AI EVALUATION, IN CONTEXT.BY EQUALITY MACHINE

LLM Stats

QMSum

QMSum is a benchmark for query-based multi-domain meeting summarization consisting of 1,808 query-summary pairs over 232 meetings across academic, product, and committee domains. The dataset enables models to select and summarize relevant spans of meetings in response to specific queries. Published at NAACL 2021, QMSum presents significant challenges in long meeting summarization where models must identify and summarize relevant content based on user queries.

Evaluation context and evidence

Source
LLM Stats
Publisher
Not recorded
Benchmark release
Not recorded
Collected
2026-08-17
Modality
text

These are source-reported observations, not independent reruns by this site. Check the task version, evaluation protocol, unit and reporting date before comparing models. Results from different setups are not a universal ranking.

Original sources

Reported results 2

Shown in source observation order, not ranked. Dates retain the precision provided by the source.

ModelValueUnitProtocolReported date and basisSource
Phi-3.5-mini-instruct0.213Not recordedNot recorded2024-08-23 · model_announcementLLM Stats
Phi-3.5-MoE-instruct0.199Not recordedNot recorded2024-08-23 · model_announcementLLM Stats