Search Results for author: Mustafa Canim

Found 9 papers, 4 papers with code

Topic Transferable Table Question Answering

1 code implementation EMNLP 2021 Saneem Ahmed Chemmengath, Vishwajeet Kumar, Samarth Bharadwaj, Jaydeep Sen, Mustafa Canim, Soumen Chakrabarti, Alfio Gliozzo, Karthik Sankaranarayanan

Weakly-supervised table question-answering(TableQA) models have achieved state-of-art performance by using pre-trained BERT transformer to jointly encoding a question and a table to produce structured query for the question.

Question Answering Question Generation

CLTR: An End-to-End, Transformer-Based System for Cell-Level Table Retrieval and Table Question Answering

no code implementations ACL 2021 Feifei Pan, Mustafa Canim, Michael Glass, Alfio Gliozzo, Peter Fox

We present the first end-to-end, transformer-based table question answering (QA) system that takes natural language questions and massive table corpora as inputs to retrieve the most relevant tables and locate the correct table cells to answer the question.

Question Answering

AIT-QA: Question Answering Dataset over Complex Tables in the Airline Industry

1 code implementation24 Jun 2021 Yannis Katsis, Saneem Chemmengath, Vishwajeet Kumar, Samarth Bharadwaj, Mustafa Canim, Michael Glass, Alfio Gliozzo, Feifei Pan, Jaydeep Sen, Karthik Sankaranarayanan, Soumen Chakrabarti

Recent advances in transformers have enabled Table Question Answering (Table QA) systems to achieve high accuracy and SOTA results on open domain datasets like WikiTableQuestions and WikiSQL.

Question Answering Semantic Parsing

CLTR: An End-to-End, Transformer-Based System for Cell Level Table Retrieval and Table Question Answering

1 code implementation8 Jun 2021 Feifei Pan, Mustafa Canim, Michael Glass, Alfio Gliozzo, Peter Fox

We present the first end-to-end, transformer-based table question answering (QA) system that takes natural language questions and massive table corpus as inputs to retrieve the most relevant tables and locate the correct table cells to answer the question.

Question Answering

Capturing Row and Column Semantics in Transformer Based Question Answering over Tables

1 code implementation NAACL 2021 Michael Glass, Mustafa Canim, Alfio Gliozzo, Saneem Chemmengath, Vishwajeet Kumar, Rishav Chakravarti, Avi Sil, Feifei Pan, Samarth Bharadwaj, Nicolas Rodolfo Fauceglia

While this model yields extremely high accuracy at finding cell values on recent benchmarks, a second model we propose, called RCI representation, provides a significant efficiency advantage for online QA systems over tables by materializing embeddings for existing tables.

Question Answering

Type Prediction Systems

no code implementations2 Apr 2021 Sarthak Dash, Nandana Mihindukulasooriya, Alfio Gliozzo, Mustafa Canim

Inferring semantic types for entity mentions within text documents is an important asset for many downstream NLP tasks, such as Semantic Role Labelling, Entity Disambiguation, Knowledge Base Question Answering, etc.

Entity Disambiguation Knowledge Base Question Answering +1

Populating Web Scale Knowledge Graphs using Distantly Supervised Relation Extraction and Validation

no code implementations21 Aug 2019 Sarthak Dash, Michael R. Glass, Alfio Gliozzo, Mustafa Canim

In addition to that, the system uses a deep learning approach for knowledge base completion by utilizing the global structure information of the induced KG to further refine the confidence of the newly discovered relations.

Knowledge Base Completion Knowledge Graphs +1

Uncheatable Machine Learning Inference

no code implementations8 Aug 2019 Mustafa Canim, Ashish Kundu, Josh Payne

Given a classification service supplier $S$, intermediary CaaS provider $P$ claiming to use $S$ as a classification backend, and customer $C$, our work addresses the following questions: (i) how can $P$'s claim to be using $S$ be verified by $C$?

Classification Fraud Detection +1

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