92 citations · 113 across the 9 of their papers we have counts for
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cs.CL2023★ 12 cited
FELM: Benchmarking Factuality Evaluation of Large Language Models
Shiqi Chen, Yiran Zhao, Jinghan Zhang +4
Assessing factuality of text generated by large language models (LLMs) is an emerging yet crucial research area, aimed at alerting users to potential errors and guiding the develop…
cs.CL2023★ 6 cited
Composing Parameter-Efficient Modules with Arithmetic Operations
Jinghan Zhang, Shiqi Chen, Junteng Liu +1
As an efficient alternative to conventional full finetuning, parameter-efficient finetuning (PEFT) is becoming the prevailing method to adapt pretrained language models. In PEFT, a…
cs.CL2023★ 92 cited
C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models
Yuzhen Huang, Yuzhuo Bai, Zhihao Zhu +10
New NLP benchmarks are urgently needed to align with the rapid development of large language models (LLMs). We present C-Eval, the first comprehensive Chinese evaluation suite desi…