61 |
SEAGLE: A platform for comparative evaluation of semantic encoders for information retrieval
|
|
|
|
BASE
|
|
Show details
|
|
63 |
Specializing distributional vectors of all words for lexical entailment
|
|
|
|
BASE
|
|
Show details
|
|
64 |
How to (properly) evaluate cross-lingual word embeddings: On strong baselines, comparative analyses, and some misconceptions
|
|
|
|
BASE
|
|
Show details
|
|
65 |
Cross-lingual semantic specialization via lexical relation induction
|
|
|
|
BASE
|
|
Show details
|
|
66 |
Generalized tuning of distributional word vectors for monolingual and cross-lingual lexical entailment
|
|
|
|
BASE
|
|
Show details
|
|
67 |
SenZi: A sentiment analysis lexicon for the latinised Arabic (Arabizi)
|
|
|
|
BASE
|
|
Show details
|
|
68 |
Informing unsupervised pretraining with external linguistic knowledge
|
|
|
|
BASE
|
|
Show details
|
|
69 |
Do we really need fully unsupervised cross-lingual embeddings?
|
|
|
|
BASE
|
|
Show details
|
|
70 |
Are we consistently biased? Multidimensional analysis of biases in distributional word vectors
|
|
|
|
BASE
|
|
Show details
|
|
71 |
Unsupervised Cross-Lingual Information Retrieval using Monolingual Data Only ...
|
|
|
|
BASE
|
|
Show details
|
|
72 |
Unsupervised Cross-Lingual Information Retrieval Using Monolingual Data Only ...
|
|
|
|
BASE
|
|
Show details
|
|
73 |
Adversarial Propagation and Zero-Shot Cross-Lingual Transfer of Word Vector Specialization ...
|
|
|
|
BASE
|
|
Show details
|
|
74 |
Post-Specialisation: Retrofitting Vectors of Words Unseen in Lexical Resources ...
|
|
|
|
BASE
|
|
Show details
|
|
75 |
A Resource-Light Method for Cross-Lingual Semantic Textual Similarity ...
|
|
|
|
BASE
|
|
Show details
|
|
76 |
Post-Specialisation: Retrofitting Vectors of Words Unseen in Lexical Resources ...
|
|
|
|
BASE
|
|
Show details
|
|
77 |
Unsupervised Cross-Lingual Information Retrieval Using Monolingual Data Only
|
|
|
|
BASE
|
|
Show details
|
|
80 |
Investigating the role of argumentation in the rhetorical analysis of scientific publications with neural multi-task learning models
|
|
|
|
BASE
|
|
Show details
|
|
|
|