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FACTS Grounding benchmark

FACTS Grounding is a Google DeepMind benchmark family for "systematically evaluating the factuality of large language models" — introduced on the DeepMind blog and extended into a benchmark suite. Cited in the 2026-05-28 Google Research I/O 2026 roundup post as the substrate of Google's multi-year factuality research programme (Source: sources/2026-05-28-google-a-new-era-of-innovation-google-research-at-io-2026).

This is a minimum-viable wiki page anchored to the I/O 2026 post's pointers to the FACTS family. Benchmark specification (prompt design, scoring rubric, dataset composition, leaderboard results) lives in the linked DeepMind blog posts and underlying papers, not in this source's raw capture.

Multi-year arc

The Google I/O 2026 post frames factuality as a sustained research arc anchored on FACTS:

The FACTS family is Google's preferred measurement substrate for factuality decisions on Gemini-family models, and a sibling research thread to the latency-decoding work (speculative decoding, speculative cascades) and factuality-decoding work (SLED, factuality decoding).

Seen in

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