research
∙
09/12/2023
Do PLMs Know and Understand Ontological Knowledge?
Ontological knowledge, which comprises classes and properties and their ...
share
research
∙
08/21/2023
SeqGPT: An Out-of-the-box Large Language Model for Open Domain Sequence Understanding
Large language models (LLMs) have shown impressive ability for open-doma...
research
∙
06/05/2023
Improving Grammar-based Sequence-to-Sequence Modeling with Decomposition and Constraints
Neural QCFG is a grammar-based sequence-tosequence (seq2seq) model with ...
research
∙
05/05/2023
DAMO-NLP at SemEval-2023 Task 2: A Unified Retrieval-augmented System for Multilingual Named Entity Recognition
The MultiCoNER 2 shared task aims to tackle multilingual named entity re...
research
∙
03/06/2023
A Multi-Grained Self-Interpretable Symbolic-Neural Model For Single/Multi-Labeled Text Classification
Deep neural networks based on layer-stacking architectures have historic...
research
∙
02/08/2023
COMBO: A Complete Benchmark for Open KG Canonicalization
Open knowledge graph (KG) consists of (subject, relation, object) triple...
research
∙
12/18/2022
Recall, Expand and Multi-Candidate Cross-Encode: Fast and Accurate Ultra-Fine Entity Typing
Ultra-fine entity typing (UFET) predicts extremely free-formed types (e....
research
∙
12/17/2022
Joint Information Extraction with Cross-Task and Cross-Instance High-Order Modeling
Prior works on Information Extraction (IE) typically predict different t...
research
∙
12/03/2022
Named Entity and Relation Extraction with Multi-Modal Retrieval
Multi-modal named entity recognition (NER) and relation extraction (RE) ...
research
∙
12/03/2022
Modeling Label Correlations for Ultra-Fine Entity Typing with Neural Pairwise Conditional Random Field
Ultra-fine entity typing (UFET) aims to predict a wide range of type phr...
research
∙
05/01/2022
Dynamic Programming in Rank Space: Scaling Structured Inference with Low-Rank HMMs and PCFGs
Hidden Markov Models (HMMs) and Probabilistic Context-Free Grammars (PCF...
research
∙
04/07/2022
Modeling Label Correlations for Second-Order Semantic Dependency Parsing with Mean-Field Inference
Second-order semantic parsing with end-to-end mean-field inference has b...
research
∙
03/09/2022
Nested Named Entity Recognition as Latent Lexicalized Constituency Parsing
Nested named entity recognition (NER) has been receiving increasing atte...
research
∙
03/01/2022
DAMO-NLP at SemEval-2022 Task 11: A Knowledge-based System for Multilingual Named Entity Recognition
The MultiCoNER shared task aims at detecting semantically ambiguous and ...
research
∙
12/13/2021
ITA: Image-Text Alignments for Multi-Modal Named Entity Recognition
Recently, Multi-modal Named Entity Recognition (MNER) has attracted a lo...
research
∙
10/11/2021
Bottom-Up Constituency Parsing and Nested Named Entity Recognition with Pointer Networks
Constituency parsing and nested named entity recognition (NER) are typic...
research
∙
08/12/2021
Combining (second-order) graph-based and headed span-based projective dependency parsing
Graph-based methods are popular in dependency parsing for decades. Recen...
research
∙
08/10/2021
Headed Span-Based Projective Dependency Parsing
We propose a headed span-based method for projective dependency parsing....
research
∙
07/06/2021
Enhanced Universal Dependency Parsing with Automated Concatenation of Embeddings
This paper describes the system used in submission from SHANGHAITECH tea...
research
∙
05/31/2021
Neural Bi-Lexicalized PCFG Induction
Neural lexicalized PCFGs (L-PCFGs) have been shown effective in grammar ...
research
∙
05/08/2021
Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning
Recent advances in Named Entity Recognition (NER) show that document-lev...
research
∙
04/28/2021
PCFGs Can Do Better: Inducing Probabilistic Context-Free Grammars with Many Symbols
Probabilistic context-free grammars (PCFGs) with neural parameterization...
research
∙
03/12/2021
Constrained Text Generation with Global Guidance – Case Study on CommonGen
This paper studies constrained text generation, which is to generate sen...
research
∙
11/11/2020
An Investigation of Potential Function Designs for Neural CRF
The neural linear-chain CRF model is one of the most widely-used approac...
research
∙
11/10/2020
Neural Latent Dependency Model for Sequence Labeling
Sequence labeling is a fundamental problem in machine learning, natural ...
research
∙
10/28/2020
Second-Order Unsupervised Neural Dependency Parsing
Most of the unsupervised dependency parsers are based on first-order pro...
research
∙
10/10/2020
Structural Knowledge Distillation
Knowledge distillation is a critical technique to transfer knowledge bet...
research
∙
10/10/2020
Automated Concatenation of Embeddings for Structured Prediction
Pretrained contextualized embeddings are powerful word representations f...
research
∙
10/10/2020
Second-Order Neural Dependency Parsing with Message Passing and End-to-End Training
In this paper, we propose second-order graph-based neural dependency par...
research
∙
10/04/2020
Adversarial Attack and Defense of Structured Prediction Models
Building an effective adversarial attacker and elaborating on countermea...
research
∙
10/04/2020
A Survey of Unsupervised Dependency Parsing
Syntactic dependency parsing is an important task in natural language pr...
research
∙
09/17/2020
More Embeddings, Better Sequence Labelers?
Recent work proposes a family of contextual embeddings that significantl...
research
∙
09/17/2020
Fast and Accurate Sequence Labeling with Approximate Inference Network
The linear-chain Conditional Random Field (CRF) model is one of the most...
research
∙
06/02/2020
Enhanced Universal Dependency Parsing with Second-Order Inference and Mixture of Training Data
This paper presents the system used in our submission to the IWPT 2020 S...
research
∙
04/08/2020
ShanghaiTech at MRP 2019: Sequence-to-Graph Transduction with Second-Order Edge Inference for Cross-Framework Meaning Representation Parsing
This paper presents the system used in our submission to the CoNLL 2019 ...
research
∙
04/08/2020
Structure-Level Knowledge Distillation For Multilingual Sequence Labeling
Multilingual sequence labeling is a task of predicting label sequences u...
research
∙
12/28/2019
Learning Numeral Embeddings
Word embedding is an essential building block for deep learning methods ...
research
∙
06/29/2019
Latent Variable Sentiment Grammar
Neural models have been investigated for sentiment classification over c...
research
∙
06/19/2019
Second-Order Semantic Dependency Parsing with End-to-End Neural Networks
Semantic dependency parsing aims to identify semantic relationships betw...
research
∙
08/13/2018
Language Style Transfer from Sentences with Arbitrary Unknown Styles
Language style transfer is the problem of migrating the content of a sou...
research
∙
05/12/2018
Gaussian Mixture Latent Vector Grammars
We introduce Latent Vector Grammars (LVeGs), a new framework that extend...
research
∙
04/10/2018
QA4IE: A Question Answering based Framework for Information Extraction
Information Extraction (IE) refers to automatically extracting structure...
research
∙
08/16/2017
Maximum A Posteriori Inference in Sum-Product Networks
Sum-product networks (SPNs) are a class of probabilistic graphical model...
research
∙
08/07/2017
Structured Attentions for Visual Question Answering
Visual attention, which assigns weights to image regions according to th...
research
∙
08/03/2017
CRF Autoencoder for Unsupervised Dependency Parsing
Unsupervised dependency parsing, which tries to discover linguistic depe...
research
∙
08/02/2017
Dependency Grammar Induction with Neural Lexicalization and Big Training Data
We study the impact of big models (in terms of the degree of lexicalizat...
research
∙
08/02/2017
Combining Generative and Discriminative Approaches to Unsupervised Dependency Parsing via Dual Decomposition
Unsupervised dependency parsing aims to learn a dependency parser from u...
research
∙
09/08/2016
Latent Dependency Forest Models
Probabilistic modeling is one of the foundations of modern machine learn...
research
∙
06/02/2015
Stochastic And-Or Grammars: A Unified Framework and Logic Perspective
Stochastic And-Or grammars (AOG) extend traditional stochastic grammars ...
research
∙
10/02/2014
