Research

Evaluation Cards selected as a spotlight paper at NeurIPS 2026

A paper on how AI evaluation results are reported, written with the EvalEval Coalition and co-authored by Nathan Heath and Dr. Wm. Matthew Kennedy, will be presented as a spotlight at NeurIPS 2026 in Sydney.

By Syntony8 to 10 December 2026 · NeurIPS · SydneyPublished 3 November 2026
Title card reading Evaluation Cards, NeurIPS 2026 Sydney, spotlight paper, beside a stack of evaluation cards that list what was tested and what is missing.
Evaluation Cards, a NeurIPS 2026 spotlight paper.

Evaluation Cards: An Interpretive Layer for AI Evaluation Reporting has been selected as a spotlight paper at NeurIPS 2026. Syntony founder Nathan Heath and Dr. Wm. Matthew Kennedy, Syntony’s Head of Research Strategy and Evaluations, are among its 48 authors. The paper appears in the conference’s Evaluations and Datasets track and will be presented in Sydney.

The work comes from the EvalEval Coalition, a group of researchers working on how AI evaluations are designed, run and reported. The author list includes Avijit Ghosh, Anka Reuel, Irene Solaiman, Stella Biderman, Sanmi Koyejo, Mykel Kochenderfer and Yacine Jernite.

What the paper addresses

Benchmark scores often travel without their context. A number in a model release rarely says what was tested, how it was scored, whether it can be compared with other results, or what it leaves out. Evaluation Cards add an interpretive layer to evaluation reporting so that a reader can see what a result supports before relying on it.

The paper combines a review of the literature, an analysis of how evaluations are reported in practice, an interview study and a working website.

Conference details
NeurIPS 2026 · Sydney
8 to 10 December 2026

Evaluations and Datasets track, spotlight paper.

The question at the center of the paper runs through Syntony’s work: whether the evidence behind a claim about an AI system supports the decision being made on it.

Read the paper on arXiv or explore the Evaluation Cards project.