Large Language Models

[TOC] Title: From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of Thought Author: Lionel Wong et. al. Publish Year: 23 Jun 2023 Review Date: Sun, Jul 2, 2023 url: https://arxiv.org/pdf/2306.12672.pdf Summary of paper Motivation leverage a theory of linguistic meaning to build machines that think in more human-like ways. we frame linguistic meaning as a context-sensitive mapping from NL into a probabilistic language of thought (PLoT) – a general-purpose symbolic substrate for probabilistic, generative world modelling...

[TOC] Title: Boosting Language Models Reasoning With Chain of Knowledge Prompting Author: Jianing Wang et. al. Publish Year: 10 Jun 2023 Review Date: Sun, Jul 2, 2023 url: https://arxiv.org/pdf/2306.06427.pdf Summary of paper Motivation “Chain of Thought (CoT)” aims at designing a simple prompt like “Let’s think step by step” however, the generated rationales often come with mistakes, making unfactual and unfaithful reasoning chain To mitigate this brittleness, we propose a novel Chain-of-Knowlege knowledge evidence in the form of structure triple Contribution Benefiting from CoK, we additional introduce a F^2 -Verification method to estimate the reliable response, the wrong evidence can be indicated to prompt the LLM to rethink....