84 citations · 248 across the 19 of their papers we have counts for
22 papers
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…
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…
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…
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…
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…
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…
An Empirical Study of Software Exceptions in the Field using Search Logs
Foyzul Hassan, Chetan Bansal, Nachiappan Nagappan +2
Software engineers spend a substantial amount of time using Web search to accomplish software engineering tasks. Such search tasks include finding code snippets, API documentation,…
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…
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…
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…
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.…
Leveraging Multi-Source Weak Social Supervision for Early Detection of Fake News
Kai Shu, Guoqing Zheng, Yichuan Li +4
Social media has greatly enabled people to participate in online activities at an unprecedented rate. However, this unrestricted access also exacerbates the spread of misinformatio…
Analyzing Web Search Behavior for Software Engineering Tasks
Nikitha Rao, Chetan Bansal, Thomas Zimmermann +2
Web search plays an integral role in software engineering (SE) to help with various tasks such as finding documentation, debugging, installation, etc. In this work, we present the…
Meta Label Correction for Noisy Label Learning
Guoqing Zheng, Ahmed Hassan Awadallah, Susan Dumais
Leveraging weak or noisy supervision for building effective machine learning models has long been an important research problem. Its importance has further increased recently due t…
Detecting Fake News with Weak Social Supervision
Kai Shu, Ahmed Hassan Awadallah, Susan Dumais +1
Limited labeled data is becoming the largest bottleneck for supervised learning systems. This is especially the case for many real-world tasks where large scale annotated examples…
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…
Characterizing and Predicting Email Deferral Behavior
Bahareh Sarrafzadeh, Ahmed Hassan Awadallah, Christopher H. Lin +3
Email triage involves going through unhandled emails and deciding what to do with them. This familiar process can become increasingly challenging as the number of unhandled email g…
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…
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…
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…
Improving Image Search based on User Created Communities
Amruta Joshi, Junghoo Cho, Dragomir Radev +1
Tag-based retrieval of multimedia content is a difficult problem, not only because of the shorter length of tags associated with images and videos, but also due to mismatch in the…
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…