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A developer building an AI legal assistant for a German law firm details seven specific LLM citation failure modes and the prompt-engineering fixes used to meet strict legal citation standards.
Lyzr Cognis introduces a unified, open-source memory system for conversational AI that fuses BM25 and Matryoshka vector search with version-aware ingestion, achieving SOTA on LoCoMo and LongMemEval benchmarks.
Analyzes the 64-D embedding manifold of Google AlphaEarth across 12.1M U.S. samples, shows non-Euclidean structure and poor vector arithmetic, then builds an agentic system with geometry-aware tools that outperforms parametric baselines on environmental queries.
Skill-RAG is a failure-aware RAG framework that uses hidden-state probing and skill routing to diagnose and correct query-evidence misalignment in retrieval-augmented generation. The approach detects retrieval failures and selectively applies targeted skills (query rewriting, question decomposition, evidence focusing) to improve accuracy on hard cases and out-of-distribution datasets.