Adam Trischler

According to our database1, Adam Trischler authored at least 48 papers between 2016 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2020
Exploring and Predicting Transferability across NLP Tasks.
CoRR, 2020

Exploiting Structured Knowledge in Text via Graph-Guided Representation Learning.
CoRR, 2020

Role-Wise Data Augmentation for Knowledge Distillation.
CoRR, 2020

Learning Dynamic Knowledge Graphs to Generalize on Text-Based Games.
CoRR, 2020

One Size Does Not Fit All: Generating and Evaluating Variable Number of Keyphrases.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Interactive Machine Comprehension with Information Seeking Agents.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019
Building Dynamic Knowledge Graphs from Text-based Games.
CoRR, 2019

Does Order Matter? An Empirical Study on Generating Multiple Keyphrases as a Sequence.
CoRR, 2019

Metalearned Neural Memory.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

An Empirical Study of Example Forgetting during Deep Neural Network Learning.
Proceedings of the 7th International Conference on Learning Representations, 2019

Learning deep representations by mutual information estimation and maximization.
Proceedings of the 7th International Conference on Learning Representations, 2019

Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension.
Proceedings of the 7th International Conference on Learning Representations, 2019

A Study of State Aliasing in Structured Prediction with RNNs.
Proceedings of the Deep Reinforcement Learning Meets Structured Prediction, 2019

Interactive Language Learning by Question Answering.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

How Reasonable are Common-Sense Reasoning Tasks: A Case-Study on the Winograd Schema Challenge and SWAG.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

The KnowRef Coreference Corpus: Removing Gender and Number Cues for Difficult Pronominal Anaphora Resolution.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018
On the Evaluation of Common-Sense Reasoning in Natural Language Understanding.
CoRR, 2018

The Hard-CoRe Coreference Corpus: Removing Gender and Number Cues for Difficult Pronominal Anaphora Resolution.
CoRR, 2018

Generating Diverse Numbers of Diverse Keyphrases.
CoRR, 2018

Learning deep representations by mutual information estimation and maximization.
CoRR, 2018

Metalearning with Hebbian Fast Weights.
CoRR, 2018

Counting to Explore and Generalize in Text-based Games.
CoRR, 2018

Towards Text Generation with Adversarially Learned Neural Outlines.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

A Generalized Knowledge Hunting Framework for the Winograd Schema Challenge.
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics, 2018

TextWorld: A Learning Environment for Text-Based Games.
Proceedings of the Computer Games - 7th Workshop, 2018

Rapid Adaptation with Conditionally Shifted Neurons.
Proceedings of the 35th International Conference on Machine Learning, 2018

Focused Hierarchical RNNs for Conditional Sequence Processing.
Proceedings of the 35th International Conference on Machine Learning, 2018

Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning.
Proceedings of the 6th International Conference on Learning Representations, 2018

Twin Networks: Matching the Future for Sequence Generation.
Proceedings of the 6th International Conference on Learning Representations, 2018

FigureQA: An Annotated Figure Dataset for Visual Reasoning.
Proceedings of the 6th International Conference on Learning Representations, 2018

Boundary Seeking GANs.
Proceedings of the 6th International Conference on Learning Representations, 2018

A Knowledge Hunting Framework for Common Sense Reasoning.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Neural Models for Key Phrase Extraction and Question Generation.
Proceedings of the Workshop on Machine Reading for Question Answering@ACL 2018, 2018

2017
Learning Rapid-Temporal Adaptations.
CoRR, 2017

Variational Bi-LSTMs.
CoRR, 2017

A Joint Model for Question Answering and Question Generation.
CoRR, 2017

Neural Models for Key Phrase Detection and Question Generation.
CoRR, 2017

Plan, Attend, Generate: Character-level Neural Machine Translation with Planning in the Decoder.
CoRR, 2017

Machine Comprehension by Text-to-Text Neural Question Generation.
Proceedings of the 2nd Workshop on Representation Learning for NLP, 2017

NewsQA: A Machine Comprehension Dataset.
Proceedings of the 2nd Workshop on Representation Learning for NLP, 2017

Plan, Attend, Generate: Character-Level Neural Machine Translation with Planning.
Proceedings of the 2nd Workshop on Representation Learning for NLP, 2017

Plan, Attend, Generate: Planning for Sequence-to-Sequence Models.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Learning Algorithms for Active Learning.
Proceedings of the 5th International Conference on Learning Representations, 2017

2016
Natural Language Comprehension with the EpiReader.
CoRR, 2016

A Parallel-Hierarchical Model for Machine Comprehension on Sparse Data.
CoRR, 2016

Towards Information-Seeking Agents.
CoRR, 2016

Natural Language Comprehension with the EpiReader.
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016

A Parallel-Hierarchical Model for Machine Comprehension on Sparse Data.
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016


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