Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
S2abEL: A Dataset for Entity Linking from Scientific Tables
Entity linking (EL) is the task of linking a textual mention to its corresponding entry in a knowledge base, and is critical for many knowledge-intensive NLP applications. When applied to tables in…
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…
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…
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…
The Semantic Reader Project: Augmenting Scholarly Documents through AI-Powered Interactive Reading Interfaces
Scholarly publications are key to the transfer of knowledge from scholars to others. However, research papers are information-dense, and as the volume of the scientific literature grows, the need…
Comparing Sentence-Level Suggestions to Message-Level Suggestions in AI-Mediated Communication
Traditionally, writing assistance systems have focused on short or even single-word suggestions. Recently, large language models like GPT-3 have made it possible to generate significantly longer…
The Semantic Scholar Open Data Platform
The volume of scientific output is creating an urgent need for automated tools to help scientists keep up with developments in their field. Semantic Scholar (S2) is an open data platform and website…