41 |
Evaluating multilingual text encoders for unsupervised cross-lingual retrieval
|
|
|
|
BASE
|
|
Show details
|
|
42 |
Multi-SimLex: A Large-Scale Evaluation of Multilingual and Cross-Lingual Lexical Semantic Similarity
|
|
|
|
In: ISSN: 0891-2017 ; EISSN: 1530-9312 ; Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-02975786 ; Computational Linguistics, Massachusetts Institute of Technology Press (MIT Press), 2020, 46 (4), pp.847-897 ; https://direct.mit.edu/coli/article/46/4/847/97326/Multi-SimLex-A-Large-Scale-Evaluation-of (2020)
|
|
BASE
|
|
Show details
|
|
43 |
Span-ConveRT: Few-shot Span Extraction for Dialog with Pretrained Conversational Representations ...
|
|
|
|
BASE
|
|
Show details
|
|
44 |
Efficient Intent Detection with Dual Sentence Encoders ...
|
|
|
|
Abstract:
Building conversational systems in new domains and with added functionality requires resource-efficient models that work under low-data regimes (i.e., in few-shot setups). Motivated by these requirements, we introduce intent detection methods backed by pretrained dual sentence encoders such as USE and ConveRT. We demonstrate the usefulness and wide applicability of the proposed intent detectors, showing that: 1) they outperform intent detectors based on fine-tuning the full BERT-Large model or using BERT as a fixed black-box encoder on three diverse intent detection data sets; 2) the gains are especially pronounced in few-shot setups (i.e., with only 10 or 30 annotated examples per intent); 3) our intent detectors can be trained in a matter of minutes on a single CPU; and 4) they are stable across different hyperparameter settings. In hope of facilitating and democratizing research focused on intention detection, we release our code, as well as a new challenging single-domain intent detection dataset ...
|
|
URL: https://dx.doi.org/10.17863/cam.53926 https://www.repository.cam.ac.uk/handle/1810/306835
|
|
BASE
|
|
Hide details
|
|
45 |
Multidirectional Associative Optimization of Function-Specific Word Representations ...
|
|
|
|
BASE
|
|
Show details
|
|
46 |
XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning ...
|
|
|
|
BASE
|
|
Show details
|
|
47 |
Emergent Communication Pretraining for Few-Shot Machine Translation ...
|
|
|
|
BASE
|
|
Show details
|
|
48 |
Orthogonal Language and Task Adapters in Zero-Shot Cross-Lingual Transfer ...
|
|
|
|
BASE
|
|
Show details
|
|
49 |
MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfer ...
|
|
|
|
BASE
|
|
Show details
|
|
50 |
How Good is Your Tokenizer? On the Monolingual Performance of Multilingual Language Models ...
|
|
|
|
BASE
|
|
Show details
|
|
51 |
UNKs Everywhere: Adapting Multilingual Language Models to New Scripts ...
|
|
|
|
BASE
|
|
Show details
|
|
53 |
MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfer ...
|
|
|
|
BASE
|
|
Show details
|
|
54 |
Manual Clustering and Spatial Arrangement of Verbs for Multilingual Evaluation and Typology Analysis ...
|
|
|
|
BASE
|
|
Show details
|
|
55 |
XHate-999: Analyzing and Detecting Abusive Language Across Domains and Languages ...
|
|
|
|
BASE
|
|
Show details
|
|
56 |
Emergent Communication Pretraining for Few-Shot Machine Translation ...
|
|
|
|
BASE
|
|
Show details
|
|
57 |
From Zero to Hero: On the Limitations of Zero-Shot Cross-Lingual Transfer with Multilingual Transformers ...
|
|
|
|
BASE
|
|
Show details
|
|
58 |
XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning ...
|
|
|
|
BASE
|
|
Show details
|
|
59 |
Emergent Communication Pretraining for Few-Shot Machine Translation ...
|
|
|
|
BASE
|
|
Show details
|
|
60 |
Manual Clustering and Spatial Arrangement of Verbs for Multilingual Evaluation and Typology Analysis ...
|
|
|
|
BASE
|
|
Show details
|
|
|
|