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cs.CL2025
Do Retrieval Augmented Language Models Know When They Don't Know?
Youchao Zhou, Heyan Huang, Yicheng Liu +5
Existing large language models (LLMs) occasionally generate plausible yet factually incorrect responses, known as hallucinations. Two main approaches have been proposed to mitigate…
cs.CL2022
U3E: Unsupervised and Erasure-based Evidence Extraction for Machine Reading Comprehension
Suzhe He, Shumin Shi, Chenghao Wu
More tasks in Machine Reading Comprehension(MRC) require, in addition to answer prediction, the extraction of evidence sentences that support the answer. However, the annotation of…