Weizhu Chen15 papers on this site (2019–2024)AGIEval: A Human-Centric Benchmark for Evaluating Foundation ModelsWanjun Zhong, Ruixiang Cui, Yiduo Guo, et al.2024AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-TuningQingru Zhang, Minshuo Chen, Alexander Bukharin, et al.2023AnnoLLM: Making Large Language Models to Be Better Crowdsourced AnnotatorsXingwei He, Zhenghao Lin, Yeyun Gong, et al.2023Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated FeedbackBaolin Peng, Michel Galley, Pengcheng He, et al.2023CRITIC: Large Language Models Can Self-Correct with Tool-Interactive CritiquingZhibin Gou, Zhihong Shao, Yeyun Gong, et al.2023Enhancing Retrieval-Augmented Large Language Models with Iterative Retrieval-Generation SynergyZhihong Shao, Yeyun Gong, Yelong Shen, et al.2023Making Language Models Better Reasoners with Step-Aware VerifierYifei Li, Zeqi Lin, Shizhuo Zhang, et al.2023ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem SolvingZhibin Gou, Zhihong Shao, Yeyun Gong, et al.2023What Makes Good In-Context Examples for GPT-3?Jiachang Liu, Dinghan Shen, Yizhe Zhang, et al.2022DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding SharingPengcheng He, Jianfeng Gao, Weizhu Chen2021TAPEX: Table Pre-training via Learning a Neural SQL ExecutorQian Liu, Bei Chen, Jiaqi Guo, et al.2021DeBERTa: Decoding-enhanced BERT with Disentangled AttentionPengcheng He, Xiaodong Liu, Jianfeng Gao, et al.2020Generation-Augmented Retrieval for Open-domain Question AnsweringYuning Mao, Pengcheng He, Xiaodong Liu, et al.2020SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized OptimizationHaoming Jiang, Pengcheng He, Weizhu Chen, et al.2020Multi-Task Deep Neural Networks for Natural Language UnderstandingXiaodong Liu, Pengcheng He, Weizhu Chen, et al.2019