Alexa teacher model: Pretraining and distilling multi-billion-parameter encoders for natural language understanding systems
We present results from a large-scale experiment on pretraining encoders with non-
embedding parameter counts ranging from 700M to 9.3 B, their subsequent distillation into …
embedding parameter counts ranging from 700M to 9.3 B, their subsequent distillation into …
Bridging the gap between synthetic and natural questions via sentence decomposition for semantic parsing
Semantic parsing maps natural language questions into logical forms, which can be
executed against a knowledge base for answers. In real-world applications, the performance …
executed against a knowledge base for answers. In real-world applications, the performance …
Optimal Transport Posterior Alignment for Cross-lingual Semantic Parsing
Cross-lingual semantic parsing transfers parsing capability from a high-resource language
(eg, English) to low-resource languages with scarce training data. Previous work has …
(eg, English) to low-resource languages with scarce training data. Previous work has …
FastRAT: Fast and Efficient Cross-lingual Text-to-SQL Semantic Parsing
Recent advances of large pre-trained language models have motivated significant
breakthroughs in various Text-to-SQL tasks. However, a number of challenges inhibit the …
breakthroughs in various Text-to-SQL tasks. However, a number of challenges inhibit the …
Enhancing zero-shot multilingual semantic parsing: A framework leveraging large language models for data augmentation and advanced prompting techniques
In recent years, significant progress has been made in semantic parsing tasks due to the
introduction of pre-trained language models. However, there remains a notable gap …
introduction of pre-trained language models. However, there remains a notable gap …
Cross-lingual Back-Parsing: Utterance Synthesis from Meaning Representation for Zero-Resource Semantic Parsing
Recent efforts have aimed to utilize multilingual pretrained language models (mPLMs) to
extend semantic parsing (SP) across multiple languages without requiring extensive …
extend semantic parsing (SP) across multiple languages without requiring extensive …
Improving Cross-Lingual Transfer through Subtree-Aware Word Reordering
Despite the impressive growth of the abilities of multilingual language models, such as XLM-
R and mT5, it has been shown that they still face difficulties when tackling typologically …
R and mT5, it has been shown that they still face difficulties when tackling typologically …
Modelling cross-lingual transfer for semantic parsing
TR Sherborne - 2024 - era.ed.ac.uk
Semantic parsing maps natural language utterances to logical form representations of
meaning (eg, lambda calculus or SQL). A semantic parser functions as a human-computer …
meaning (eg, lambda calculus or SQL). A semantic parser functions as a human-computer …