Researchers proposed REALM, a reconsolidation-evolution agentic long-term memory framework for LLM agents that models memory as a continual lifecycle, organizing memories into a heterogeneous cognitiv…
Retrieval-augmented generation (RAG) gives a language model a temporary, query-specific memory by searching an external corpus, selecting evidence, and placing it in the prompt before the model answer…
Researchers introduced REALM, the first unified red-teaming benchmark for physical-world vision-language models (VLMs), integrating 12 attack methods, 3 defenses, and 13 VLMs under a black-box threat …
Google AI Mode, ChatGPT Search, Perplexity Pro Search, and other major AI search platforms have abandoned single-shot retrieval-augmented generation (RAG) in favor of "agentic RAG," a multi-step archi…