35 citations · 201 across the 39 of their papers we have counts for
10 papers · 1 filter
Automatic Mixed-Precision Quantization Search of BERT
Changsheng Zhao, Ting Hua, Yilin Shen +2
Pre-trained language models such as BERT have shown remarkable effectiveness in various natural language processing tasks. However, these models usually contain millions of paramet…
ISEEQ: Information Seeking Question Generation using Dynamic Meta-Information Retrieval and Knowledge Graphs
Manas Gaur, Kalpa Gunaratna, Vijay Srinivasan +1
Conversational Information Seeking (CIS) is a relatively new research area within conversational AI that attempts to seek information from end-users in order to understand and sati…
Exploring Covariate and Concept Shift for Detection and Calibration of Out-of-Distribution Data
Junjiao Tian, Yen-Change Hsu, Yilin Shen +2
Moving beyond testing on in-distribution data works on Out-of-Distribution (OOD) detection have recently increased in popularity. A recent attempt to categorize OOD data introduces…
Using Neighborhood Context to Improve Information Extraction from Visual Documents Captured on Mobile Phones
Kalpa Gunaratna, Vijay Srinivasan, Sandeep Nama +1
Information Extraction from visual documents enables convenient and intelligent assistance to end users. We present a Neighborhood-based Information Extraction (NIE) approach that…
Enhancing the Generalization for Intent Classification and Out-of-Domain Detection in SLU
Yilin Shen, Yen-Chang Hsu, Avik Ray +1
Intent classification is a major task in spoken language understanding (SLU). Since most models are built with pre-collected in-domain (IND) training utterances, their ability to d…
An Adversarial Learning based Multi-Step Spoken Language Understanding System through Human-Computer Interaction
Yu Wang, Yilin Shen, Hongxia Jin
Most of the existing spoken language understanding systems can perform only semantic frame parsing based on a single-round user query. They cannot take users' feedback to update/ad…
Always Be Dreaming: A New Approach for Data-Free Class-Incremental Learning
James Smith, Yen-Chang Hsu, Jonathan Balloch +3
Modern computer vision applications suffer from catastrophic forgetting when incrementally learning new concepts over time. The most successful approaches to alleviate this forgett…
A Coarse to Fine Question Answering System based on Reinforcement Learning
Yu Wang, Hongxia Jin
In this paper, we present a coarse to fine question answering (CFQA) system based on reinforcement learning which can efficiently processes documents with different lengths by choo…
Entity Context Graph: Learning Entity Representations fromSemi-Structured Textual Sources on the Web
Kalpa Gunaratna, Yu Wang, Hongxia Jin
Knowledge is captured in the form of entities and their relationships and stored in knowledge graphs. Knowledge graphs enhance the capabilities of applications in many different ar…
Negative Data Augmentation
Abhishek Sinha, Kumar Ayush, Jiaming Song +3
Data augmentation is often used to enlarge datasets with synthetic samples generated in accordance with the underlying data distribution. To enable a wider range of augmentations,…