Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
From Who You Know to What You Read: Augmenting Scientific Recommendations with Implicit Social Networks
The ever-increasing pace of scientific publication necessitates methods for quickly identifying relevant papers. While neural recommenders trained on user interests can help, they still result in…
Inferring Implicit Relations with Language Models
A prominent challenge for modern language understanding systems is the ability to answer implicit reasoning questions, where the required reasoning steps for answering the question are not mentioned…
LM-Debugger: An Interactive Tool for Inspection and Intervention in Transformer-Based Language Models
The opaque nature and unexplained behavior of transformer-based language models (LMs) have spurred a wide interest in interpreting their predictions. However, current interpretation methods mostly…
Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation
Since the introduction of the transformer model by Vaswani et al. (2017), a fundamental question has yet to be answered: how does a model achieve extrapolation at inference time for sequences that…
S2AMP: A High-Coverage Dataset of Scholarly Mentorship Inferred from Publications
Mentorship is a critical component of academia, but is not as visible as publications, citations, grants, and awards. Despite the importance of studying the quality and impact of mentorship, there…
Bursting Scientific Filter Bubbles: Boosting Innovation via Novel Author Discovery
Isolated silos of scientific research and the growing challenge of information overload limit awareness across the literature and hinder innovation. Algorithmic curation and recommendation, which…
Beam Decoding with Controlled Patience
Text generation with beam search has proven successful in a wide range of applications. The commonly-used implementation of beam decoding follows a first come, first served heuris-tic: it keeps a set…
Infrastructure for rapid open knowledge network development
The past decade has witnessed a growth in the use of knowledge graph technologies for advanced data search, data integration, and query-answering applications. The leading example of a public,…
Continuous Scene Representations for Embodied AI
We propose Continuous Scene Representations (CSR), a scene representation constructed by an embodied agent navigating within a space, where objects and their relationships are modeled by continuous…
Benchmarking Generalization via In-Context Instructions on 1, 600+ Language Tasks
How can we measure the generalization of models to a variety of unseen tasks when provided with their language instructions? To facilitate progress in this goal, we introduce N ATURAL -I NSTRUCTIONS…