Search Results for author:
Found 25 papers, 8 papers with code
Multitask Learning for Cross-Lingual Transfer of Broad-coverage Semantic Dependencies
We describe a method for developing broad-coverage semantic dependency parsers for languages for which no semantically annotated resource is available.
“Wikily” Supervised Neural Translation Tailored to Cross-Lingual Tasks
Our captioning results on Arabic are slightly better than that of its supervised model.
External Language Model Integration for Factorized Neural Transducers
We propose an adaptation method for factorized neural transducers (FNT) with external language models.
Bidirectional Language Models Are Also Few-shot Learners
An arbitrary task can be reformulated as a natural language prompt, and a language model can be asked to generate the completion, indirectly performing the task in a paradigm known as prompt-based learning.
Multilingual Bidirectional Unsupervised Translation Through Multilingual Finetuning and Back-Translation
We propose a two-stage approach for training a single NMT model to translate unseen languages both to and from English.
Cultural and Geographical Influences on Image Translatability of Words across Languages
We find that images of words are not always invariant across languages, and that language pairs with shared culture, meaning having either a common language family, ethnicity or religion, have improved image translatability (i. e., have more similar images for similar words) compared to its converse, regardless of their geographic proximity.
Cultural Vocal Bursts Intensity Prediction
Multilingual NLP
+3
"Wikily" Supervised Neural Translation Tailored to Cross-Lingual Tasks
Our captioning results on Arabic are slightly better than that of its supervised model.
ParsiNLU: A Suite of Language Understanding Challenges for Persian
Despite the progress made in recent years in addressing natural language understanding (NLU) challenges, the majority of this progress remains to be concentrated on resource-rich languages like English.
Automatic Standardization of Colloquial Persian
We also show that our model improves English-to-Persian machine translation in scenarios for which the training data is from colloquial Persian with 1. 4 absolute BLEU score difference in the development data, and 0. 8 in the test data.
The Persian Dependency Treebank Made Universal
Our delexicalized Persian-to-English parser transfer experiments show that a parsing model trained on our data is ~2% absolutely more accurate than that of Seraji et al. (2016) in terms of labeled attachment score.
Mutlitask Learning for Cross-Lingual Transfer of Semantic Dependencies
We make use of supervised syntactic parsing as an auxiliary task in a multitask learning framework, and show that with different multitask learning settings, we consistently improve over the single-task baseline.
Cross-Lingual Transfer of Semantic Roles: From Raw Text to Semantic Roles
We describe a transfer method based on annotation projection to develop a dependency-based semantic role labeling system for languages for which no supervised linguistic information other than parallel data is available.
Low-Resource Syntactic Transfer with Unsupervised Source Reordering
We describe a cross-lingual transfer method for dependency parsing that takes into account the problem of word order differences between source and target languages.
Entity-Aware Language Model as an Unsupervised Reranker
One solution is to use a reranker trained with global features, in which global features are derived from n-best lists.
Transferring Semantic Roles Using Translation and Syntactic Information
Our paper addresses the problem of annotation projection for semantic role labeling for resource-poor languages using supervised annotations from a resource-rich language through parallel data.
Cross-Lingual Syntactic Transfer with Limited Resources
We describe a simple but effective method for cross-lingual syntactic transfer of dependency parsers, in the scenario where a large amount of translation data is not available.
Yara Parser: A Fast and Accurate Dependency Parser
At its fastest, Yara can parse about 4000 sentences per second when in greedy mode (1 beam).
