[ACL 2023] Reasoning with Language Model Prompting: A Survey
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Updated
May 21, 2025
[ACL 2023] Reasoning with Language Model Prompting: A Survey
Framework and Language for Neurosymbolic Programming.
一本人生编程的教科书——当老天是 Python 程序员
ToK aka Tree of Knowledge for Large Language Models LLM. It's a novel dataset that inspires knowledge symbolic correlation in simple input and output prompts
[EMNLP '23] Discriminator-Guided Chain-of-Thought Reasoning
[ICML 2023] Answering Complex Logical Queries on Knowledge Graphs via Query Computation Tree Optimization
A symbolic benchmark for verifiable chain-of-thought financial reasoning. Includes executable templates, 58 topics across 12 domains, and ChainEval metrics.
Synthetic data generation for evaluating LLM symbolic and logic reasoning
Expert system with deductive querying and verification of constraints expressed in natural language
Production-ready Neuro-Symbolic AI & GraphRAG-powered Multi-domain Expert System. Hybrid forward/backward chaining inference engine over Neo4j Knowledge Graph + Qdrant Vector DB, operating across Chemistry, Plane Geometry, and Algebra domains via FastAPI & Streamlit.
Code and data for Paper "Enhancing Ethical Explanations of Large Language Models through Iterative Symbolic Refinement"
[EMNLP 2024] NormTab: Improving Symbolic Reasoning in LLMs Through Tabular Data Normalization
Participating in Explainable AI for Educational Question-Answering with Symbolic Reasoning
Mythral Neurosymbolic AI
ARC Prize 2024 Silver Medal Solution – Rule-based DSL symbolic reasoning system implemented in C++ for abstract grid transformation and search.
Official implementation of "A Deep Learning Model of Mental Rotation Informed by Interactive VR Experiments"
Training reliable AI models with neuro-symbolic verification and constraint-guided learning.
Team synchronization extension for Pi coding agent - coordinate work across team members
Complex-valued neuro-symbolic transformer using PyTorch.
MCP server + Python CLI for AI agents to do tarot, I Ching, and Xiao Liu Ren divination. Audited local scripts generate the result; the model only interprets.
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