Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
ABC: Attention with Bounded-memory Control
Transformer architectures have achieved state-of-the-art results on a variety of sequence modeling tasks. However, their attention mechanism comes with a quadratic complexity in sequence lengths,…
NumGLUE: A Suite of Fundamental yet Challenging Mathematical Reasoning Tasks
Given the ubiquitous nature of numbers in text, reasoning with numbers to perform simple calculations is an important skill of AI systems. While many datasets and models have been developed to this…
Generating Scientific Definitions with Controllable Complexity
Unfamiliar terminology and complex language can present barriers to understanding science. Natural language processing stands to help address these issues by automatically defining unfamiliar terms.…
Extracting Latent Steering Vectors from Pretrained Language Models
Prior work on controllable text generation has focused on learning how to control language models through trainable decoding, smart-prompt design, or fine-tuning based on a desired objective. We…
Productive Performance Engineering for Weather and Climate Modeling with Python
Earth system models are developed with a tight coupling to target hardware, often containing highly-specialized code predicated on processor characteristics. This coupling stems from using…
Generating Scientific Claims for Zero-Shot Scientific Fact Checking
Automated scientific fact checking is difficult due to the complexity of scientific language and a lack of significant amounts of training data, as annotation requires domain expertise. To address…
Is GPT-3 Text Indistinguishable from Human Text? SCARECROW: A Framework for Scrutinizing Machine Text
Modern neural text generation systems can produce remarkably fluent and grammatical texts. While earlier language models suffered from repetition and syntactic errors, the errors made by contemporary…
Situated Dialogue Learning through Procedural Environment Generation
We teach goal-driven agents to interactively act and speak in situated environments by training on generated curriculums. Our agents operate in LIGHT (Urbanek et al. 2019)—a large-scale…
Draw Me a Flower: Grounding Formal Abstract Structures Stated in Informal Natural Language
Forming and interpreting abstraction is a core process in human communication. In particular, when giving and performing complex instructions stated in natural language (NL), people may naturally…
ACCoRD: A Multi-Document Approach to Generating Diverse Descriptions of Scientific Concepts
Systems that can automatically define unfamiliar terms hold the promise of improving the accessibility of scientific texts, especially for readers who may lack prerequisite background knowledge.…