Daniel Khashabi

Allen Institute for AI
http://danielkhashabi.com
Publications66
h-index19
Citations1,393
Highly Influential Citations190
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Looking Beyond the Surface: A Challenge Set for Reading Comprehension over Multiple Sentences
TLDR
The dataset is the first to study multi-sentence inference at scale, with an open-ended set of question types that requires reasoning skills, and finds human solvers to achieve an F1-score of 88.1%. Expand
UnifiedQA: Crossing Format Boundaries With a Single QA System
TLDR
This work uses the latest advances in language modeling to build a single pre-trained QA model, UNIFIEDQA, that performs well across 19 QA datasets spanning 4 diverse formats, and results in a new state of the art on 10 factoid and commonsense question answering datasets. Expand
Solving Hard Coreference Problems
TLDR
This paper presents a general coreference resolution system that significantly improves state-of-the-art performance on hard, Winograd-style, pronoun resolution cases, while still performing at the state of the art level on standard coreferenceresolution datasets. Expand
Joint Demosaicing and Denoising via Learned Nonparametric Random Fields
TLDR
The proposed method addresses both demosaicing challenges by learning a statistical model of images and noise from hundreds of natural images, and outperforms the previous state-of-the-art, in some setups by 0.7-dB PSNR. Expand
Combining Retrieval, Statistics, and Inference to Answer Elementary Science Questions
TLDR
This paper evaluates the methods on six years of unseen, unedited exam questions from the NY Regents Science Exam, and shows that the overall system's score is 71.3%, an improvement of 23.8% (absolute) over the MLN-based method described in previous work. Expand
Online Learning with Adversarial Delays
TLDR
It is shown that online-gradient-descent and follow-the-perturbed-leader achieve regret O(√D) in the delayed setting, where D is the sum of delays of each round's feedback. Expand
"Going on a vacation" takes longer than "Going for a walk": A Study of Temporal Commonsense Understanding
TLDR
It is found that the best current methods used on MCTACO are still far behind human performance, by about 20%, and several directions for improvement are discussed. Expand
Question Answering via Integer Programming over Semi-Structured Knowledge
TLDR
This work proposes a structured inference system for this task, formulated as an Integer Linear Program (ILP), that answers natural language questions using a semi-structured knowledge base derived from text, including questions requiring multi-step inference and a combination of multiple facts. Expand
Seeing Things from a Different Angle:Discovering Diverse Perspectives about Claims
TLDR
A thorough analysis of the dataset is provided to highlight key underlying language understanding challenges, and it is shown that human baselines across multiple subtasks far outperform ma-chine baselines built upon state-of-the-art NLP techniques. Expand
TransOMCS: From Linguistic Graphs to Commonsense Knowledge
TLDR
Experimental results demonstrate the transferability of linguistic knowledge to commonsense knowledge and the effectiveness of the proposed approach in terms of quantity, novelty, and quality. Expand
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