Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Answering Questions by Meta-Reasoning over Multiple Chains of Thought
Modern systems for multi-hop question answering (QA) typically break questions into a sequence of reasoning steps, termed chain-of-thought (CoT), before arriving at a final answer. Often, multiple…
A Global Survey of Rotating Convective Updrafts in the GFDL X‐SHiELD 2021 Global Storm Resolving Model
We present the global characteristics of rotating convective updrafts in the 2021 version of GFDL's eXperimental System for High‐resolution prediction on Earth‐to‐Local Domains (X‐SHiELD), a…
CiteSee: Augmenting Citations in Scientific Papers with Persistent and Personalized Historical Context
When reading a scholarly article, inline citations help researchers contextualize the current article and discover relevant prior work. However, it can be challenging to prioritize and make sense of…
ComLittee: Literature Discovery with Personal Elected Author Committees
In order to help scholars understand and follow a research topic, significant research has been devoted to creating systems that help scholars discover relevant papers and authors. Recent approaches…
Relatedly: Scaffolding Literature Reviews with Existing Related Work Sections
Scholars who want to research a scientific topic must take time to read, extract meaning, and identify connections across many papers. As scientific literature grows, this becomes increasingly…
Toxicity in ChatGPT: Analyzing Persona-assigned Language Models
Large language models (LLMs) have shown incredible capabilities and transcended the natural language processing (NLP) community, with adoption throughout many services like healthcare, therapy,…
Beyond Summarization: Designing AI Support for Real-World Expository Writing Tasks
Large language models have introduced exciting new opportunities and challenges in designing and developing new AI-assisted writing support tools. Recent work has shown that leveraging this new…
When Learning Is Out of Reach, Reset: Generalization in Autonomous Visuomotor Reinforcement Learning
Episodic training, where an agent's environment is reset to some initial condition after every success or failure, is the de facto standard when training embodied reinforcement learning (RL) agents.…
Queer In AI: A Case Study in Community-Led Participatory AI
We present Queer in AI as a case study for community-led participatory design in AI. We examine how participatory design and intersectional tenets started and shaped this community's programs over…
Scim: Intelligent Faceted Highlights for Interactive, Multi-Pass Skimming of Scientific Papers
Researchers are expected to keep up with an immense literature, yet often find it prohibitively time-consuming to do so. This paper ex-plores how intelligent agents can help scaffold in-situ…