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20232026
most citedOutlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity

2 citations · 3 across the 4 of their papers we have counts for

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cs.CL2025★ 1 cited

Learning to Reason for Hallucination Span Detection

Hsuan Su, Ting-Yao Hu, Hema Swetha Koppula +7

Large language models (LLMs) often generate hallucinations -- unsupported content that undermines reliability. While most prior works frame hallucination detection as a binary task…

cs.CL2024

Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning

Abhinav Bandari, Lu Yin, Cheng-Yu Hsieh +5

Network pruning has emerged as a potential solution to make LLMs cheaper to deploy. However, existing LLM pruning approaches universally rely on the C4 dataset as the calibration d…