Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
SciA11y: Converting Scientific Papers to Accessible HTML
We present SciA11y, a system that renders inaccessible scientific paper PDFs into HTML. SciA11y uses machine learning models to extract and understand the content of scientific PDFs, and reorganizes…
Delphi: Towards Machine Ethics and Norms
Failing to account for moral norms could notably hinder AI systems’ ability to interact with people. AI systems empirically require social, cultural, and ethical norms to make moral judgments.…
Can Machines Learn Morality? The Delphi Experiment
As AI systems become increasingly powerful and pervasive, there are growing concerns about machines’ morality or a lack thereof. Yet, teaching morality to machines is a formidable task, as morality…
Reflective Decoding: Beyond Unidirectional Generation with Off-the-Shelf Language Models
Publicly available, large pretrained Language Models (LMs) generate text with remarkable quality, but only sequentially from left to right. As a result, they are not immediately applicable to…
SciCo: Hierarchical Cross-Document Coreference for Scientific Concepts
Determining coreference of concept mentions across multiple documents is fundamental for natural language understanding. Work on cross-document coreference resolution (CDCR) typically considers…
Scientific Language Models for Biomedical Knowledge Base Completion: An Empirical Study
Biomedical knowledge graphs (KGs) hold rich information on entities such as diseases, drugs, and genes. Predicting missing links in these graphs can boost many important applications, such as drug…
ReadOnce Transformers: Reusable Representations of Text for Transformers
While large-scale language models are extremely effective when directly fine-tuned on many end-tasks, such models learn to extract information and solve the task simultaneously from end-task…
Investigating Transfer Learning in Multilingual Pre-trained Language Models through Chinese Natural Language Inference
Multilingual transformers (XLM, mT5) have been shown to have remarkable transfer skills in zero-shot settings. Most transfer studies, however, rely on automatically translated resources (XNLI,…
Ethical-Advice Taker: Do Language Models Understand Natural Language Interventions?
Is it possible to use natural language to intervene in a model’s behavior and alter its prediction in a desired way? We investigate the effectiveness of natural language interventions for…
Expected Validation Performance and Estimation of a Random Variable's Maximum
Research in NLP is often supported by experimental results, and improved reporting of such results can lead to better understanding and more reproducible science. In this paper we analyze three…