete,…
Multi-class Hierarchical Question Classification for Multiple Choice Science Exams
Prior work has demonstrated that question classification (QC), recognizing the problem domain of a question, can help answer it more accurately. However, developing strong QC algorithms has been…
Transformers as Soft Reasoners over Language
AI has long pursued the goal of having systems reason over explicitly provided knowledge, but building suitable representations has proved challenging. Here we explore whether transformers can…
TransOMCS: From Linguistic Graphs to Commonsense Knowledge
Commonsense knowledge acquisition is a key problem for artificial intelligence. Conventional methods of acquiring commonsense knowledge generally require laborious and costly human annotations,…
Not All Claims are Created Equal: Choosing the Right Approach to Assess Your Hypotheses
Empirical research in Natural Language Processing (NLP) has adopted a narrow set of principles for assessing hypotheses, relying mainly on p-value computation, which suffers from several known…
Temporal Common Sense Acquisition with Minimal Supervision
Temporal common sense (e.g., duration and frequency of events) is crucial for understanding natural language. However, its acquisition is challenging, partly because such information is often not…
Procedural Reading Comprehension with Attribute-Aware Context Flow
Procedural texts often describe processes (e.g., photosynthesis and cooking) that happen over entities (e.g., light, food). In this paper, we introduce an algorithm for procedural reading…
Do Dogs have Whiskers? A New Knowledge Base of hasPart Relations
We present a new knowledge-base (KB) of hasPart relationships, extracted from a large corpus of generic statements. Complementary to other resources available, it is the first which is all three of:…
GenericsKB: A Knowledge Base of Generic Statements
We present a new resource for the NLP community, namely a large (3.5M+ sentence) knowledge base of *generic statements*, e.g., "Trees remove carbon dioxide from the atmosphere", collected from…