Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
LitPivot: Developing Well-Situated Research Ideas Through Dynamic Contextualization and Critique within the Literature Landscape
Developing a novel research idea is hard. It must be distinct enough from prior work to claim a contribution while also building on it. This requires iteratively reviewing literature and refining an…
Cracks in the Foundation: Seemingly Minor Architectural Choices Impact Long Context Extension
One might imagine that architectural variations within the dense transformer paradigm have a limited effect on accuracy. However, we demonstrate that this is not the case in the long context…
Olmo Hybrid: From Theory to Practice and Back
Recent work has demonstrated the potential of non-transformer language models, especially linear recurrent neural networks (RNNs) and hybrid models that mix recurrence and attention. Yet there is no…
Measuring AI Scientists: From Exams to Discovery
Large language models and agentic systems are increasingly embedded across the scientific work-flow, from literature synthesis and hypothesis generation to code execution, data analysis and writing.…
Process-Oriented Evaluation of AI-Assisted Scientific Writing
Bad writing hinders the publication of science. The role of artificial intelligence (AI) in generating and editing scientific texts remains unsettled. Abstracts serve as the critical gateway to…
Stochastic Emulation of a Fully Coupled Preindustrial E3SMv3 Simulation
We present a stochastic coupled emulator of E3SM version 3, built on the SamudrACE framework, which couples an atmosphere emulator (ACE2) with a full-depth ocean emulator (Samudra). We replace the…
ArtifactLinker: Linking Scientific Artifacts for Automatic State-of-the-Art Discovery
Scientific artifacts such as models and datasets are foundations for research. With the rapid growth of platforms like HuggingFace, researchers now have access to a large number of artifacts. Yet, a…
CoTs as Tractable Probabilistic Programs
Chain-of-thought (CoT) traces are used across language model prompting, training, test-time inference, and interpretability, yet they are often modeled in task-specific ways. We propose treating CoT…
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…
Narrative Scaffolding: A Narrative-First Framework for Data-Driven Sensemaking
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…