Evolving semantic indexes for generative retrieval
LLM-driven evolutionary search is starting to auto-design the discrete pieces of generative search indexes.
Context engineering, retrieval, long-horizon memory, knowledge for agents
LLM-driven evolutionary search is starting to auto-design the discrete pieces of generative search indexes.
How Latent Compaction treats the KV cache as a trainable latent and squeezes 32× context with minimal accuracy loss.
MM-KG makes explicit, testable links between patient data and biomedical graphs, changing how clinical LLM stacks should use knowledge.
Turning demo videos into navigable tool hierarchies instead of bloated prompts.
Turning repeated source access into reusable, source-specific competence for LLM agents