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Found 119 papers, 22 papers with code
Coordination Generation via Synchronized Text-Infilling
Generating synthetic data for supervised learning from large-scale pre-trained language models has enhanced performances across several NLP tasks, especially in low-resource scenarios.
Improving Neural Machine Translation on resource-limited pairs using auxiliary data of a third language
This article combines three different ideas (splitting words into smaller units, using an extra dataset of a related language pair and using monolingual data) for improving the performance of NMT models on language pairs with limited data.
Improving Discriminative Learning for Zero-Shot Relation Extraction
Zero-shot relation extraction (ZSRE) aims to predict target relations that cannot be observed during training.
Ranked #3 on
Zero-shot Relation Classification
on FewRel
Recent Trends in Personalized Dialogue Generation: A Review of Datasets, Methodologies, and Evaluations
Enhancing user engagement through personalization in conversational agents has gained significance, especially with the advent of large language models that generate fluent responses.
A Dataset for Pharmacovigilance in German, French, and Japanese: Annotating Adverse Drug Reactions across Languages
User-generated data sources have gained significance in uncovering Adverse Drug Reactions (ADRs), with an increasing number of discussions occurring in the digital world.
Enhancing Semantic Correlation between Instances and Relations for Zero-Shot Relation Extraction
This study argues that enhancing the semantic correlation between instances and relations is key to effectively solving the zero-shot relation extraction task.
Ranked #1 on
Zero-shot Relation Classification
on FewRel
Unsupervised Paraphrasing of Multiword Expressions
We propose an unsupervised approach to paraphrasing multiword expressions (MWEs) in context.
Is In-hospital Meta-information Useful for Abstractive Discharge Summary Generation?
During the patient's hospitalization, the physician must record daily observations of the patient and summarize them into a brief document called "discharge summary" when the patient is discharged.
Switching to Discriminative Image Captioning by Relieving a Bottleneck of Reinforcement Learning
Discriminativeness is a desirable feature of image captions: captions should describe the characteristic details of input images.
Exploring Optimal Granularity for Extractive Summarization of Unstructured Health Records: Analysis of the Largest Multi-Institutional Archive of Health Records in Japan
We first defined three types of summarization units with different granularities to compare the performance of the discharge summary generation: whole sentences, clinical segments, and clauses.
Unsupervised Lexical Substitution with Decontextualised Embeddings
We propose a new unsupervised method for lexical substitution using pre-trained language models.
Improved Decomposition Strategy for Joint Entity and Relation Extraction
A recent study (Yu et al. 2020) proposed a novel decomposition strategy that splits the task into two interrelated subtasks: detection of the head-entity (HE) and identification of the corresponding tail-entity and relation (TER) for each extracted head-entity.
Dependency Patterns of Complex Sentences and Semantic Disambiguation for Abstract Meaning Representation Parsing
Abstract Meaning Representation (AMR) is a sentence-level meaning representation based on predicate argument structure.
Nested Named Entity Recognition via Explicitly Excluding the Influence of the Best Path
This paper presents a novel method for nested named entity recognition.
Ranked #13 on
Nested Named Entity Recognition
on ACE 2005
Removing Word-Level Spurious Alignment between Images and Pseudo-Captions in Unsupervised Image Captioning
Unsupervised image captioning is a challenging task that aims at generating captions without the supervision of image-sentence pairs, but only with images and sentences drawn from different sources and object labels detected from the images.
CovRelex: A COVID-19 Retrieval System with Relation Extraction
This paper presents CovRelex, a scientific paper retrieval system targeting entities and relations via relation extraction on COVID-19 scientific papers.
Coordination Boundary Identification without Labeled Data for Compound Terms Disambiguation
We propose a simple method for nominal coordination boundary identification.
Learning Contextualised Cross-lingual Word Embeddings and Alignments for Extremely Low-Resource Languages Using Parallel Corpora
We propose a new approach for learning contextualised cross-lingual word embeddings based on a small parallel corpus (e. g. a few hundred sentence pairs).
Bilingual Lexicon Induction
Cross-Lingual Word Embeddings
+5
LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention
In this paper, we propose new pretrained contextualized representations of words and entities based on the bidirectional transformer.
Ranked #1 on
Entity Typing
on Open Entity
Length-controllable Abstractive Summarization by Guiding with Summary Prototype
Unlike the previous models, our length-controllable abstractive summarization model incorporates a word-level extractive module in the encoder-decoder model instead of length embeddings.
Global Entity Disambiguation with BERT
We propose a global entity disambiguation (ED) model based on BERT.
Ranked #1 on
Entity Disambiguation
on MSNBC
Gated Graph Recursive Neural Networks for Molecular Property Prediction
Molecule property prediction is a fundamental problem for computer-aided drug discovery and materials science.
Improving Multi-Word Entity Recognition for Biomedical Texts
The proposed SR model, FROBES, improves the representation of multi-word entities.
Stochastic Tokenization with a Language Model for Neural Text Classification
To make the model robust against infrequent tokens, we sampled segmentation for each sentence stochastically during training, which resulted in improved performance of text classification.
Unsupervised Multilingual Word Embedding with Limited Resources using Neural Language Models
Recently, a variety of unsupervised methods have been proposed that map pre-trained word embeddings of different languages into the same space without any parallel data.
Relation Classification Using Segment-Level Attention-based CNN and Dependency-based RNN
Recently, relation classification has gained much success by exploiting deep neural networks.
Decomposed Local Models for Coordinate Structure Parsing
We propose a simple and accurate model for coordination boundary identification.
Wikipedia2Vec: An Efficient Toolkit for Learning and Visualizing the Embeddings of Words and Entities from Wikipedia
The embeddings of entities in a large knowledge base (e. g., Wikipedia) are highly beneficial for solving various natural language tasks that involve real world knowledge.
Playing by the Book: An Interactive Game Approach for Action Graph Extraction from Text
Understanding procedural text requires tracking entities, actions and effects as the narrative unfolds.
Coordinate Structures in Universal Dependencies for Head-final Languages
This paper discusses the representation of coordinate structures in the Universal Dependencies framework for two head-final languages, Japanese and Korean.
Reduction of Parameter Redundancy in Biaffine Classifiers with Symmetric and Circulant Weight Matrices
Currently, the biaffine classifier has been attracting attention as a method to introduce an attention mechanism into the modeling of binary relations.
A Span Selection Model for Semantic Role Labeling
We present a simple and accurate span-based model for semantic role labeling (SRL).
Ranked #7 on
Semantic Role Labeling
on CoNLL 2005
Dynamic Feature Selection with Attention in Incremental Parsing
One main challenge for incremental transition-based parsers, when future inputs are invisible, is to extract good features from a limited local context.
Cooperating Tools for MWE Lexicon Management and Corpus Annotation
Those two tools cooperate so that the words and multi-word expressions stored in Cradle are directly referred to by ChaKi in conducting corpus annotation, and the words and expressions annotated in ChaKi can be output as a list of lexical entities that are to be stored in Cradle.
Sentence Suggestion of Japanese Functional Expressions for Chinese-speaking Learners
We present a computer-assisted learning system, Jastudy, which is particularly designed for Chinese-speaking learners of Japanese as a second language (JSL) to learn Japanese functional expressions with suggestion of appropriate example sentences.
Ranking-Based Automatic Seed Selection and Noise Reduction for Weakly Supervised Relation Extraction
This paper addresses the tasks of automatic seed selection for bootstrapping relation extraction, and noise reduction for distantly supervised relation extraction.
A Fast and Easy Regression Technique for k-NN Classification Without Using Negative Pairs
This paper proposes an inexpensive way to learn an effective dissimilarity function to be used for $k$-nearest neighbor ($k$-NN) classification.
Interpretable Adversarial Perturbation in Input Embedding Space for Text
This paper restores interpretability to such methods by restricting the directions of perturbations toward the existing words in the input embedding space.
Improving Neural Text Normalization with Data Augmentation at Character- and Morphological Levels
In this study, we investigated the effectiveness of augmented data for encoder-decoder-based neural normalization models.
Segment-Level Neural Conditional Random Fields for Named Entity Recognition
We present Segment-level Neural CRF, which combines neural networks with a linear chain CRF for segment-level sequence modeling tasks such as named entity recognition (NER) and syntactic chunking.
Can Discourse Relations be Identified Incrementally?
Humans process language word by word and construct partial linguistic structures on the fly before the end of the sentence is perceived.
Coordination Boundary Identification with Similarity and Replaceability
We propose a neural network model for coordination boundary detection.
Improving Sequence to Sequence Neural Machine Translation by Utilizing Syntactic Dependency Information
In order to assess the performance, we construct model based on an attention mechanism encoder-decoder model in which the source language is input to the encoder as a sequence and the decoder generates the target language as a linearized dependency tree structure.
Effective Online Reordering with Arc-Eager Transitions
We present a new transition system with word reordering for unrestricted non-projective dependency parsing.
Adversarial Training for Cross-Domain Universal Dependency Parsing
We describe our submission to the CoNLL 2017 shared task, which exploits the shared common knowledge of a language across different domains via a domain adaptation technique.
Joint Prediction of Morphosyntactic Categories for Fine-Grained Arabic Part-of-Speech Tagging Exploiting Tag Dictionary Information
One reason for this is that in the tagging scheme for such languages, a complete POS tag is formed by combining tags from multiple tag sets defined for each morphosyntactic category.
Neural Modeling of Multi-Predicate Interactions for Japanese Predicate Argument Structure Analysis
The performance of Japanese predicate argument structure (PAS) analysis has improved in recent years thanks to the joint modeling of interactions between multiple predicates.
English Multiword Expression-aware Dependency Parsing Including Named Entities
Because syntactic structures and spans of multiword expressions (MWEs) are independently annotated in many English syntactic corpora, they are generally inconsistent with respect to one another, which is harmful to the implementation of an aggregate system.
Knowledge Transfer for Out-of-Knowledge-Base Entities: A Graph Neural Network Approach
Knowledge base completion (KBC) aims to predict missing information in a knowledge base. In this paper, we address the out-of-knowledge-base (OOKB) entity problem in KBC:how to answer queries concerning test entities not observed at training time.
A* CCG Parsing with a Supertag and Dependency Factored Model
Our model achieves the state-of-the-art results on English and Japanese CCG parsing.
Multilingual Back-and-Forth Conversion between Content and Function Head for Easy Dependency Parsing
Universal Dependencies (UD) is becoming a standard annotation scheme cross-linguistically, but it is argued that this scheme centering on content words is harder to parse than the conventional one centering on function words.
An Algebraic Formalization of Forward and Forward-backward Algorithms
back propagation) on computation graphs with addition and multiplication, and so on.
Simplification of Example Sentences for Learners of Japanese Functional Expressions
Learning functional expressions is one of the difficulties for language learners, since functional expressions tend to have multiple meanings and complicated usages in various situations.
Demonstration of ChaKi.NET -- beyond the corpus search system
ChaKi. NET is a corpus management system for dependency structure annotated corpora.
Global Pre-ordering for Improving Sublanguage Translation
When translating formal documents, capturing the sentence structure specific to the sublanguage is extremely necessary to obtain high-quality translations.
Japanese Lexical Simplification for Non-Native Speakers
This paper introduces Japanese lexical simplification.
Identification of Flexible Multiword Expressions with the Help of Dependency Structure Annotation
This paper presents our ongoing work on compilation of English multi-word expression (MWE) lexicon.
BCCWJ-DepPara: A Syntactic Annotation Treebank on the `Balanced Corpus of Contemporary Written Japanese'
Paratactic syntactic structures are difficult to represent in syntactic dependency tree structures.
Japanese Text Normalization with Encoder-Decoder Model
Text normalization is the task of transforming lexical variants to their canonical forms.
Construction of an English Dependency Corpus incorporating Compound Function Words
Nevertheless, this method often leads to the following problem: A node derived from an MWE could have multiple heads and the whole dependency structure including MWE might be cyclic.
Universal Dependencies for Japanese
We present an attempt to port the international syntactic annotation scheme, Universal Dependencies, to the Japanese language in this paper.
Dependency Parsing with LSTMs: An Empirical Evaluation
We propose a transition-based dependency parser using Recurrent Neural Networks with Long Short-Term Memory (LSTM) units.
Ridge Regression, Hubness, and Zero-Shot Learning
This paper discusses the effect of hubness in zero-shot learning, when ridge regression is used to find a mapping between the example space to the label space.
Parsing Chinese Synthetic Words with a Character-based Dependency Model
Synthetic word analysis is a potentially important but relatively unexplored problem in Chinese natural language processing.
Collocation or Free Combination? --- Applying Machine Translation Techniques to identify collocations in Japanese
This work presents an initial investigation on how to distinguish collocations from free combinations.
Efficient Stacked Dependency Parsing by Forest Reranking
This paper proposes a discriminative forest reranking algorithm for dependency parsing that can be seen as a form of efficient stacked parsing.
UniDic for Early Middle Japanese: a Dictionary for Morphological Analysis of Classical Japanese
In order to construct an annotated diachronic corpus of Japanese, we propose to create a new dictionary for morphological analysis of Early Middle Japanese (Classical Japanese) based on UniDic, a dictionary for Contemporary Japanese.
