Science Explained/Brief

New benchmark and method aim to forecast meeting continuations

A preprint describes a benchmark built from 2,207 real meetings and a method called GLARE that generates plausible meeting continuations. The results are from human evaluations, but the work has not yet been peer-reviewed.

BriefPublished 14 September 20261 min read1 linked source · 3 checked facts

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The abstract reports that GLARE achieved average human-evaluated win rates of 0.66 on utility and 0.70 on human-likeness, outperforming SFT and SPIN but remaining below human continuations. The benchmark includes 24,794 future-facing queries. As a preprint, these results have not been independently verified.

What the reporting says

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Stated by arXiv

The Meeting Dynamic Forecasting Benchmark (MDFB) was constructed from 2,207 real-world meetings and 24,794 future-facing queries.
GLARE attains average human-evaluated win rates of 0.66 on utility and 0.70 on human-likeness.
GLARE outperforms SFT and SPIN while remaining below the observed human continuation.

Our view

This preprint offers a new way to evaluate meeting forecasting, but the lack of peer review means the win rates should be treated as preliminary.

What the reporting says: The abstract states that GLARE attains average human-evaluated win rates of 0.66 on utility and 0.70 on human-likeness, outperforming SFT and SPIN while remaining below the observed human continuation.

Sources

arXivText stored 14 September 2026 · checked 14 September 2026

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New benchmark and method aim to forecast meeting continuations

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GLARE method outperforms SFT and SPIN on meeting continuation benchmark

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