BabyLM 2026 Strict-Small

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papersSEP 12 04:00 UTC

Qiushi Engine Reports Autonomous Research Run on BabyLM 2026 Strict-Small

An arXiv paper describes a long-horizon autonomous research program by Qiushi Engine targeting the BabyLM 2026 Strict-Small benchmark, which caps training data at 10 million words. The work examines how models can learn efficiently from limited text while retaining capabilities and generalizing to new inputs.

language-modeling/benchmarks/data-efficiency/autonomous-agents