8 citations · 14 across the 6 of their papers we have counts for
10 papers
FormNetV2: Multimodal Graph Contrastive Learning for Form Document Information Extraction
Chen-Yu Lee, Chun-Liang Li, Hao Zhang +13
The recent advent of self-supervised pre-training techniques has led to a surge in the use of multimodal learning in form document understanding. However, existing approaches that…
Generate-and-Retrieve: use your predictions to improve retrieval for semantic parsing
Yury Zemlyanskiy, Michiel de Jong, Joshua Ainslie +5
A common recent approach to semantic parsing augments sequence-to-sequence models by retrieving and appending a set of training samples, called exemplars. The effectiveness of this…
LogicInference: A New Dataset for Teaching Logical Inference to seq2seq Models
Santiago Ontanon, Joshua Ainslie, Vaclav Cvicek +1
Machine learning models such as Transformers or LSTMs struggle with tasks that are compositional in nature such as those involving reasoning/inference. Although many datasets exist…
FormNet: Structural Encoding beyond Sequential Modeling in Form Document Information Extraction
Chen-Yu Lee, Chun-Liang Li, Timothy Dozat +7
Sequence modeling has demonstrated state-of-the-art performance on natural language and document understanding tasks. However, it is challenging to correctly serialize tokens in fo…
ShopTalk: A System for Conversational Faceted Search
Gurmeet Manku, James Lee-Thorp, Bhargav Kanagal +11
We present ShopTalk, a multi-turn conversational faceted search system for shopping that is designed to handle large and complex schemas that are beyond the scope of state of the a…
Improving Compositional Generalization in Classification Tasks via Structure Annotations
Juyong Kim, Pradeep Ravikumar, Joshua Ainslie +1
Compositional generalization is the ability to generalize systematically to a new data distribution by combining known components. Although humans seem to have a great ability to g…