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cs.CL2025
Teaching Large Language Models to Maintain Contextual Faithfulness via Synthetic Tasks and Reinforcement Learning
Shuzheng Si, Haozhe Zhao, Cheng Gao +11
Teaching large language models (LLMs) to be faithful in the provided context is crucial for building reliable information-seeking systems. Therefore, we propose a systematic framew…
cs.CL2025
GLTW: Joint Improved Graph Transformer and LLM via Three-Word Language for Knowledge Graph Completion
Kangyang Luo, Yuzhuo Bai, Cheng Gao +11
Knowledge Graph Completion (KGC), which aims to infer missing or incomplete facts, is a crucial task for KGs. However, integrating the vital structural information of KGs into Larg…
cs.CL2024★ 1 cited
FastFiD: Improve Inference Efficiency of Open Domain Question Answering via Sentence Selection
Yufei Huang, Xu Han, Maosong Sun
Open Domain Question Answering (ODQA) has been advancing rapidly in recent times, driven by significant developments in dense passage retrieval and pretrained language models. Curr…