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Found 8 papers, 2 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.
Automatic Song Translation for Tonal Languages
This paper develops automatic song translation (AST) for tonal languages and addresses the unique challenge of aligning words' tones with melody of a song in addition to conveying the original meaning.
Which Evaluations Uncover Sense Representations that Actually Make Sense?
Text representations are critical for modern natural language processing.
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.
A Differentiable Self-disambiguated Sense Embedding Model via Scaled Gumbel Softmax
We present a differentiable multi-prototype word representation model that disentangles senses of polysemous words and produces meaningful sense-specific embeddings without external resources.
Inducing and Embedding Senses with Scaled Gumbel Softmax
Methods for learning word sense embeddings represent a single word with multiple sense-specific vectors.
On Evaluating and Comparing Open Domain Dialog Systems
In this paper, we propose a comprehensive evaluation strategy with multiple metrics designed to reduce subjectivity by selecting metrics which correlate well with human judgement.
Topic-based Evaluation for Conversational Bots
Dialog evaluation is a challenging problem, especially for non task-oriented dialogs where conversational success is not well-defined.
