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Tian Yu

2 accepted papers

2024

Truth-Aware Context Selection: Mitigating Hallucinations of Large Language Models Being Misled by Untruthful Contexts

ACL 2024findings

Although Large Language Models (LLMs) have demonstrated impressive text generation capabilities, they are easily misled by untruthful contexts provided by users or knowledge augmentation tools, leading to hallucinations. To alleviate LLMs from being misled by untruthful context and take advantage of…

2024

TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space

ACL 2024long

Large Language Models (LLMs) sometimes suffer from producing hallucinations, especially LLMs may generate untruthful responses despite knowing the correct knowledge. Activating the truthfulness within LLM is the key to fully unlocking LLM’s knowledge potential. In this paper, we propose TruthX, an i…