Information Retrieval

What if you happen to might tune multimodal retrieval at serve time—buying and selling accuracy, latency, and index dimension—just by selecting what number of learnable Meta Tokens (e.g., 1→16 for queries, 1→64 for candidates) to make use of? Meta Superintelligence Labs introduces MetaEmbed, a late-interaction recipe for multimodal retrieval that exposes a single management floor…

Yandex has launched ARGUS (AutoRegressive Generative User Sequential modeling), a large-scale transformer-based framework for recommender methods that scales up to one billion parameters. This breakthrough locations Yandex amongst a small group of worldwide expertise leaders — alongside Google, Netflix, and Meta — which have efficiently overcome the long-standing technical limitations in scaling recommender transformers. Breaking…

Large Language Models (LLMs) have revolutionized many areas of natural language processing, but they still face critical limitations when dealing with up-to-date facts, domain-specific information, or complex multi-hop reasoning. Retrieval-Augmented Generation (RAG) approaches aim to address these gaps by allowing language models to retrieve and integrate information from external sources. However, most existing graph-based RAG…