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Found 8 papers, 4 papers with code
汉语学习者依存句法树库构建(Construction of a Treebank of Learner Chinese)
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。
Ensuring Safety and Trust: Analyzing the Risks of Large Language Models in Medicine
The remarkable capabilities of Large Language Models (LLMs) make them increasingly compelling for adoption in real-world healthcare applications.
CSRec: Rethinking Sequential Recommendation from A Causal Perspective
The essence of sequential recommender systems (RecSys) lies in understanding how users make decisions.
FMint: Bridging Human Designed and Data Pretrained Models for Differential Equation Foundation Model
The fast simulation of dynamical systems is a key challenge in many scientific and engineering applications, such as weather forecasting, disease control, and drug discovery.
Large Language Models and Causal Inference in Collaboration: A Comprehensive Survey
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.
DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization
To quantify this inactivity, we adopt dormant ratio as a metric to measure inactivity in the RL agent's network.
C-Disentanglement: Discovering Causally-Independent Generative Factors under an Inductive Bias of Confounder
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.
COMPILING: A Benchmark Dataset for Chinese Complexity Controllable Definition Generation
To the best of our knowledge, it is the largest dataset of the Chinese definition generation task.
