A neurosymbolic perspective on LLMs
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Updated
Mar 21, 2026 - Python
A neurosymbolic perspective on LLMs
Logic Language for LLMs 🌱🐋🌍 Build Neuro-Symbolic AI for learning and reasoning
Deterministic verification layer for AI. QWED verifies LLM outputs using math, logic, and symbolic execution — creating an auditable trust boundary for agentic AI systems. Not generation. Verification.
Domain-Aware Neurosymbolic Agent (Dana), an agent-native programming language
A collection of neuro-symbolic systems, papers and videos
Web knowledge is fragmented — duplicated across fonts, embeddings, metadata, and renderings. Humans see pixels, AI sees tokens, neither shares the source. Knowledge3D: a sovereign GPU-native reference implementation for W3C PM-KR, where humans and AI consume the same procedural knowledge from one source.
Differentiable probabilistic answer set programming
Scalable association rule mining from tabular datasets.
Sparse Circuits on the GPU (ICLR2025)
Code for the ICLR 2024 paper "How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data"
Official repository for CoTran: An LLM-based code translator for whole-program translation, fine-tuned using feedback from compiler and symbolic execution
An advanced tool for generating, visualizing, and evaluating domain-specific knowledge graphs and ontologies.
Unleash the fuzz on your C codebase.
A Recursive Ontological Framework for Cognitive Design, Neurodivergence Modeling, AI Co-Development, and "Structural AI"
An intelligent, multi-agent framework for artificial biome simulation.
A dedicated repository for learning and researching about neuro-symbolic artificial intelligence (NSAI)
🎓 Free course on deterministic AI verification. Learn how to mathematically prove LLM output correctness using formal methods. From theory to production workflows with QWED-AI.
Code and data of "NeSIG: A Neuro-Symbolic Method for Learning to Generate Planning Problems"
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