Search Results for author: Yunshi Lan

Found 11 papers, 7 papers with code

GradMA: A Gradient-Memory-based Accelerated Federated Learning with Alleviated Catastrophic Forgetting

1 code implementation28 Feb 2023 Kangyang Luo, Xiang Li, Yunshi Lan, Ming Gao

Federated Learning (FL) has emerged as a de facto machine learning area and received rapid increasing research interests from the community.

Continual Learning Federated Learning +1

Improving Compositional Generalization in Math Word Problem Solving

1 code implementation3 Sep 2022 Yunshi Lan, Lei Wang, Jing Jiang, Ee-Peng Lim

To improve the compositional generalization in MWP solving, we propose an iterative data augmentation method that includes diverse compositional variation into training data and could collaborate with MWP methods.

Data Augmentation Math Word Problem Solving

MWPToolkit: An Open-Source Framework for Deep Learning-Based Math Word Problem Solvers

1 code implementation2 Sep 2021 Yihuai Lan, Lei Wang, Qiyuan Zhang, Yunshi Lan, Bing Tian Dai, Yan Wang, Dongxiang Zhang, Ee-Peng Lim

Over the last few years, there are a growing number of datasets and deep learning-based methods proposed for effectively solving MWPs.

Math Word Problem Solving

Modeling Transitions of Focal Entities for Conversational Knowledge Base Question Answering

1 code implementation ACL 2021 Yunshi Lan, Jing Jiang

We propose a novel graph-based model to capture the transitions of focal entities and apply a graph neural network to derive a probability distribution of focal entities for each question, which is then combined with a standard KBQA module to perform answer ranking.

Knowledge Base Question Answering

Improving Multi-hop Knowledge Base Question Answering by Learning Intermediate Supervision Signals

1 code implementation11 Jan 2021 Gaole He, Yunshi Lan, Jing Jiang, Wayne Xin Zhao, Ji-Rong Wen

In our approach, the student network aims to find the correct answer to the query, while the teacher network tries to learn intermediate supervision signals for improving the reasoning capacity of the student network.

Knowledge Base Question Answering Semantic Parsing

Query Graph Generation for Answering Multi-hop Complex Questions from Knowledge Bases

no code implementations ACL 2020 Yunshi Lan, Jing Jiang

Previous work on answering complex questions from knowledge bases usually separately addresses two types of complexity: questions with constraints and questions with multiple hops of relations.

Graph Generation

Embedding WordNet Knowledge for Textual Entailment

no code implementations COLING 2018 Yunshi Lan, Jing Jiang

In this paper, we study how we can improve a deep learning approach to textual entailment by incorporating lexical entailment relations from WordNet.

Feature Engineering Lexical Entailment +1

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