Tag
MOSAIC is a structured, conflict-aware long-term memory framework for LLM agents that uses entity-typed graph storage, hash-accelerated retrieval, and active conflict detection to achieve high accuracy and efficiency on long-conversation QA and factual conflict detection tasks.
This paper presents a conflict-free path-planning algorithm for en-route air traffic control, designed to be interpretable and computationally efficient for human operators. The algorithm integrates three conflict detection methods and achieves fast computation times, demonstrated on a real-world sector.
Atomic Memory is a tool that upgrades Ollama's memory system with per-turn updates, semantic recall, conflict detection, and cheap GPU usage, addressing limitations of Hermes' built-in memory. It uses a small dedicated model to provide efficient and unbounded memory management for individual or team use.
Verus is an open-source belief database for AI agents that tracks conflicting claims from multiple sources with confidence scores and conflict detection; the author seeks real-world datasets and feedback.
ConflictRAG is a conflict-aware RAG framework that detects, classifies, and resolves knowledge conflicts in retrieved documents, achieving 88.7% detection F1 and 5.3–6.1% correctness gains over baselines while reducing API costs by 62%.