---
title: "Xiaodong Liu — papers"
description: "Xiaodong Liu: 10 papers in the Elamur Research library (2015–2026) — our summary of each, its ideas, references and who cites it."
canonical: "https://research.elamur.ai/free/en/authors/xiaodong-liu/"
---
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# Xiaodong Liu

10 papers on this site (2015–2026)

[OpenAlex](https://openalex.org/A5100374810) · [ORCID](https://orcid.org/0009-0004-6648-2302) · h-index 21 · 61 works · 8000 citations (openalex-snapshot, 2026-10-14)

Profile data from OpenAlex; authors with the same name are not always told apart.

- [Consistency of LLMs to Comparative Statements in Mathematical Reasoning Tasks](https://md.research.elamur.ai/free/en/papers/san-2026-consistency-llms-comparative-statements-mathematical/) — Aidan W. San, Daniel Juyoung Son, Xiaodong Liu, et al. · 2026
- [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
- [UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training](https://md.research.elamur.ai/free/en/papers/bao-2020-unilmv2-pseudo-masked-language-models/) — Hangbo Bao, Li Dong, Furu Wei, 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
- [Unified Language Model Pre-training for Natural Language Understanding and Generation](https://md.research.elamur.ai/free/en/papers/dong-2019-unified-language-model-pre-training/) — Li Dong, Nan Yang, Wenhui Wang, et al. · 2019
- [ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension](https://md.research.elamur.ai/free/en/papers/zhang-2018-record-bridging-gap-between-human/) — Sheng Zhang, Xiaodong Liu, Jingjing Liu, et al. · 2018
- [MS MARCO: A Human Generated MAchine Reading COmprehension Dataset](https://md.research.elamur.ai/free/en/papers/bajaj-2016-ms-marco-human-generated/) — Payal Bajaj, Daniel Campos, Nick Craswell, et al. · 2016
- [Representation Learning Using Multi-Task Deep Neural Networks for Semantic Classification and Information Retrieval](https://md.research.elamur.ai/free/en/papers/liu-2015-representation-learning-multi-task-deep/) — Xiaodong Liu, Jianfeng Gao, Xiaodong He, et al. · 2015