4 citations · 8 across the 4 of their papers we have counts for
5 papers · 1 filter
Table-To-Text generation and pre-training with TabT5
Ewa Andrejczuk, Julian Martin Eisenschlos, Francesco Piccinno +2
Encoder-only transformer models have been successfully applied to different table understanding tasks, as in TAPAS (Herzig et al., 2020). A major limitation of these architectures…
What Did You Say? Task-Oriented Dialog Datasets Are Not Conversational!?
Alice Shoshana Jakobovits, Francesco Piccinno, Yasemin Altun
High-quality datasets for task-oriented dialog are crucial for the development of virtual assistants. Yet three of the most relevant large scale dialog datasets suffer from one com…
Translate & Fill: Improving Zero-Shot Multilingual Semantic Parsing with Synthetic Data
Massimo Nicosia, Zhongdi Qu, Yasemin Altun
While multilingual pretrained language models (LMs) fine-tuned on a single language have shown substantial cross-lingual task transfer capabilities, there is still a wide performan…
Answering Conversational Questions on Structured Data without Logical Forms
Thomas Müller, Francesco Piccinno, Massimo Nicosia +2
We present a novel approach to answering sequential questions based on structured objects such as knowledge bases or tables without using a logical form as an intermediate represen…
Generating Logical Forms from Graph Representations of Text and Entities
Peter Shaw, Philip Massey, Angelica Chen +2
Structured information about entities is critical for many semantic parsing tasks. We present an approach that uses a Graph Neural Network (GNN) architecture to incorporate informa…