3 papers
cs.CL2026
Finding the Cracks: Improving LLMs Reasoning with Paraphrastic Probing and Consistency Verification
Weili Shi, Dongliang Guo, Lehan Yang +3
Large language models have demonstrated impressive performance across a variety of reasoning tasks. However, their problem-solving ability often declines on more complex tasks due…
cs.CL2025
GraphCheck: Breaking Long-Term Text Barriers with Extracted Knowledge Graph-Powered Fact-Checking
Yingjian Chen, Haoran Liu, Yinhong Liu +8
Large language models (LLMs) are widely used, but they often generate subtle factual errors, especially in long-form text. These errors are fatal in some specialized domains such a…
cs.CL2025
MKG-Rank: Enhancing Large Language Models with Knowledge Graph for Multilingual Medical Question Answering
Feiyang Li, Yingjian Chen, Haoran Liu +10
Large Language Models (LLMs) have shown remarkable progress in medical question answering (QA), yet their effectiveness remains predominantly limited to English due to imbalanced m…