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Found 33 papers, 15 papers with code
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
Iterative Span Selection: Self-Emergence of Resolving Orders in Semantic Role Labeling
Semantic Role Labeling (SRL) is the task of labeling semantic arguments for marked semantic predicates.
Graph-Structured Trajectory Extraction from Travelogues
Previous studies on sequence-based extraction of human movement trajectories have an issue of inadequate trajectory representation.
Can Language Models Induce Grammatical Knowledge from Indirect Evidence?
What kinds of and how much data is necessary for language models to induce grammatical knowledge to judge sentence acceptability?
Text2Traj2Text: Learning-by-Synthesis Framework for Contextual Captioning of Human Movement Trajectories
This paper presents Text2Traj2Text, a novel learning-by-synthesis framework for captioning possible contexts behind shopper's trajectory data in retail stores.
AdTEC: A Unified Benchmark for Evaluating Text Quality in Search Engine Advertising
With the increase in the more fluent ad texts automatically created by natural language generation technology, it is in the high demand to verify the quality of these creatives in a real-world setting.
Towards Temporal Change Explanations from Bi-Temporal Satellite Images
Explaining temporal changes between satellite images taken at different times is important for urban planning and environmental monitoring.
Japanese Lexical Complexity for Non-Native Readers: A New Dataset
Lexical complexity prediction (LCP) is the task of predicting the complexity of words in a text on a continuous scale.
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
Second Language Acquisition of Neural Language Models
With the success of neural language models (LMs), their language acquisition has gained much attention.
Arukikata Travelogue Dataset with Geographic Entity Mention, Coreference, and Link Annotation
Geoparsing is a fundamental technique for analyzing geo-entity information in text.
Arukikata Travelogue Dataset
We have constructed Arukikata Travelogue Dataset and released it free of charge for academic research.
N-best Response-based Analysis of Contradiction-awareness in Neural Response Generation Models
In this scenario, the quality of the n-best list considerably affects the occurrence of contradictions because the final response is chosen from this n-best list.
Instance-Based Neural Dependency Parsing
Interpretable rationales for model predictions are crucial in practical applications.
Pseudo Zero Pronoun Resolution Improves Zero Anaphora Resolution
Masked language models (MLMs) have contributed to drastic performance improvements with regard to zero anaphora resolution (ZAR).
You May Like This Hotel Because ...: Identifying Evidence for Explainable Recommendations
To tackle the challenge, this paper proposes a novel and practical task to explain evidences in recommending hotels given vague requests expressed freely in natural language.
An Empirical Study of Contextual Data Augmentation for Japanese Zero Anaphora Resolution
This study addresses two underexplored issues on CDA, that is, how to reduce the computational cost of data augmentation and how to ensure the quality of the generated data.
Corruption Is Not All Bad: Incorporating Discourse Structure into Pre-training via Corruption for Essay Scoring
Existing approaches for automated essay scoring and document representation learning typically rely on discourse parsers to incorporate discourse structure into text representation.
Embeddings of Label Components for Sequence Labeling: A Case Study of Fine-grained Named Entity Recognition
In general, the labels used in sequence labeling consist of different types of elements.
Evaluating Dialogue Generation Systems via Response Selection
Existing automatic evaluation metrics for open-domain dialogue response generation systems correlate poorly with human evaluation.
Instance-Based Learning of Span Representations: A Case Study through Named Entity Recognition
Interpretable rationales for model predictions play a critical role in practical applications.
Transductive Learning of Neural Language Models for Syntactic and Semantic Analysis
In transductive learning, an unlabeled test set is used for model training.
Inject Rubrics into Short Answer Grading System
Most existing SAG systems predict scores based only on the answers, including the model used as base line in this paper, which gives the-state-of-the-art performance.
Analytic Score Prediction and Justification Identification in Automated Short Answer Scoring
This paper provides an analytical assessment of student short answer responses with a view to potential benefits in pedagogical contexts.
An Empirical Study of Span Representations in Argumentation Structure Parsing
For several natural language processing (NLP) tasks, span representation design is attracting considerable attention as a promising new technique; a common basis for an effective design has been established.
Unsupervised Learning of Discourse-Aware Text Representation for Essay Scoring
Existing document embedding approaches mainly focus on capturing sequences of words in documents.
The Sally Smedley Hyperpartisan News Detector at SemEval-2019 Task 4
Our system achieved 80. 9{\%} accuracy on the test set for the formal run and got the 3rd place out of 42 teams.
Suspicious News Detection Using Micro Blog Text
We present a new task, suspicious news detection using micro blog text.
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
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.
