mzio/aprm-sft-thoughts-tau2-retail

Act-PRM SFT thoughts — tau2-bench retail Act-PRM (Action Process Reward Models) infers the latent thoughts behind logged, action-only agent demonstrations via an offline EM. For each logged action x in state s we sample G=4 candidate thoughts z, score each by the length-penalized action likelihood reward(z) = p(x | s, z) - 0.15 * len_frac (len_frac grows with the thought's token length), and mark the best thought (argmax reward). The (thought + action) span is then what… See the full description on the dataset page: https://huggingface.co/datasets/mzio/aprm-sft-thoughts-tau2-retail.