Google Research posts Harness2, a recursive agent harness
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Stories tagged #google-research
Google Research RRSI Guide: Mastering Self-Improving AI Agents
Google Research's RRSI uses noise bands, cost rules, and leakage screens for safer self-improving AI agents.
A Coding Guide to Google Research’s Kauldron: Configs That Are Plain Data, Components Wired by String, and a JAX Trainer You Can Read End to End
A coding guide demonstrates Google Research's Kauldron, a modular JAX trainer using plain-data configs and string wiring.
Google Research Open-Sources RRSI: AI Agents That Improve Their Own Harness Without Overfitting
Google Research open-sourced RRSI, letting frozen-weight agents improve their harness without overfitting benchmarks.
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A Coding Guide to Google Research’s MSEB: Writing Sound Encoders to the Benchmark Contract and Scoring Them Across Classification, Clustering, Retrieval and Segmentation
A tutorial implements sound encoders for Google Research's MSEB and scores them on four audio tasks.
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RRSI: Regularized Recursive Self-Improvement of Agent Harnesses
Google Research's RRSI regularizes recursive agent-harness edits, lifting held-out scores while cutting policy tokens.
RRSI: Regularized Recursive Self-Improvement of Agent Harnesses
Google Research's RRSI regularizes recursive agent-harness evolution, lifting out-of-distribution scores while cutting policy tokens 30%.
Google Research Introduces Retrieve-for-Train (R4T): An RL-Compiled Diffusion Retriever for 12× to 20× Faster Query Fan-Out
Google Research introduced R4T, an RL-trained fan-out pipeline distilled into a 53.9M-parameter diffusion retriever achieving 12x-20x faster query fan-out.
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Google Research Releases ToolGrad: Answer-First Framework Hits 99.8% Pass Rate for Tool-Use Data Generation
Google Research and partners introduce ToolGrad, a verified tool-chain-first data generation framework reaching 99.8% pass rate and boosting Gemma-3-12B to 83.1 on BFCL.
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