Search Results for author: Jiaxin Yuan

Found 6 papers, 2 papers with code

汉语学习者依存句法树库构建(Construction of a Treebank of Learner Chinese)

no code implementations CCL 2020 Jialu Shi, Xinyu Luo, Liner Yang, Dan Xiao, Zhengsheng Hu, Yijun Wang, Jiaxin Yuan, Yu Jingsi, Erhong Yang

汉语学习者依存句法树库为非母语者语料提供依存句法分析, 可以支持第二语言教学与研究, 也对面向第二语言的句法分析、语法改错等相关研究具有重要意义。然而, 现有的汉语学习者依存句法树库数量较少, 且在标注方面仍存在一些问题。为此, 本文改进依存句法标注规范, 搭建在线标注平台, 并开展汉语学习者依存句法标注。本文重点介绍了数据选取、标注流程等问题, 并对标注结果进行质量分析, 探索二语偏误对标注质量与句法分析的影响。

FMint: Bridging Human Designed and Data Pretrained Models for Differential Equation Foundation Model

no code implementations23 Apr 2024 Zezheng Song, Jiaxin Yuan, Haizhao Yang

It incorporates in-context learning and has been pre-trained on a diverse corpus of 500, 000 dynamical systems, showcasing exceptional generalization across a broad spectrum of real-world applications.

In-Context Learning

Large Language Models and Causal Inference in Collaboration: A Comprehensive Survey

no code implementations14 Mar 2024 Xiaoyu Liu, Paiheng Xu, Junda Wu, Jiaxin Yuan, Yifan Yang, YuHang Zhou, Fuxiao Liu, Tianrui Guan, Haoliang Wang, Tong Yu, Julian McAuley, Wei Ai, Furong Huang

Causal inference has shown potential in enhancing the predictive accuracy, fairness, robustness, and explainability of Natural Language Processing (NLP) models by capturing causal relationships among variables.

Causal Inference Fairness

C-Disentanglement: Discovering Causally-Independent Generative Factors under an Inductive Bias of Confounder

1 code implementation NeurIPS 2023 Xiaoyu Liu, Jiaxin Yuan, Bang An, Yuancheng Xu, Yifan Yang, Furong Huang

Representation learning assumes that real-world data is generated by a few semantically meaningful generative factors (i. e., sources of variation) and aims to discover them in the latent space.

Disentanglement Inductive Bias

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