While large language models (LLMs) have demonstrated impressive performance
in question-answering tasks, their performance is limited when the questions
require knowledge that is not included in the model's training data and can
only be acquired through direct observation or interaction with the real world.
Existing methods decompose reasoning tasks through the use of modules invoked
sequentially, limiting their ability to answer deep reasoning tasks. We
introduce a method, Recursion based extensible LLM (REBEL), which handles
open-world, deep reasoning tasks by employing automated reasoning techniques
like dynamic planning and forward-chaining strategies. REBEL allows LLMs to
reason via recursive problem decomposition and utilization of external tools.
The tools that REBEL uses are specified only by natural language description.
We further demonstrate REBEL capabilities on a set of problems that require a
deeply nested use of external tools in a compositional and conversational
setting.

使用递归解决方案和自动推理技术，REBEL 方法扩展了大型语言模型的能力，允许其在开放世界情境中进行深度推理任务和外部工具的使用。

LLM 引导的归纳推理在解决组合问题上的应用

LLM Guided Inductive Inference for Solving Compositional Problems

A simplified variant of Gödel's ontological argument is presented. The
simplified argument is valid already in basic modal logics K or KT, it does not
suffer from modal collapse, and it avoids the rather complex predicates of
essence (Ess.) and necessary existence (NE) as used by Gödel. The variant
presented has been obtained as a side result of a series of theory
simplification experiments conducted in interaction with a modern proof
assistant system. The starting point for these experiments was the computer
encoding of Gödel's argument, and then automated reasoning techniques were
systematically applied to arrive at the simplified variant presented. The
presented work thus exemplifies a fruitful human-computer interaction in
computational metaphysics. Whether the presented result increases or decreases
the attractiveness and persuasiveness of the ontological argument is a question
I would like to pass on to philosophy and theology.

提出了哥德尔本体论论证的简化变体，该变体使用的基本模态逻辑 K 或 KT 已经是有效的，并且避免了原论证中使用的复杂谓词，是一次计算形而上学中成功的人机交互实验。