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
WebCiteS: Attributed Query-Focused Summarization on Chinese Web Search Results with Citations
Haolin Deng, Chang Wang, Xin Li, Dezhang Yuan, Junlang Zhan, Tianhua Zhou, Jin Ma, Jun Gao, Ruifeng Xu
Towards Self-Contained Answers: Entity-Based Answer Rewriting in Conversational Search
Ivan Sekulić, Krisztian Balog, Fabio Crestani