TL;DR
The overall objectives of the CLEF 2017 Dynamic Search Lab are described, the resources created for the pilot task, the resources created for the pilot task and the evaluation methodology adopted.
This work extends the existing Exquisitor URF system with conversational search, and the user interface has been completely redesigned to prepare for future integration with conversational search and better support novice users.
The results show that modern agents can autonomously operate interactive video retrieval systems to solve many search tasks from an initial intent description, achieving performance competitive with strong historical expert-operated systems in several settings.
Agentic Conversational Recommender Systems (ACRSs), in which a large language model orchestrates dialogue, item retrieval, and tool use (such as querying item attributes or ranking candidate items), are advancing quickly, yet two problems prevent us from fully understanding their potential and limitations. First, progr...
Conversational LLM agents increasingly rely on Web search, yet the end-to-end lifecycle of agentic search remains poorly understood. We present the first study of Web search across four major conversational platforms (ChatGPT, Claude, Grok, and DeepSeek), combining real-world user interactions (invivo) with controlled...
It is concluded that conversational elicitation is an effective mechanism for narrowing the expertise gap in this domain, and that the lexical results motivate pairing it with hybrid sparse–dense retrieval.
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