Search Results for author:
Found 7 papers, 2 papers with code
ImPaKT: A Dataset for Open-Schema Knowledge Base Construction
Large language models have ushered in a golden age of semantic parsing.
MAVE: A Product Dataset for Multi-source Attribute Value Extraction
Attribute value extraction refers to the task of identifying values of an attribute of interest from product information.
Ranked #1 on
Attribute Value Extraction
on MAVE
ShopTalk: A System for Conversational Faceted Search
The dialog understanding system consists of a deep-learned Contextual Language Understanding module, which interprets user utterances, and a primarily rules-based Dialog-State Tracker (DST), which updates the dialog state and formulates search requests intended for the fulfillment engine.
DOCENT: Learning Self-Supervised Entity Representations from Large Document Collections
This enables a new class of powerful, high-capacity representations that can ultimately distill much of the useful information about an entity from multiple text sources, without any human supervision.
RealFormer: Transformer Likes Residual Attention
Transformer is the backbone of modern NLP models.
Ranked #4 on
Paraphrase Identification
on Quora Question Pairs
Learning to Extract Attribute Value from Product via Question Answering: A Multi-task Approach
In particular, we build a question answering model which treats each attribute as a question and identifies the answer span corresponding to the attribute value in the product context.
A Generic Coordinate Descent Framework for Learning from Implicit Feedback
A diversity of complex models has been proposed for a wide variety of applications.
