Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper
Query: Evaluating Neural Word Representations in Tensor-Based Compositional Settings
Distributed Representations of Words and Phrases and their Compositionality
Disentangled Representations in Neural Models
Vector-based Models of Semantic Composition
Extending and Improving Wordnet via Unsupervised Word Embeddings
Dynamic Entity Representations in Neural Language Models
Advances in Pre-Training Distributed Word Representations
Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank
Distributed Word Representations Improve NER for e-Commerce
Best of Both Worlds: Making Word Sense Embeddings Interpretable.
Visualizing and Understanding Neural Models in NLP
Evaluating Layers of Representation in Neural Machine Translation on Part-of-Speech and Semantic Tagging Tasks
Improve Lexicon-based Word Embeddings By Word Sense Disambiguation
Learning New Facts From Knowledge Bases With Neural Tensor Networks and Semantic Word Vectors
Comparison of NER Performance Using Word Embedding
RC-NET: A General Framework for Incorporating Knowledge into Word Representations
Uncovering divergent linguistic information in word embeddings with lessons for intrinsic and extrinsic evaluation
Contextualized Word Representations for Reading Comprehension
Uncertainty in Neural Network Word Embedding: Exploration of Threshold for Similarity
Vector Space Semantic Parsing: A Framework for Compositional Vector Space Models
Factors Influencing the Surprising Instability of Word Embeddings
linguistically motivated large - scale nlp with c & c and boxer .
Efficient self-shadowed radiosity normal mapping
Marasmioid and gymnopoid fungi of the Republic of Korea. 2. Marasmius sect. Globulares
Risk Mining: Company-Risk Identification from Unstructured Sources
Autonomous lift of a cable-suspended load by an unmanned aerial robot