MTR-Suite: A Framework for Evaluating and Synthesizing Conversational Retrieval Benchmarks
Researchers have developed MTR-Suite, a new framework designed to improve the evaluation and creation of conversational retrieval benchmarks. This suite includes MTR-Eval, an LLM-based tool for assessing existing benchmarks, and MTR-Pipeline, a multi-agent system that generates realistic dialogues at a significantly reduced cost. The framework also introduces MTR-Bench, a general-domain benchmark that simulates complex conversational challenges like topic switching and verbosity. AI
IMPACT Introduces a new framework to improve the evaluation and creation of conversational retrieval benchmarks, potentially accelerating RAG system development.