[R] SymbolicAI: A framework for logic-based approaches combining generative models and solvers

**Paper**: [https://arxiv.org/abs/2402.00854](https://arxiv.org/abs/2402.00854)

**Code**: [https://github.com/ExtensityAI/symbolicai](https://github.com/ExtensityAI/symbolicai)

**Benchmark**: [https://github.com/ExtensityAI/benchmark](https://github.com/ExtensityAI/benchmark)

**Abstract**:

>We introduce **SymbolicAI**, a versatile and modular framework employing a logic-based approach to concept learning and flow management in generative processes. SymbolicAI enables the seamless integration of generative models with a diverse range of solvers by treating large language models (LLMs) as semantic parsers that execute tasks based on both natural and formal language instructions, thus bridging the gap between symbolic reasoning and generative AI. We leverage probabilistic programming principles to tackle complex …

abstract concept diverse flow framework gap generative generative models integration language language models large language large language models llms logic machinelearning management modular natural processes seamless integration semantic tasks