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Found 21 papers, 8 papers with code
Machine Translation Aided Bilingual Data-to-Text Generation and Semantic Parsing
We present a system for bilingual Data-ToText Generation and Semantic Parsing.
Machine Translation Pre-training for Data-to-Text Generation - A Case Study in Czech
Since the structured data is generally expressed in English, text generation into other languages involves elements of translation, transliteration and copying - elements already encoded in neural machine translation systems.
XTREME-UP: A User-Centric Scarce-Data Benchmark for Under-Represented Languages
We evaluate commonly used models on the benchmark.
CLSE: Corpus of Linguistically Significant Entities
Using the CLSE's entities and a small number of human translations, we create a linguistically representative NLG evaluation benchmark in three languages: French (high-resource), Marathi (low-resource), and Russian (highly inflected language).
Mining Duplicate Questions of Stack Overflow
There has a been a significant rise in the use of Community Question Answering sites (CQAs) over the last decade owing primarily to their ability to leverage the wisdom of the crowd.
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
BIG-bench focuses on tasks that are believed to be beyond the capabilities of current language models.
XTREME-S: Evaluating Cross-lingual Speech Representations
Covering 102 languages from 10+ language families, 3 different domains and 4 task families, XTREME-S aims to simplify multilingual speech representation evaluation, as well as catalyze research in "universal" speech representation learning.
Improving Compositional Generalization with Self-Training for Data-to-Text Generation
Data-to-text generation focuses on generating fluent natural language responses from structured meaning representations (MRs).
nmT5 - Is parallel data still relevant for pre-training massively multilingual language models?
Recently, mT5 - a massively multilingual version of T5 - leveraged a unified text-to-text format to attain state-of-the-art results on a wide variety of multilingual NLP tasks.
Using Machine Translation to Localize Task Oriented NLG Output
One of the challenges in a task oriented natural language application like the Google Assistant, Siri, or Alexa is to localize the output to many languages.
Automatic Construction of Evaluation Suites for Natural Language Generation Datasets
By applying this framework to the GEM generation benchmark, we propose an evaluation suite made of 80 challenge sets, demonstrate the kinds of analyses that it enables and shed light onto the limits of current generation models.
nmT5 -- Is parallel data still relevant for pre-training massively multilingual language models?
Recently, mT5 - a massively multilingual version of T5 - leveraged a unified text-to-text format to attain state-of-the-art results on a wide variety of multilingual NLP tasks.
ByT5: Towards a token-free future with pre-trained byte-to-byte models
Most widely-used pre-trained language models operate on sequences of tokens corresponding to word or subword units.
Ranked #1 on
Cross-Lingual Natural Language Inference
on XNLI
Cross-Lingual Natural Language Inference
Cross-Lingual NER
+3
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics
We introduce GEM, a living benchmark for natural language Generation (NLG), its Evaluation, and Metrics.
Ranked #1 on
Extreme Summarization
on GEM-XSum
Abstractive Text Summarization
Cross-Lingual Abstractive Summarization
+5
mT5: A massively multilingual pre-trained text-to-text transformer
The recent "Text-to-Text Transfer Transformer" (T5) leveraged a unified text-to-text format and scale to attain state-of-the-art results on a wide variety of English-language NLP tasks.
Ranked #2 on
Reading Comprehension
on MuSeRC
Text-to-Text Pre-Training for Data-to-Text Tasks
We study the pre-train + fine-tune strategy for data-to-text tasks.
Ranked #1 on
Data-to-Text Generation
on ToTTo
Template Guided Text Generation for Task-Oriented Dialogue
Virtual assistants such as Google Assistant, Amazon Alexa, and Apple Siri enable users to interact with a large number of services and APIs on the web using natural language.
Ranked #2 on
Data-to-Text Generation
on MULTIWOZ 2.1
Machine Translation Pre-training for Data-to-Text Generation -- A Case Study in Czech
Since the structured data is generally expressed in English, text generation into other languages involves elements of translation, transliteration and copying - elements already encoded in neural machine translation systems.
Ranked #1 on
Data-to-Text Generation
on Czech Restaurant NLG
Incorporating Bilingual Dictionaries for Low Resource Semi-Supervised Neural Machine Translation
We explore ways of incorporating bilingual dictionaries to enable semi-supervised neural machine translation.
Supervised Contextual Embeddings for Transfer Learning in Natural Language Processing Tasks
Pre-trained word embeddings are the primary method for transfer learning in several Natural Language Processing (NLP) tasks.
Tartan: A retrieval-based socialbot powered by a dynamic finite-state machine architecture
Tartan is a non-goal-oriented socialbot focused around providing users with an engaging and fluent casual conversation.
