Summary

This repository addresses the limitations of Large Language Models (LLMs) in complex reasoning and planning by curating the latest advances in Neuro-Symbolic (NeSy) learning. It serves researchers and engineers by providing a comprehensive collection of papers, tutorials, and benchmarks, enabling them to leverage NeSy techniques to enhance LLM capabilities.

How It Works

The project compiles research that bridges neural network-based LLMs with symbolic reasoning systems. It categorizes approaches based on how symbolic components are integrated with LLMs, such as symbolic generation, LLM formalization, program-aided methods, and tool-assisted reasoning. This structured curation highlights novel architectures and methodologies designed to imbue LLMs with more robust logical and planning skills.

Quick Start & Requirements

This repository is a curated list of research papers and resources, not a runnable software project. Therefore, it does not have installation instructions or specific software requirements. Users are directed to the individual papers and projects for their respective setup details.

Highlighted Details

• Broad Scope: Encompasses tutorials, surveys, foundational frameworks, and diverse integration strategies for NeSy LLMs.
• Extensive Benchmarks: Features a wide array of datasets and benchmarks for evaluating LLM reasoning across mathematical, logical, visual, and code generation tasks.
• Interdisciplinary Coverage: Covers applications in AI planning, theorem proving, robotics, and agent development, showcasing the versatility of NeSy approaches.

Maintenance & Community

The provided README does not contain information regarding project maintenance, specific contributors, sponsorships, or community channels (e.g., Discord, Slack). It appears to be a static, curated collection of research links.

Licensing & Compatibility

No specific licensing information is provided within the README. Users should refer to the individual linked papers and projects for their respective licenses and compatibility terms.

Limitations & Caveats

As a curated list, its comprehensiveness is dependent on the last update. The rapidly evolving field of LLMs and neuro-symbolic AI means new advancements may emerge frequently. It serves as a research guide rather than a deployable system, thus lacking direct software limitations but reflecting the ongoing research challenges in the domain.