Search Results for author: Shulin Cao

Found 7 papers, 4 papers with code

GraphQ IR: Unifying Semantic Parsing of Graph Query Language with Intermediate Representation

no code implementations24 May 2022 Lunyiu Nie, Shulin Cao, Jiaxin Shi, Qi Tian, Lei Hou, Juanzi Li, Jidong Zhai

Subject to the semantic gap lying between natural and formal language, neural semantic parsing is typically bottlenecked by the paucity and imbalance of data.

Few-Shot Learning Semantic Parsing

Schema-Free Dependency Parsing via Sequence Generation

no code implementations28 Jan 2022 Boda Lin, Zijun Yao, Jiaxin Shi, Shulin Cao, Binghao Tang, Si Li, Yong Luo, Juanzi Li, Lei Hou

To remedy these drawbacks, we propose to achieve universal and schema-free Dependency Parsing (DP) via Sequence Generation (SG) DPSG by utilizing only the pre-trained language model (PLM) without any auxiliary structures or parsing algorithms.

Dependency Parsing Language Modelling

Program Transfer for Answering Complex Questions over Knowledge Bases

1 code implementation ACL 2022 Shulin Cao, Jiaxin Shi, Zijun Yao, Xin Lv, Jifan Yu, Lei Hou, Juanzi Li, Zhiyuan Liu, Jinghui Xiao

In this paper, we propose the approach of program transfer, which aims to leverage the valuable program annotations on the rich-resourced KBs as external supervision signals to aid program induction for the low-resourced KBs that lack program annotations.

Program induction Semantic Parsing

TransferNet: An Effective and Transparent Framework for Multi-hop Question Answering over Relation Graph

1 code implementation EMNLP 2021 Jiaxin Shi, Shulin Cao, Lei Hou, Juanzi Li, Hanwang Zhang

Multi-hop Question Answering (QA) is a challenging task because it requires precise reasoning with entity relations at every step towards the answer.

Multi-hop Question Answering Question Answering

OpenKE: An Open Toolkit for Knowledge Embedding

1 code implementation EMNLP 2018 Xu Han, Shulin Cao, Xin Lv, Yankai Lin, Zhiyuan Liu, Maosong Sun, Juanzi Li

We release an open toolkit for knowledge embedding (OpenKE), which provides a unified framework and various fundamental models to embed knowledge graphs into a continuous low-dimensional space.

Information Retrieval Knowledge Graphs +2

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