Search Engine
Search engines are evolving rapidly, driven by the integration of large language models (LLMs) and a shift towards more conversational and multimodal interfaces. Current research focuses on improving the accuracy and relevance of search results, particularly for complex queries and diverse data types, using techniques like retrieval-augmented generation (RAG) and multi-agent systems. This research is significant because it impacts not only the efficiency and effectiveness of information retrieval but also the reliability and trustworthiness of online information, with implications for various fields from education to healthcare.
Papers
Towards a Search Engine for Machines: Unified Ranking for Multiple Retrieval-Augmented Large Language Models
Alireza Salemi, Hamed Zamani
GUing: A Mobile GUI Search Engine using a Vision-Language Model
Jialiang Wei, Anne-Lise Courbis, Thomas Lambolais, Binbin Xu, Pierre Louis Bernard, Gérard Dray, Walid Maalej