Structural verification for graph databases. 5M vertices. 35 microseconds. Zero ML.
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Updated
Jun 13, 2026 - Python
Structural verification for graph databases. 5M vertices. 35 microseconds. Zero ML.
Internet never forgots and now thought police never fails
[EMNLP 2025] Think Wider, Detect Sharper: Reinforced Reference Coverage for Document-Level Self-Contradiction Detection.
A sophisticated semantic network system capable of encoding inference rules within the network itself. Built for efficient memory usage and powerful logical reasoning, zelph can process the entire Wikidata knowledge graph (1.7TB) to detect contradictions and make logical deductions.
A tool for auditing bias through large language models
Hybrid memory architecture combining exact recall with infinite-capacity fuzzy understanding for LLMs. Temporal Belief Graph (TBG) for contradiction detection.
A python script that uses Spacy library to detect contradiction among input statements
MedTrace is a PubMed-powered RAG application that retrieves, embeds, and analyzes biomedical literature, adding a contradiction detection layer to highlight supporting vs. opposing evidence and an LLM-as-a-judge evaluation module to score response relevance, groundedness, and confidence.
Contradiction Detection using LSTMs
MindGraph OS: An AI powered knowledge operating system that transforms documents and codebases into a living temporal knowledge graph with autonomous reasoning agents.
discover the unseen
Local-first provenance-aware concept graph for confidence-weighted claims, contradiction tracking, and TS-style inspectable knowledge memory.
Evaluating retrieval strategy bias in biomedical scientific claim verification using RAG — comparing dense, BM25, hybrid, and query-reformulation retrieval across Support Recall, Contradiction Recall, and Balance Score on SciFact.
🔍 Detect contradictions between AI skills — 15 categories, accumulation mode, bilingual IT/EN
LLM-powered deceptive review detection system using semantic embeddings and contradiction reasoning.
Rule-based and Transformer-based NLP Systems for detecting textual contradictions in paired witness statements
🔍 Detect contradictions between AI skills — 15 categories, accumulation mode, bilingual IT/EN
Token ranked neuro symbolic transformer with SQL working memory, causal graph reasoning, and adaptive belief consolidation for self explaining cognition.
Detects contradictions between courtroom testimony and case evidence in seconds.
The Marked Bench: a versioned contradiction-detection benchmark for AI reasoning evaluation.
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