Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Evidence-Informed LLM Beliefs for Continual Scientific Discovery
Open-ended scientific discovery with large language models (LLMs) increasingly operates as a long-horizon loop of hypothesis search and verification, where a reward signal guides which hypotheses to…
Efficiently Representing Algorithms With Chain-of-Thought Transformers
The increasing popularity of \emph{reasoning} models -- language models that output a series of reasoning or thought tokens before producing an answer -- is justified, in part, by theoretical…
Operadic consistency: a label-free signal for compositional reasoning failures in LLMs
Detecting LLM reasoning failures at inference time without ground-truth labels has motivated a wide range of confidence baselines, including self-consistency, semantic entropy, and P(True), built on…
Operads for compositional reasoning in LLMs
Question decomposition, i.e. breaking a complex query into simpler sub-queries whose answers are composed to produce a final answer, is a widely used strategy for improving LLM reasoning, yet it…
Disentangling the effects of sea surface temperature and CO$_2$ in global machine learned weather-climate emulators
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…
VideoNet: A Large-Scale Dataset for Domain-Specific Action Recognition
Videos are unique in their ability to capture actions which transcend multiple frames. Accordingly, for many years action recognition was the quintessential task for video understanding.…
Enabling federated discovery leveraging agentic AI systems: The Cancer AI Alliance and DataVoyager
Background: Artificial intelligence (AI) has the potential to transform oncology, but robust AI models require diverse, multi-institutional data that preserve patient privacy. Federating data across…
SamudrACE: Fast and Accurate Coupled Climate Modeling with 3D Ocean and Atmosphere Emulators
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…
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…
AIMIP Phase 1: systematic evaluations of AI weather and climate models
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…