Rethinking AI Reasoning: A New Framework Challenges Conventional Wisdom
GRAPHEVAL, a graph-based reasoning framework, offers a fresh approach to addressing the flaws in LLM reasoning by introducing the Graph Reasoning Coherence Score and Graph Self-Consistency.
Read the full articleYou might also wanna read
MCP and Knowledge Graphs: GraphRAG, Multi-Hop Reasoning, and Structured AI Memory
How to connect AI agents to knowledge graphs via MCP — GraphRAG vs vector RAG, Neo4j and Memgraph MCP servers, Graphiti agent memory, and hy
Theoretical Perspective on Continuous Chain of Thoughts in Reasoning
Large Language Models (LLMs) have demonstrated remarkable performance in many applications, including challenging reasoning problems via cha
arxiv.org·1y ago
Comprehensive Survey of Reasoning Failures in Large Language Models
Large Language Models (LLMs) have exhibited remarkable reasoning capabilities, achieving impressive results across a wide range of tasks. De
arxiv.org·4mo ago
AI Evolution in 2025: From Stochastic Parrots to Chain of Thought Reasoning
blog comments powered by Disqus
antirez.com·6mo ago
Evaluating LangGraph for Agentic AI Workflows: A Decision-Maker's Guide
LangGraph is gaining real adoption for agentic AI workflows. But for most teams evaluating it, the question is not how to build a pipeline -
labyrinthanalyticsconsulting.com·1mo ago
Research Reveals Reasoning LLMs Lack Systematic Problem-Solving Capabilities
Large Language Models (LLMs) have demonstrated impressive reasoning abilities through test-time computation (TTC) techniques such as chain-o
arxiv.org·9mo ago
Comments
Sign in to join the conversation.
No comments yet. Be the first.