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cs.CL2024
Graph Neural Network Enhanced Retrieval for Question Answering of LLMs
Zijian Li, Qingyan Guo, Jiawei Shao +4
Retrieval augmented generation has revolutionized large language model (LLM) outputs by providing factual supports. Nevertheless, it struggles to capture all the necessary knowledg…
cs.CL2024
Mitigating Reversal Curse in Large Language Models via Semantic-aware Permutation Training
Qingyan Guo, Rui Wang, Junliang Guo +3
While large language models (LLMs) have achieved impressive performance across diverse tasks, recent studies showcase that causal LLMs suffer from the "reversal curse". It is a typ…