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A researcher who published a sales-conversion model in March 2025 that predicts probabilities rather than generating text, with the paper, the weights and the dataset open, on seeing a funded lab announce the same shape. The replies mostly agreed on the shape and disagreed on the claim: his model is trained for one task, where what Jev is being credited with is doing this zero-shot for any set of choices.
nandakishor_ml, in Hacker News
Everyone now talks about the architecture that's not auto regressive and does lightning fast probability prediction with a json schema. I worked on this literally one year back in March 2025, published an arxiv paper, pushed the model to huggingface along with the pypi package and training dataset. And then one year later, a frontier lab came, proposing the same idea like literal breakthrough without technical papers, open weights and no open dataset.
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My model uses PPO over sequence embeddings to output turn-by-turn conversion trajectories (probabilities from 0.0 to 1.0). [...]
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