MuSiQue

MuSiQue is a dataset used to evaluate multi-hop question answering systems by providing a collection of questions that require reasoning across multiple pieces of information.

Papers using MuSiQue (9)

Agent-Orchestrated Adaptive RAG: A Comparative Study on Structured and Multi-Hop Retrieval2026Cascading Hallucination in Agentic RAG: The CHARM Framework for Detection and Mitigation2026Retrieval as Reasoning: Self-Evolving Agent-Native Retrieval via LLM-Wiki2026Critic-R: Improving Agentic Search using Instruction-tuned Retrievers with Natural Language Introspective Feedback2026Natural Language Query to Configuration for Retrieval Agents2026GRASP: Graph Agentic Search over Propositions for Multi-hop Question Answering2026TAPE: Tool-guided Adaptive Planning And Constrained Execution In Language Model Agents2026Scaling Multi-agent Systems: A Smart Middleware for Improving Agent Interactions2026Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources2025