10 citations · 14 across the 14 of their papers we have counts for
4 papers · 1 filter
ConsistentChat: Building Skeleton-Guided Consistent Multi-Turn Dialogues for Large Language Models from Scratch
Jiawei Chen, Xinyan Guan, Qianhao Yuan +7
Current instruction data synthesis methods primarily focus on single-turn instructions and often neglect cross-turn coherence, resulting in context drift and reduced task completio…
REInstruct: Building Instruction Data from Unlabeled Corpus
Shu Chen, Xinyan Guan, Yaojie Lu +3
Manually annotating instruction data for large language models is difficult, costly, and hard to scale. Meanwhile, current automatic annotation methods typically rely on distilling…
Mitigating Large Language Model Hallucinations via Autonomous Knowledge Graph-based Retrofitting
Xinyan Guan, Yanjiang Liu, Hongyu Lin +4
Incorporating factual knowledge in knowledge graph is regarded as a promising approach for mitigating the hallucination of large language models (LLMs). Existing methods usually on…
Improving Temporal Generalization of Pre-trained Language Models with Lexical Semantic Change
Zhaochen Su, Zecheng Tang, Xinyan Guan +3
Recent research has revealed that neural language models at scale suffer from poor temporal generalization capability, i.e., the language model pre-trained on static data from past…