107 citations · 185 across the 10 of their papers we have counts for
6 papers · 1 filter
SeeGULL: A Stereotype Benchmark with Broad Geo-Cultural Coverage Leveraging Generative Models
Akshita Jha, Aida Davani, Chandan K. Reddy +3
Stereotype benchmark datasets are crucial to detect and mitigate social stereotypes about groups of people in NLP models. However, existing datasets are limited in size and coverag…
A Simple and Effective Self-Supervised Contrastive Learning Framework for Aspect Detection
Tian Shi, Liuqing Li, Ping Wang +1
Unsupervised aspect detection (UAD) aims at automatically extracting interpretable aspects and identifying aspect-specific segments (such as sentences) from online reviews. However…
LATTE: Latent Type Modeling for Biomedical Entity Linking
Ming Zhu, Busra Celikkaya, Parminder Bhatia +1
Entity linking is the task of linking mentions of named entities in natural language text, to entities in a curated knowledge-base. This is of significant importance in the biomedi…
Text-to-SQL Generation for Question Answering on Electronic Medical Records
Ping Wang, Tian Shi, Chandan K. Reddy
Electronic medical records (EMR) contain comprehensive patient information and are typically stored in a relational database with multiple tables. Effective and efficient patient i…
LeafNATS: An Open-Source Toolkit and Live Demo System for Neural Abstractive Text Summarization
Tian Shi, Ping Wang, Chandan K. Reddy
Neural abstractive text summarization (NATS) has received a lot of attention in the past few years from both industry and academia. In this paper, we introduce an open-source toolk…
Neural Abstractive Text Summarization with Sequence-to-Sequence Models
Tian Shi, Yaser Keneshloo, Naren Ramakrishnan +1
In the past few years, neural abstractive text summarization with sequence-to-sequence (seq2seq) models have gained a lot of popularity. Many interesting techniques have been propo…