Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper.
Query: Learning with Noise: Enhance Distantly Supervised Relation Extraction with Dynamic Transition Matrix
Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks
Reinforcement Learning for Relation Classification from Noisy Data
Learning Relational Dependency Networks for Relation Extraction
Exploring Fine-grained Entity Type Constraints for Distantly Supervised Relation Extraction
Convolution Neural Network for Relation Extraction
Web Relation Extraction with Distant Supervision
Review of Relation Extraction Methods: What Is New Out There?
Connecting Language and Knowledge Bases with Embedding Models for Relation Extraction
Multi-instance Multi-label Learning for Relation Extraction
Ensemble Neural Relation Extraction with Adaptive Boosting
Self-supervised relation extraction from the Web
Kernel methods for relation extraction
Unsupervised Relation Extraction with General Domain Knowledge
The Tradeoffs Between Open and Traditional Relation Extraction
RelNN: A Deep Neural Model for Relational Learning
Ensemble Semantics for Large-scale Unsupervised Relation Extraction
Relation Extraction using Distant Supervision, SVMs, and Probabilistic First Order Logic
Weakly-supervised relation classification for information extraction
Numerical relation extraction with minimal supervision
Joint learning of named entity recognition and relation extraction
Online gaming addiction in children and adolescents: A review of empirical research
predicting user preference for movies using netflix database .
Don't count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors
Analysis and optimization of software requirements prioritization techniques
AUDIO TRANSFORMATION TECHNOLOGIES APPLIED TO VIDEO GAMES