Matt Gardner

Orcid: 0000-0001-8458-1727

Affiliations:
  • Microsoft Semantic Machines
  • Allen Institute for Artificial Intelligence (AI2), Seattle, USA
  • Carnegie Mellon University, School of Computer Science, Pittsburgh, PA, USA
  • Brigham Young University, Department of Computer Scienc, Provo, UT, USA


According to our database1, Matt Gardner authored at least 89 papers between 2009 and 2023.

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Bibliography

2023
QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehension.
ACM Comput. Surv., 2023

Coverage-based Example Selection for In-Context Learning.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022
Structurally Diverse Sampling Reduces Spurious Correlations in Semantic Parsing Datasets.
CoRR, 2022

Impact of Pretraining Term Frequencies on Few-Shot Reasoning.
CoRR, 2022

Evidentiality-guided Generation for Knowledge-Intensive NLP Tasks.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Snoopy: An Online Interface for Exploring the Effect of Pretraining Term Frequencies on Few-Shot LM Performance.
Proceedings of the The 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Impact of Pretraining Term Frequencies on Few-Shot Numerical Reasoning.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

CONDAQA: A Contrastive Reading Comprehension Dataset for Reasoning about Negation.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Structurally Diverse Sampling for Sample-Efficient Training and Comprehensive Evaluation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Successive Prompting for Decomposing Complex Questions.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Generating Data to Mitigate Spurious Correlations in Natural Language Inference Datasets.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

When to Use Multi-Task Learning vs Intermediate Fine-Tuning for Pre-Trained Encoder Transfer Learning.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2022

ReCLIP: A Strong Zero-Shot Baseline for Referring Expression Comprehension.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

Tailor: Generating and Perturbing Text with Semantic Controls.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

A Meta-framework for Spatiotemporal Quantity Extraction from Text.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021
Latent Compositional Representations Improve Systematic Generalization in Grounded Question Answering.
Trans. Assoc. Comput. Linguistics, 2021

Documenting the English Colossal Clean Crawled Corpus.
CoRR, 2021

Mitigating False-Negative Contexts in Multi-document QuestionAnswering with Retrieval Marginalization.
CoRR, 2021

A Dataset of Information-Seeking Questions and Answers Anchored in Research Papers.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Mitigating False-Negative Contexts in Multi-document Question Answering with Retrieval Marginalization.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Paired Examples as Indirect Supervision in Latent Decision Models.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Generative Context Pair Selection for Multi-hop Question Answering.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Learning with Instance Bundles for Reading Comprehension.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

COVR: A Test-Bed for Visually Grounded Compositional Generalization with Real Images.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Competency Problems: On Finding and Removing Artifacts in Language Data.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Enforcing Consistency in Weakly Supervised Semantic Parsing.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020
Break It Down: A Question Understanding Benchmark.
Trans. Assoc. Comput. Linguistics, 2020

Understanding Mention Detector-Linker Interaction for Neural Coreference Resolution.
CoRR, 2020

Multi-Step Inference for Reasoning Over Paragraphs.
CoRR, 2020

Evaluating NLP Models via Contrast Sets.
CoRR, 2020

Neural Module Networks for Reasoning over Text.
Proceedings of the 8th International Conference on Learning Representations, 2020

Learning from Task Descriptions.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Interpreting Predictions of NLP Models.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Tutorial Abstracts, 2020

MedICaT: A Dataset of Medical Images, Captions, and Textual References.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Improving Compositional Generalization in Semantic Parsing.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

TORQUE: A Reading Comprehension Dataset of Temporal Ordering Questions.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Easy, Reproducible and Quality-Controlled Data Collection with CROWDAQ.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, 2020

Multi-Step Inference for Reasoning Over Paragraphs.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

IIRC: A Dataset of Incomplete Information Reading Comprehension Questions.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

MOCHA: A Dataset for Training and Evaluating Generative Reading Comprehension Metrics.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020


Obtaining Faithful Interpretations from Compositional Neural Networks.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

On Importance Sampling-Based Evaluation of Latent Language Models.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Dynamic Sampling Strategies for Multi-Task Reading Comprehension.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Benefits of Intermediate Annotations in Reading Comprehension.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019
ORB: An Open Reading Benchmark for Comprehensive Evaluation of Machine Reading Comprehension.
CoRR, 2019

Question Answering is a Format; When is it Useful?
CoRR, 2019

Universal Adversarial Triggers for NLP.
CoRR, 2019

Grammar-based Neural Text-to-SQL Generation.
CoRR, 2019

Analyzing Compositionality in Visual Question Answering.
Proceedings of the Visually Grounded Interaction and Language (ViGIL), 2019

Linguistic Knowledge and Transferability of Contextual Representations.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Iterative Search for Weakly Supervised Semantic Parsing.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Do NLP Models Know Numbers? Probing Numeracy in Embeddings.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Universal Adversarial Triggers for Attacking and Analyzing NLP.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

QuaRTz: An Open-Domain Dataset of Qualitative Relationship Questions.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Quoref: A Reading Comprehension Dataset with Questions Requiring Coreferential Reasoning.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Global Reasoning over Database Structures for Text-to-SQL Parsing.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Compositional Questions Do Not Necessitate Multi-hop Reasoning.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Barack's Wife Hillary: Using Knowledge Graphs for Fact-Aware Language Modeling.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Reasoning Over Paragraph Effects in Situations.
Proceedings of the 2nd Workshop on Machine Reading for Question Answering, 2019

On Making Reading Comprehension More Comprehensive.
Proceedings of the 2nd Workshop on Machine Reading for Question Answering, 2019

Comprehensive Multi-Dataset Evaluation of Reading Comprehension.
Proceedings of the 2nd Workshop on Machine Reading for Question Answering, 2019

Evaluating Question Answering Evaluation.
Proceedings of the 2nd Workshop on Machine Reading for Question Answering, 2019

QUAREL: A Dataset and Models for Answering Questions about Qualitative Relationships.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
AllenNLP: A Deep Semantic Natural Language Processing Platform.
CoRR, 2018

Never-ending learning.
Commun. ACM, 2018

Deep Contextualized Word Representations.
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

Structured Alignment Networks for Matching Sentences.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Neural Semantic Parsing.
Proceedings of ACL 2018, Melbourne, Australia, July 15-20, 2018, Tutorial Abstracts, 2018

Simple and Effective Multi-Paragraph Reading Comprehension.
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

2017
Neural Semantic Parsing with Type Constraints for Semi-Structured Tables.
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

Crowdsourcing Multiple Choice Science Questions.
Proceedings of the 3rd Workshop on Noisy User-generated Text, 2017

Open-Vocabulary Semantic Parsing with both Distributional Statistics and Formal Knowledge.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2015
CMUML System for KBP 2015 Cold Start Slot Filling.
Proceedings of the 2015 Text Analysis Conference, 2015

Translation Invariant Word Embeddings.
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, 2015

Efficient and Expressive Knowledge Base Completion Using Subgraph Feature Extraction.
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, 2015

Combining Vector Space Embeddings with Symbolic Logical Inference over Open-Domain Text.
Proceedings of the 2015 AAAI Spring Symposia, 2015


2014
Incorporating Vector Space Similarity in Random Walk Inference over Knowledge Bases.
Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, 2014

2013
CMUML System for KBP 2013 Slot Filling.
Proceedings of the Sixth Text Analysis Conference, 2013

Improving Learning and Inference in a Large Knowledge-Base using Latent Syntactic Cues.
Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, 2013

2012
A speculative approach to parallelization in particle swarm optimization.
Swarm Intell., 2012

Adding Distributional Semantics to Knowledge Base Entities through Web-scale Entity Linking.
Proceedings of the Joint Workshop on Automatic Knowledge Base Construction and Web-scale Knowledge Extraction, 2012

2010
Speculative Evaluation in Particle Swarm Optimization.
Proceedings of the Parallel Problem Solving from Nature, 2010

2009
An exploration of topologies and communication in large particle swarms.
Proceedings of the IEEE Congress on Evolutionary Computation, 2009


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