Instruct: Given a paper title, retrieve paper titles that are cited by the given paper.
Query: An Attention-Based Deep Net for Learning to Rank
Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks
End-to-End Neural Ad-hoc Ranking with Kernel Pooling
Learning to Rank Academic Experts in the DBLP Dataset
Continuation Methods and Curriculum Learning for Learning to Rank
On interactive learning-to-rank for IR: Overview, recent advances, challenges, and directions
Learning to Rank based on Analogical Reasoning
Position Bias Estimation for Unbiased Learning to Rank in Personal Search
Inferring Searcher Attention by Jointly Modeling User Interactions and Content Salience
Feature Selection and Model Comparison on Microsoft Learning-to-Rank Data Sets
Federated Online Learning to Rank with Evolution Strategies
Dynamic Attention Deep Model for Article Recommendation by Learning Human Editors' Demonstration
FSMRank: Feature Selection Algorithm for Learning to Rank
Learning to rank for robust question answering
Knowledge-aware Attentive Neural Network for Ranking Question Answer Pairs
Quality versus efficiency in document scoring with learning-to-rank models
A regression framework for learning ranking functions using relative relevance judgments
Neural Attentional Rating Regression with Review-level Explanations
MergeRUCB: A Method for Large-Scale Online Ranker Evaluation
MacroBase: Prioritizing Attention in Fast Data
A Batch Learning Framework for Scalable Personalized Ranking
Fe and Cu stable isotopes in archeological human bones and their relationship to sex.
A background subtraction algorithm for detecting and tracking vehicles
Object retrieval with large vocabularies and fast spatial matching
Supplier-supplier relationships and their implications for buyer-supplier relationships
Static and Dynamic Analysis for Contactor with a New Type of Permanent Magnet Actuator