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Found 13 papers, 4 papers with code
XGLUE: A New Benchmark Datasetfor Cross-lingual Pre-training, Understanding and Generation
In this paper, we introduce XGLUE, a new benchmark dataset to train large-scale cross-lingual pre-trained models using multilingual and bilingual corpora, and evaluate their performance across a diverse set of cross-lingual tasks.
Cross-Lingual Ability of Multilingual Masked Language Models: A Study of Language Structure
Our main conclusion is that the contribution of constituent order and word co-occurrence is limited, while the composition is more crucial to the success of cross-linguistic transfer.
Multi-View Document Representation Learning for Open-Domain Dense Retrieval
Second, to prevent multi-view embeddings from collapsing to the same one, we further propose a global-local loss with annealed temperature to encourage the multiple viewers to better align with different potential queries.
XLM-K: Improving Cross-Lingual Language Model Pre-training with Multilingual Knowledge
The results on MLQA and NER exhibit the superiority of XLM-K in knowledge related tasks.
Discovering Representation Sprachbund For Multilingual Pre-Training
Then we cluster all the target languages into multiple groups and name each group as a representation sprachbund.
Simpson's Bias in NLP Training
In most machine learning tasks, we evaluate a model $M$ on a given data population $S$ by measuring a population-level metric $F(S;M)$.
Tag and Correct: Question aware Open Information Extraction with Two-stage Decoding
The semi-structured answer has two advantages which are more readable and falsifiable compared to span answer.
GLOW : Global Weighted Self-Attention Network for Web Search
Deep matching models aim to facilitate search engines retrieving more relevant documents by mapping queries and documents into semantic vectors in the first-stage retrieval.
Document Modeling with Graph Attention Networks for Multi-grained Machine Reading Comprehension
Natural Questions is a new challenging machine reading comprehension benchmark with two-grained answers, which are a long answer (typically a paragraph) and a short answer (one or more entities inside the long answer).
Enhancing Answer Boundary Detection for Multilingual Machine Reading Comprehension
Multilingual pre-trained models could leverage the training data from a rich source language (such as English) to improve performance on low resource languages.
XGLUE: A New Benchmark Dataset for Cross-lingual Pre-training, Understanding and Generation
In this paper, we introduce XGLUE, a new benchmark dataset that can be used to train large-scale cross-lingual pre-trained models using multilingual and bilingual corpora and evaluate their performance across a diverse set of cross-lingual tasks.
Unicoder: A Universal Language Encoder by Pre-training with Multiple Cross-lingual Tasks
On XNLI, 1. 8% averaged accuracy improvement (on 15 languages) is obtained.
Cross-Lingual Natural Language Inference
Cross-Lingual Question Answering
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Dense Procedure Captioning in Narrated Instructional Videos
Understanding narrated instructional videos is important for both research and real-world web applications.
