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AI Agents & Workflows

1247 summarised stories about AI Agents & Workflows, each linking back to the original source. Browse all topics →

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Thursday, 18 June 2026

MosaicLeaks: Can your research agent keep a secret?

Hugging Face 4 months ago 46

Research agents that combine private documents with web searches leak sensitive information through the cumulative pattern of their queries, even when individual searches appear innocuous. Across tested models, answer or full-information leakage reached 34.0% in baseline agents and climbed to 51.7% when agents were trained only for task performance. The Privacy-Aware Deep Research training method reduced leakage to 9.9% while maintaining 58.7% strict chain success by rewarding agents for constructing queries that avoid revealing private details.

Is it agentic enough? Benchmarking open models on your own tooling

Hugging Face 4 months ago 6

Researchers benchmarked how well different language models can use the transformers library by measuring not just whether they got the right answer, but how much effort it took them to get there. The evaluation framework tested each task across three different tool access levels (bare install, cloned source code, or packaged skill) and found that adding a CLI reduced median task completion time but increased token consumption by 60% due to agents reading documentation. The results show that library design significantly affects agent efficiency—smaller models benefited more from curated documentation while larger models sometimes performed better with full source code access.

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