24 citations · 126 across the 11 of their papers we have counts for
15 papers
Atlas: Making Sense of Long Horizon Agent Trajectories
Sangho Suh, Joseph Chee Chang, Pao Siangliulue +5
AI agents can now search literature, generate hypotheses, analyze datasets, and run experiments at a scale difficult for researchers to match. Yet scaling scientific execution does…
Asterism: Exploring and Synthesizing Scattered Observations into Literature-Grounded Hypotheses and Theories
Joseph Chee Chang, Michael D'Arcy, Amy X. Zhang +15
A theory draws many independent observations into one framework with novel hypotheses. A researcher building such a theory must synthesize observations scattered across many papers…
AstaBench: Rigorous Benchmarking of AI Agents with a Scientific Research Suite
Jonathan Bragg, Mike D'Arcy, Nishant Balepur +36
AI agents hold the potential to revolutionize scientific productivity by automating literature reviews, replicating experiments, analyzing data, and even proposing new directions o…
SciArena: An Open Evaluation Platform for Non-Verifiable Scientific Literature-Grounded Tasks
Yilun Zhao, Kaiyan Zhang, Tiansheng Hu +15
We present SciArena, an open and collaborative platform for evaluating foundation models on scientific literature-grounded tasks. Unlike traditional benchmarks for scientific liter…
Ai2 Scholar QA: Organized Literature Synthesis with Attribution
Amanpreet Singh, Joseph Chee Chang, Chloe Anastasiades +15
Retrieval-augmented generation is increasingly effective in answering scientific questions from literature, but many state-of-the-art systems are expensive and closed-source. We in…
Cocoa: Co-Planning and Co-Execution with AI Agents
K. J. Kevin Feng, Kevin Pu, Matt Latzke +6
As AI agents take on increasingly long-running tasks involving sophisticated planning and execution, there is a corresponding need for novel interaction designs that enable deeper…
OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs
Akari Asai, Jacqueline He, Rulin Shao +22
Scientific progress depends on researchers' ability to synthesize the growing body of literature. Can large language models (LMs) assist scientists in this task? We introduce OpenS…
IdeaSynth: Iterative Research Idea Development Through Evolving and Composing Idea Facets with Literature-Grounded Feedback
Kevin Pu, K. J. Kevin Feng, Tovi Grossman +6
Research ideation involves broad exploring and deep refining ideas. Both require deep engagement with literature. Existing tools focus primarily on idea broad generation, yet offer…
PaperWeaver: Enriching Topical Paper Alerts by Contextualizing Recommended Papers with User-collected Papers
Yoonjoo Lee, Hyeonsu B. Kang, Matt Latzke +4
With the rapid growth of scholarly archives, researchers subscribe to "paper alert" systems that periodically provide them with recommendations of recently published papers that ar…
Mitigating Barriers to Public Social Interaction with Meronymous Communication
Nouran Soliman, Hyeonsu B Kang, Matthew Latzke +4
In communities with social hierarchies, fear of judgment can discourage communication. While anonymity may alleviate some social pressure, fully anonymous spaces enable toxic behav…
Papeos: Augmenting Research Papers with Talk Videos
Tae Soo Kim, Matt Latzke, Jonathan Bragg +2
Research consumption has been traditionally limited to the reading of academic papers-a static, dense, and formally written format. Alternatively, pre-recorded conference presentat…
The Semantic Reader Project: Augmenting Scholarly Documents through AI-Powered Interactive Reading Interfaces
Kyle Lo, Joseph Chee Chang, Andrew Head +52
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…
ComLittee: Literature Discovery with Personal Elected Author Committees
Hyeonsu B. Kang, Nouran Soliman, Matt Latzke +2
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.…
From Who You Know to What You Read: Augmenting Scientific Recommendations with Implicit Social Networks
Hyeonsu B. Kang, Rafal Kocielnik, Andrew Head +6
The ever-increasing pace of scientific publication necessitates methods for quickly identifying relevant papers. While neural recommenders trained on user interests can help, they…
Improving the Accessibility of Scientific Documents: Current State, User Needs, and a System Solution to Enhance Scientific PDF Accessibility for Blind and Low Vision Users
Lucy Lu Wang, Isabel Cachola, Jonathan Bragg +7
The majority of scientific papers are distributed in PDF, which pose challenges for accessibility, especially for blind and low vision (BLV) readers. We characterize the scope of t…