Welcome to EvalEval Working Group Infrastructure! Please help us get set up by filling out this form - we are excited to get to know you! This is an interest form to contribute/collaborate on a research project, building standardized infrastructure for AI evaluation. Status Quo: The AI evaluation ecosystem currently lacks standardized methods for storing, sharing, and comparing evaluation results across different models and benchmarks. This fragmentation leads to unnecessary duplication of compute-intensive evaluations, challenges in reproducing results, and barriers to comprehensive cross-model analysis. What's the project? We plan to address these challenges by developing a comprehensive standardized format for capturing the complete evaluation lifecycle. This format will provide a clear and extensible structure for documenting evaluation inputs (hyperparameters, prompts, datasets), outputs, metrics, and metadata. This standardization enables efficient storage, retrieval, sharing, and comparison of evaluation results across the AI research community. Building on this foundation, we will create a centralized repository with both raw data access and API interfaces that allow researchers to contribute evaluation runs and access cached results. The project will integrate with popular evaluation frameworks (LM-eval, HELM, Unitxt) and provide SDKs to simplify adoption. Additionally, we will populate the repository with evaluation results from leading AI models across diverse benchmarks, creating a valuable resource that reduces computational redundancy and facilitates deeper comparative analysis. Tasks? As a collaborator, you would be expected to: Work towards merging/integrating popular evaluation frameworks (LM-eval, HELM, Unitxt) Group 1 - Extend to Any Task: Design universal metadata schemas that work for ANY NLP task, extending beyond current frameworks like lm-eval/DOVE to support specialized domains (e.g., machine translation) Group 2 - Save the Relevant: Develop efficient query/download systems for accessing only relevant data subsets from massive repositories (DOVE: 2TB, HELM: extensive metadata) The result will be open infrastructure for the AI research community, plus an academic publication. When? We're looking for researchers who can join ASAP and work with us for at least 5 to 7 months. We are hoping to find researchers who would take this on as an active project (8 hours+/week) in this period.

We seek to understand if there is interest in being able to attend NeurIPS in Europe, i.e. without travelling to San Diego, US. In the following, assume that it is possible to present accepted papers ...

Pulitzer-winning cartoonists are experimenting with AI image generators.