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20112022
most citedStructure-Grounded Pretraining for Text-to-SQL

84 citations · 248 across the 19 of their papers we have counts for

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15 papers · 1 filter

cs.CL2022

PREME: Preference-based Meeting Exploration through an Interactive Questionnaire

Negar Arabzadeh, Ali Ahmadvand, Julia Kiseleva +4

The recent increase in the volume of online meetings necessitates automated tools for managing and organizing the material, especially when an attendee has missed the discussion an…

cs.CL2021

NL-EDIT: Correcting semantic parse errors through natural language interaction

Ahmed Elgohary, Christopher Meek, Matthew Richardson +3

We study semantic parsing in an interactive setting in which users correct errors with natural language feedback. We present NL-EDIT, a model for interpreting natural language feed…

cs.CL2020★ 84 cited

Structure-Grounded Pretraining for Text-to-SQL

Xiang Deng, Ahmed Hassan Awadallah, Christopher Meek +3

Learning to capture text-table alignment is essential for tasks like text-to-SQL. A model needs to correctly recognize natural language references to columns and values and to grou…

cs.CL2020★ 34 cited

Adaptive Self-training for Few-shot Neural Sequence Labeling

Yaqing Wang, Subhabrata Mukherjee, Haoda Chu +4

Sequence labeling is an important technique employed for many Natural Language Processing (NLP) tasks, such as Named Entity Recognition (NER), slot tagging for dialog systems and s…

cs.CL2020★ 41 cited

Uncertainty-aware Self-training for Text Classification with Few Labels

Subhabrata Mukherjee, Ahmed Hassan Awadallah

Recent success of large-scale pre-trained language models crucially hinge on fine-tuning them on large amounts of labeled data for the downstream task, that are typically expensive…

cs.CL2020★ 1 cited

Speak to your Parser: Interactive Text-to-SQL with Natural Language Feedback

Ahmed Elgohary, Saghar Hosseini, Ahmed Hassan Awadallah

We study the task of semantic parse correction with natural language feedback. Given a natural language utterance, most semantic parsing systems pose the problem as one-shot transl…

cs.CL2020★ 26 cited

Learning with Weak Supervision for Email Intent Detection

Kai Shu, Subhabrata Mukherjee, Guoqing Zheng +3

Email remains one of the most frequently used means of online communication. People spend a significant amount of time every day on emails to exchange information, manage tasks and…

cs.CL2020

Smart To-Do : Automatic Generation of To-Do Items from Emails

Sudipto Mukherjee, Subhabrata Mukherjee, Marcello Hasegawa +2

Intelligent features in email service applications aim to increase productivity by helping people organize their folders, compose their emails and respond to pending tasks. In this…

cs.CL2020

XtremeDistil: Multi-stage Distillation for Massive Multilingual Models

Subhabrata Mukherjee, Ahmed Awadallah

Deep and large pre-trained language models are the state-of-the-art for various natural language processing tasks. However, the huge size of these models could be a deterrent to us…

cs.CL2020★ 7 cited

Gender Bias in Multilingual Embeddings and Cross-Lingual Transfer

Jieyu Zhao, Subhabrata Mukherjee, Saghar Hosseini +2

Multilingual representations embed words from many languages into a single semantic space such that words with similar meanings are close to each other regardless of the language.…

cs.CL2019★ 9 cited

Distilling BERT into Simple Neural Networks with Unlabeled Transfer Data

Subhabrata Mukherjee, Ahmed Hassan Awadallah

Recent advances in pre-training huge models on large amounts of text through self supervision have obtained state-of-the-art results in various natural language processing tasks. H…

cs.CL2018★ 7 cited

Multi-Source Cross-Lingual Model Transfer: Learning What to Share

Xilun Chen, Ahmed Hassan Awadallah, Hany Hassan +2

Modern NLP applications have enjoyed a great boost utilizing neural networks models. Such deep neural models, however, are not applicable to most human languages due to the lack of…

cs.CL2018★ 4 cited

Adversarial Training for Community Question Answer Selection Based on Multi-scale Matching

Xiao Yang, Madian Khabsa, Miaosen Wang +4

Community-based question answering (CQA) websites represent an important source of information. As a result, the problem of matching the most valuable answers to their correspondin…

cs.CL2017

Actionable Email Intent Modeling with Reparametrized RNNs

Chu-Cheng Lin, Dongyeop Kang, Michael Gamon +3

Emails in the workplace are often intentional calls to action for its recipients. We propose to annotate these emails for what action its recipient will take. We argue that our app…

cs.CL2011★ 4 cited

The effect of linguistic constraints on the large scale organization of language

Madhav Krishna, Ahmed Hassan, Yang Liu +1

This paper studies the effect of linguistic constraints on the large scale organization of language. It describes the properties of linguistic networks built using texts of written…