2 papers
cs.CL2026
GraphIF: Enhancing Multi-Turn Instruction Following for Large Language Models with Relation Graph Prompt
Zhenhe Li, Can Lin, Ling Zheng +3
Multi-turn instruction following is essential for building intelligent conversational systems that can consistently adhere to instructions across dialogue turns. However, existing…
cs.CL2025
Research on Multi-hop Inference Optimization of LLM Based on MQUAKE Framework
Zucheng Liang, Wenxin Wei, Kaijie Zhang +1
Accurately answering complex questions has consistently been a significant challenge for Large Language Models (LLMs). To address this, this paper proposes a multi-hop question dec…