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Ian Foster

7 accepted papers

2026

Position: It is Time to Virtualize Foundation Models with a Self-evolving Operating System Layer

ICML 2026poster

AI applications have shifted from single, mono-lithic foundation models (FM) to compound agentic systems. Yet today’s stacks remain fragmented: even as protocols (e.g., MCP, A2A) ease tool/agent connectivity, each framework embeds an implicit runtime for state, memory, budgets, and guardrails, makin…

Cited by 0SourceScholar
2026

The False Promise of Zero-Shot Super-Resolution in Machine-Learned Operators

ICLR 2026poster

A core challenge in scientific machine learning, and scientific computing more generally, is modeling continuous phenomena which (in practice) are represented discretely. Machine-learned operators (MLO) have been introduced as a means to achieve this modeling goal, as this class of architecture can…

Cited by 0SourcecodeScholar
2025

Mitigating Memorization in Language Models

ICLR 2025spotlight

Language models (LMs) can “memorize” information, i.e., encode training data in their weights in such a way that inference-time queries can lead to verbatim regurgitation of that data. This ability to extract training data can be problematic, for example, when data are private or sensitive. In this…

2025

OmniCast: A Masked Latent Diffusion Model for Weather Forecasting Across Time Scales

NeurIPS 2025poster

Accurate weather forecasting across time scales is critical for anticipating and mitigating the impacts of climate change. Recent data-driven methods based on deep learning have achieved significant success in the medium range, but struggle at longer subseasonal-to-seasonal (S2S) horizons due to err…

Cited by 0SourcecodeScholar
2024

Scaling transformer neural networks for skillful and reliable medium-range weather forecasting

NeurIPS 2024poster

Weather forecasting is a fundamental problem for anticipating and mitigating the impacts of climate change. Recently, data-driven approaches for weather forecasting based on deep learning have shown great promise, achieving accuracies that are competitive with operational systems. However, those met…

2023

The Diminishing Returns of Masked Language Models to Science

ACL 2023findings

Transformer-based masked language models such as BERT, trained on general corpora, have shown impressive performance on downstream tasks. It has also been demonstrated that the downstream task performance of such models can be improved by pretraining larger models for longer on more data. In this wo…

2023

WordScape: a Pipeline to extract multilingual, visually rich Documents with Layout Annotations from Web Crawl Data

NeurIPS 2023poster

We introduce WordScape, a novel pipeline for the creation of cross-disciplinary, multilingual corpora comprising millions of pages with annotations for document layout detection. Relating visual and textual items on document pages has gained further significance with the advent of multimodal models.…