26 citations · 212 across the 74 of their papers we have counts for
9 papers · 2 filters
ITA: Image-Text Alignments for Multi-Modal Named Entity Recognition
Xinyu Wang, Min Gui, Yong Jiang +6
Recently, Multi-modal Named Entity Recognition (MNER) has attracted a lot of attention. Most of the work utilizes image information through region-level visual representations obta…
Bottom-Up Constituency Parsing and Nested Named Entity Recognition with Pointer Networks
Songlin Yang, Kewei Tu
Constituency parsing and nested named entity recognition (NER) are similar tasks since they both aim to predict a collection of nested and non-crossing spans. In this work, we cast…
Combining (second-order) graph-based and headed-span-based projective dependency parsing
Songlin Yang, Kewei Tu
Graph-based methods, which decompose the score of a dependency tree into scores of dependency arcs, are popular in dependency parsing for decades. Recently, \citet{Yang2022Span} pr…
Headed-Span-Based Projective Dependency Parsing
Songlin Yang, Kewei Tu
We propose a new method for projective dependency parsing based on headed spans. In a projective dependency tree, the largest subtree rooted at each word covers a contiguous sequen…
Enhanced Universal Dependency Parsing with Automated Concatenation of Embeddings
Xinyu Wang, Zixia Jia, Yong Jiang +1
This paper describes the system used in submission from SHANGHAITECH team to the IWPT 2021 Shared Task. Our system is a graph-based parser with the technique of Automated Concatena…
Neural Bi-Lexicalized PCFG Induction
Songlin Yang, Yanpeng Zhao, Kewei Tu
Neural lexicalized PCFGs (L-PCFGs) have been shown effective in grammar induction. However, to reduce computational complexity, they make a strong independence assumption on the ge…
Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning
Xinyu Wang, Yong Jiang, Nguyen Bach +4
Recent advances in Named Entity Recognition (NER) show that document-level contexts can significantly improve model performance. In many application scenarios, however, such contex…
PCFGs Can Do Better: Inducing Probabilistic Context-Free Grammars with Many Symbols
Songlin Yang, Yanpeng Zhao, Kewei Tu
Probabilistic context-free grammars (PCFGs) with neural parameterization have been shown to be effective in unsupervised phrase-structure grammar induction. However, due to the cub…
Constrained Text Generation with Global Guidance -- Case Study on CommonGen
Yixian Liu, Liwen Zhang, Wenjuan Han +2
This paper studies constrained text generation, which is to generate sentences under certain pre-conditions. We focus on CommonGen, the task of generating text based on a set of co…