Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Querying Multimodal Scientific Papers with AI: Practices and Preferences Across Blind, Low-Vision, and Sighted Scientists
Visual diagrams, figures, and tables are central to scientific papers, and convey information beyond what is captured in text. While blind or low-vision (BLV) scientists have traditionally relied on…
Language Models Don't Know What You Want: Evaluating Personalization in Deep Research Needs Real Users
Deep Research (DR) systems help researchers cope with ballooning publishing counts. Such tools synthesize scientific papers to answer research queries, but lack understanding of their users. We…
Scientific reasoning does not reliably translate into scientific forecasting in frontier AI
AI systems are increasingly used to support forward-looking scientific judgment, but it remains unclear whether they can form reliable expectations about future scientific advances. Here we show…
Improving Attributed Long-form Question Answering with Intent Awareness
Large language models (LLMs) are increasingly being used to generate comprehensive, knowledge-intensive reports. However, while these models are trained on diverse academic papers and reports, they…
Cocoa: Co-Planning and Co-Execution with AI Agents
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 human-agent…
SciArena: An Open Evaluation Platform for Foundation Models in Scientific Literature Tasks
We present SciArena, an open and collaborative platform for evaluating foundation models on scientific literature tasks. Unlike traditional benchmarks for scientific literature understanding and…
SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific Literature
We present SciRIFF (Scientific Resource for Instruction-Following and Finetuning), a dataset of 137K instruction-following instances for training and evaluation, covering 54 tasks. These tasks span…
Intent-Aware Schema Generation And Refinement For Literature Review Tables
The increasing volume of academic literature makes it essential for researchers to organize, compare, and contrast collections of documents. Large language models (LLMs) can support this process by…
AstaBench: Rigorous Benchmarking of AI Agents with a Scientific Research Suite
AI agents hold great real-world promise, with the potential to revolutionize scientific productivity by automating literature reviews, replicating experiments, analyzing data, and even proposing new…
LLMs as Research Tools: A Large Scale Survey of Researchers' Usage and Perceptions
The rise of large language models (LLMs) has led many researchers to consider their usage for scientific work. Some have found benefits using LLMs to augment or automate aspects of their research…