The verifiable memory for the physical world, built to reuse across long-horizon multi-agent systems.

Neurosymbolic framework that catches LLM hallucinations mid-reasoning using causal graphs and GNNs. Converts chain-of-thought outputs into Causal Reasoning Graphs, detects flawed steps with a Graph Attention Network, and auto-corrects via RAG context injection ... before errors propagate.

Evidence-grounded medical RAG system that retrieves FDA and NICE drug guidelines, generates cited answers, and safely refuses unsupported queries to minimize hallucinations.

Hoshimiya Script / StarPolaris OS — internal multi-layer AI architecture for LLMs. Self-contained behavioral OS (Type-G Trinity).

Explicit control and observability over when an LLM should answer, hedge, or refuse — treating generation as a governed system layer, not a side effect of retrieval.

Trustworthy Agentic RAG prototype for scientific knowledge bases with multi-granularity retrieval, answer auditing, and conservative refusal.

Emergent pseudo-intimacy and emotional overflow in long-term human-AI dialogue: A case study on LLM behavior in affective computing and human-AI intimacy.

This repository will provide an organised list of research papers, relevant code, and a brief summary related to medical hallucination in Large Language and Large Vision-Language Models.