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School of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai, 200240, P.R.China.
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Forget gradients: this new sampler learns complex distributions, even with discrete parameters, by enforcing time-reversibility and comparing forward and backward Markov trajectories.
Forget discrete search and trial-and-error prompting: nabla-Reasoner uses gradient descent in the LLM's latent space to boost reasoning accuracy by 20% while cutting model calls by up to 40%.
