5 citations · 6 across the 6 of their papers we have counts for
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cs.LG2024★ 5 cited
Llama Scope: Extracting Millions of Features from Llama-3.1-8B with Sparse Autoencoders
Zhengfu He, Wentao Shu, Xuyang Ge +9
Sparse Autoencoders (SAEs) have emerged as a powerful unsupervised method for extracting sparse representations from language models, yet scalable training remains a significant ch…
cs.CR2024★ 1 cited
WAPITI: A Watermark for Finetuned Open-Source LLMs
Lingjie Chen, Ruizhong Qiu, Siyu Yuan +6
Watermarking of large language models (LLMs) generation embeds an imperceptible statistical pattern within texts, making it algorithmically detectable. Watermarking is a promising…
cs.CL2024
"A good pun is its own reword": Can Large Language Models Understand Puns?
Zhijun Xu, Siyu Yuan, Lingjie Chen +1
Puns play a vital role in academic research due to their distinct structure and clear definition, which aid in the comprehensive analysis of linguistic humor. However, the understa…