Daniel Khashabi

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Coreference resolution is a key problem in natural language understanding that still escapes reliable solutions. One fundamental difficulty has been that of resolving instances involving pronouns… (More)

Joint Demosaicing and Denoising via Learned Nonparametric Random Fields

Daniel Khashabi, Sebastian Nowozin, Jeremy Jancsary, Andrew W. Fitzgibbon
IEEE Transactions on Image Processing
2014

We introduce a machine learning approach to demosaicing, the reconstruction of color images from incomplete color filter array samples. There are two challenges to overcome by a demosaicing method:… (More)

Question Answering via Integer Programming over Semi-Structured Knowledge

Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Peter Clark, Oren Etzioni, Dan Roth
IJCAI
2016

Answering science questions posed in natural language is an important AI challenge. Answering such questions often requires non-trivial inference and knowledge that goes beyond factoid retrieval.… (More)

Looking Beyond the Surface: A Challenge Set for Reading Comprehension over Multiple Sentences

Daniel Khashabi, Snigdha Chaturvedi, Michael A. Roth, Shyam Upadhyay, Dan Roth
NAACL-HLT
2018

We present a reading comprehension challenge in which questions can only be answered by taking into account information from multiple sentences. We solicit and verify questions and answers for this… (More)

Online Learning with Adversarial Delays

We study the performance of standard online learning algorithms when the feedback is delayed by an adversary. We show that online-gradient-descent [1] and follow-the-perturbed-leader [2] achieve… (More)

Learning What is Essential in Questions

Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Dan Roth
CoNLL
2017

Question answering (QA) systems are easily distracted by irrelevant or redundant words in questions, especially when faced with long or multi-sentence questions in difficult domains. This paper… (More)

Combining Retrieval, Statistics, and Inference to Answer Elementary Science Questions

Peter Clark, Oren Etzioni, +4 authors Daniel Khashabi
AAAI
2016

What capabilities are required for an AI system to pass standard 4th Grade Science Tests? Previous work has examined the use of Markov Logic Networks (MLNs) to represent the requisite background… (More)

Question Answering as Global Reasoning Over Semantic Abstractions

Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Dan Roth
AAAI
2018

We propose a novel method for exploiting the semantic structure of text to answer multiple-choice questions. The approach is especially suitable for domains that require reasoning over a diverse set… (More)

EDISON: Feature Extraction for NLP, Simplified

Mark Sammons, Christos Christodoulopoulos, Parisa Kordjamshidi, Daniel Khashabi, Vivek Srikumar, Dan Roth
LREC
2016

When designing Natural Language Processing (NLP) applications that use Machine Learning (ML) techniques, feature extraction becomes a significant part of the development effort, whether developing a… (More)

Better call Saul: Flexible Programming for Learning and Inference in NLP

Parisa Kordjamshidi, Daniel Khashabi, Christos Christodoulopoulos, Bhargav Mangipudi, Sameer Singh, Dan Roth
COLING
2016

We present a novel way for designing complex joint inference and learning models using Saul (Kordjamshidi et al., 2015), a recently-introduced declarative learning-based programming language (DeLBP).… (More)

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