3 papers
cs.IR2026
Beyond the Final Prompt: Measuring the Effect of Within-Conversation Context on AI Answers
Benjamin Tannenbaum
An isolated final user message is often treated as the query in evaluations of AI systems. In a conversation, however, the actionable request may be distributed across preceding tu…
cs.IR2026
The Prompt Is Not the Query: How Request State Evolves Across Multi-Turn AI Conversations
Benjamin Tannenbaum
AI-search evaluation commonly treats a prompt as a stable query that can be counted, classified, and replayed in isolation. A conversation makes that unit of analysis questionable:…
cs.IR2026
Answer-Reconstruction Search Density: Measuring the Query and Source Work Compressed by Conversational Answers
Benjamin Tannenbaum
Conversational systems can collapse a visible sequence of web queries, result inspections, and source comparisons into a single synthesized answer. Existing retrieval metrics evalu…