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pro vyhledávání: '"Geh, Renato Lui"'
Large Language Models (LLMs) are typically shipped with tokenizers that deterministically encode text into so-called canonical token sequences, to which the LLMs assign probability values. One common assumption is that the probability of a piece of t
Externí odkaz:
http://arxiv.org/abs/2408.08541
Autor:
Geh, Renato Lui, Gonçalves, Jonas, Silveira, Igor Cataneo, Mauá, Denis Deratani, Cozman, Fabio Gagliardi
We present dPASP, a novel declarative probabilistic logic programming framework for differentiable neuro-symbolic reasoning. The framework allows for the specification of discrete probabilistic models with neural predicates, logic constraints and int
Externí odkaz:
http://arxiv.org/abs/2308.02944