@tunguz
BREAKING: the AI community discovers seed averaging and ensembling. Something we’ve been doing on Kaggle since … forever.
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BREAKING: the AI community discovers seed averaging and ensembling. Something we’ve been doing on Kaggle since … forever.
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"text": "Simply adding Gaussian noise to LLMs (one step—no iterations, no learning rate, no gradients) and ensembling them can achieve performance comparable to or even better than standard GRPO/PPO on math reasoning, coding, writing, and chemistry tasks. We call this algorithm RandOpt.\n\nTo verify that this is not limited to specific models, we tested it on Qwen, Llama, OLMo3, and VLMs.\n\nWhat's behind this? We find that in the Gaussian search neighborhood around pretrained LLMs, diverse task experts are densely distributed — a regime we term Neural Thickets.\n\nPaper: https://t.co/rFJz2kVEOA\nCode: https://t.co/HAmonfpXIA\nWebsite: https://t.co/QZ6AMIsKCw",
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