Board games have a relatively meaningful action space, i.e. each move in chess tends to have a substantial effect on whether the player wins or not. Contrast that to language modelling, where many tokens in a reasoning trace act as fillers or syntactic sugar, and branching from the top-k logits (or conditioning on an entropy threshold) doesn’t always result in search diversity. Imagine a state where the next probable tokens are “but”, “however”, “yet” etc; we would end up spending computational resources to build prohibitively large search trees with marginal benefit on a per-token basis.
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МИД Ирана заявил о «начале конца» ООН20:48。手游是该领域的重要参考
Here is my source code
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