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Research - Papers

Explore a selection of our published work on a variety of key research challenges in AI.

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Narrative Scaffolding: A Narrative-First Framework for Data-Driven Sensemaking

Oliver HuangMuhammad FatirTian LuoCarolina Nobre
2026
International Conference on Intelligent User Interfaces (IUI)

When exploring data, analysts construct narratives about what the data means by asking questions, generating visualizations, reflecting on patterns, and revising their interpretations as new… 

Language Models Don't Know What You Want: Evaluating Personalization in Deep Research Needs Real Users

Nishant BalepurMalachi HamadaV. KishoreAakanksha Naik
2026
ACL

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… 

Disentangling the effects of sea surface temperature and CO$_2$ in global machine learned weather-climate emulators

S. ClarkTroy ArcomanoJames P. C. DuncanChristopher S. Bretherton
2026
arXiv

While previous versions of the Ai2 Climate Emulator (ACE) have been trained with CO$_2$ as a forcing, they are only accurate within a narrow range of scenarios, for example climate over the last 80… 

SamudrACE: Fast and Accurate Coupled Climate Modeling with 3D Ocean and Atmosphere Emulators

James P. C. DuncanElynn WuSurya DheeshjithChristopher S. Bretherton
2026
Geophysical Research Letters

Traditional numerical global climate models simulate the full Earth system by exchanging boundary conditions between separate simulators of the atmosphere, ocean, sea ice, land surface, and other… 

AIMIP Phase 1: systematic evaluations of AI weather and climate models

Brian HennChristopher S. BrethertonNikolay KodunovIgnacio Lopez-Gomez
2026
arXiv

We present the AI weather and climate model intercomparison project (AIMIP), phase 1. Drawing from the rich tradition of intercomparisons in climate model development, we specify a common… 

Improving Attributed Long-form Question Answering with Intent Awareness

Xinran ZhaoAakanksha NaikJay DeYoungV. Kishore
2026
ICLR

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

K. FengKevin PuMatt LatzkeJoseph Chee Chang
2026
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems

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… 

Perspectra: Choosing Your Experts Enhances Critical Thinking in Multi-Agent Research Ideation

Yiren LiuViraj ShahSangho SuhYun Huang
2026
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems

Early-stage interdisciplinary research ideation is often challenged by limited expert access, uncertainty about what to ask, and the cognitive burden of synthesizing unfamiliar domain perspectives.… 

FloeNet: A mass-conserving global sea ice emulator that generalizes across climates

William GregoryM. BushukJames P. C. DuncanL. Zanna
2026
arXiv

We introduce FloeNet, a machine-learning emulator trained on the Geophysical Fluid Dynamics Laboratory global sea ice model, SIS2. FloeNet is a mass-conserving model, emulating 6-hour mass and area… 

Examining Fast Radiative Feedbacks Using Machine-Learning Weather Emulators

Ankur MaheshWilliam D. CollinsTravis A. O'BrienDa Yang
2026
arXiv

The response of the climate system to increased greenhouse gases and other radiative perturbations is governed by a combination of fast and slow feedbacks. Slow feedbacks are typically activated in… 

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