--- title: "Weizhu Chen — papers" description: "Weizhu Chen: 16 papers in the Elamur Research library (2019–2024) — our summary of each, its ideas, references and who cites it." canonical: "https://research.elamur.ai/free/en/authors/weizhu-chen/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/weizhu-chen/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Weizhu Chen # Weizhu Chen 16 papers on this site (2019–2024) [OpenAlex](https://openalex.org/A5051745436) · [ORCID](https://orcid.org/0000-0003-4196-7229) · h-index 48 · 249 works · 10419 citations (openalex-snapshot, 2026-10-14) Profile data from OpenAlex; authors with the same name are not always told apart. - [AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models](https://md.research.elamur.ai/free/en/papers/zhong-2024-agieval-human-centric-benchmark-evaluating/) — Wanjun Zhong, Ruixiang Cui, Yiduo Guo, et al. · 2024 - [AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning](https://md.research.elamur.ai/free/en/papers/zhang-2023-adalora-adaptive-budget-allocation-parameter/) — Qingru Zhang, Minshuo Chen, Alexander Bukharin, et al. · 2023 - [AnnoLLM: Making Large Language Models to Be Better Crowdsourced Annotators](https://md.research.elamur.ai/free/en/papers/he-2023-annollm-making-large-language-models/) — Xingwei He, Zhenghao Lin, Yeyun Gong, et al. · 2023 - [Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback](https://md.research.elamur.ai/free/en/papers/peng-2023-check-facts-try-again-improving/) — Baolin Peng, Michel Galley, Pengcheng He, et al. · 2023 - [CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing](https://md.research.elamur.ai/free/en/papers/gou-2023-critic-large-language-models-self/) — Zhibin Gou, Zhihong Shao, Yeyun Gong, et al. · 2023 - [Enhancing Retrieval-Augmented Large Language Models with Iterative Retrieval-Generation Synergy](https://md.research.elamur.ai/free/en/papers/shao-2023-enhancing-retrieval-augmented-large-language/) — Zhihong Shao, Yeyun Gong, Yelong Shen, et al. · 2023 - [Making Language Models Better Reasoners with Step-Aware Verifier](https://md.research.elamur.ai/free/en/papers/li-2023-making-language-models-better-reasoners/) — Yifei Li, Zeqi Lin, Shizhuo Zhang, et al. · 2023 - [ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving](https://md.research.elamur.ai/free/en/papers/gou-2023-tora-tool-integrated-reasoning-agent/) — Zhibin Gou, Zhihong Shao, Yeyun Gong, et al. · 2023 - [A Token-level Reference-free Hallucination Detection Benchmark for Free-form Text Generation](https://md.research.elamur.ai/free/en/papers/liu-2022-token-level-reference-free-hallucination/) — Tianyu Liu, Yizhe Zhang, Chris Brockett, et al. · 2022 - [What Makes Good In-Context Examples for GPT-3?](https://md.research.elamur.ai/free/en/papers/liu-2022-what-makes-good-context-examples/) — Jiachang Liu, Dinghan Shen, Yizhe Zhang, et al. · 2022 - [DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing](https://md.research.elamur.ai/free/en/papers/he-2021-debertav3-improving-deberta-using-electra/) — Pengcheng He, Jianfeng Gao, Weizhu Chen · 2021 - [TAPEX: Table Pre-training via Learning a Neural SQL Executor](https://md.research.elamur.ai/free/en/papers/liu-2021-tapex-table-pre-training-learning/) — Qian Liu, Bei Chen, Jiaqi Guo, et al. · 2021 - [DeBERTa: Decoding-enhanced BERT with Disentangled Attention](https://md.research.elamur.ai/free/en/papers/he-2020-deberta-decoding-enhanced-bert-disentangled/) — Pengcheng He, Xiaodong Liu, Jianfeng Gao, et al. · 2020 - [Generation-Augmented Retrieval for Open-domain Question Answering](https://md.research.elamur.ai/free/en/papers/mao-2020-generation-augmented-retrieval-open-domain/) — Yuning Mao, Pengcheng He, Xiaodong Liu, et al. · 2020 - [SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization](https://md.research.elamur.ai/free/en/papers/jiang-2020-smart-robust-efficient-fine-tuning/) — Haoming Jiang, Pengcheng He, Weizhu Chen, et al. · 2020 - [Multi-Task Deep Neural Networks for Natural Language Understanding](https://md.research.elamur.ai/free/en/papers/liu-2019-multi-task-deep-neural-networks/) — Xiaodong Liu, Pengcheng He, Weizhu Chen, et al. · 2019