New agentic memory framework uses 118K tokens per query. LangMem burns through 3.26M.

NUS researchers' MRAgent framework reduces LLM agent memory retrieval to 118K tokens per query — vs. 3.26M for LangMem — using step-by-step reasoning.
IEEE

Optimizing Query-by-Example Spoken Term Detection with Audio-to-Token Sequence Clustering and Query-Guided Retrieval

Abstract: Query-by-Example Spoken Term Detection (QbE-STD) retrieves relevant audio files corresponding to a spoken query, without relying on explicit word-level textual transcriptions. In ...

How to use Google query expansion to improve content visibility

Your content may already be surfacing for searches you never planned for. Here's how to identify those opportunities and act ...