DE eng

Search in the Catalogues and Directories

Hits 1 – 19 of 19

1
Parameter-Efficient Neural Reranking for Cross-Lingual and Multilingual Retrieval ...
BASE
Show details
2
Geographic Adaptation of Pretrained Language Models ...
BASE
Show details
3
Crossing the Conversational Chasm: A Primer on Natural Language Processing for Multilingual Task-Oriented Dialogue Systems ...
BASE
Show details
4
On Cross-Lingual Retrieval with Multilingual Text Encoders ...
BASE
Show details
5
Evaluating Multilingual Text Encoders for Unsupervised Cross-Lingual Retrieval ...
BASE
Show details
6
AraWEAT: Multidimensional Analysis of Biases in Arabic Word Embeddings ...
BASE
Show details
7
XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning ...
BASE
Show details
8
On the Limitations of Cross-lingual Encoders as Exposed by Reference-Free Machine Translation Evaluation ...
BASE
Show details
9
Orthogonal Language and Task Adapters in Zero-Shot Cross-Lingual Transfer ...
BASE
Show details
10
From Zero to Hero: On the Limitations of Zero-Shot Cross-Lingual Transfer with Multilingual Transformers ...
BASE
Show details
11
Verb Knowledge Injection for Multilingual Event Processing ...
BASE
Show details
12
Probing Pretrained Language Models for Lexical Semantics ...
BASE
Show details
13
Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ...
BASE
Show details
14
Do We Really Need Fully Unsupervised Cross-Lingual Embeddings? ...
BASE
Show details
15
How to (Properly) Evaluate Cross-Lingual Word Embeddings: On Strong Baselines, Comparative Analyses, and Some Misconceptions ...
Abstract: Cross-lingual word embeddings (CLEs) enable multilingual modeling of meaning and facilitate cross-lingual transfer of NLP models. Despite their ubiquitous usage in downstream tasks, recent increasingly popular projection-based CLE models are almost exclusively evaluated on a single task only: bilingual lexicon induction (BLI). Even BLI evaluations vary greatly, hindering our ability to correctly interpret performance and properties of different CLE models. In this work, we make the first step towards a comprehensive evaluation of cross-lingual word embeddings. We thoroughly evaluate both supervised and unsupervised CLE models on a large number of language pairs in the BLI task and three downstream tasks, providing new insights concerning the ability of cutting-edge CLE models to support cross-lingual NLP. We empirically demonstrate that the performance of CLE models largely depends on the task at hand and that optimizing CLE models for BLI can result in deteriorated downstream performance. We indicate the ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/1902.00508
https://dx.doi.org/10.48550/arxiv.1902.00508
BASE
Hide details
16
Unsupervised Cross-Lingual Information Retrieval using Monolingual Data Only ...
BASE
Show details
17
Adversarial Propagation and Zero-Shot Cross-Lingual Transfer of Word Vector Specialization ...
BASE
Show details
18
Post-Specialisation: Retrofitting Vectors of Words Unseen in Lexical Resources ...
BASE
Show details
19
A Resource-Light Method for Cross-Lingual Semantic Textual Similarity ...
BASE
Show details

Catalogues
0
0
0
0
0
0
0
Bibliographies
0
0
0
0
0
0
0
0
0
Linked Open Data catalogues
0
Online resources
0
0
0
0
Open access documents
19
0
0
0
0
© 2013 - 2024 Lin|gu|is|tik | Imprint | Privacy Policy | Datenschutzeinstellungen ändern