#Google Research

'Google Research's ReasoningBank converts agent traces into high-level strategies and, with MaTTS, yields large gains in effectiveness and efficiency at test time.'

'A curated guide to the top computer vision blogs and research hubs in 2025, focusing on sources that publish reproducible code, rigorous benchmarks, and production-ready guidance.'

'Google shows active learning can fine-tune LLMs with under 500 targeted labels, matching or improving model quality while reducing labeling needs by orders of magnitude.'

Google researchers introduced REFVNLI, a new cost-effective metric that jointly evaluates textual alignment and subject consistency in subject-driven text-to-image generation without relying on expensive APIs.