Samuel R. Bowman

According to our database1, Samuel R. Bowman authored at least 28 papers between 2010 and 2018.

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

Timeline

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Bibliography

2018
Do latent tree learning models identify meaningful structure in sentences?
TACL, 2018

A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference.
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

ListOps: A Diagnostic Dataset for Latent Tree Learning.
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics, 2018

Training a Ranking Function for Open-Domain Question Answering.
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics, 2018

Annotation Artifacts in Natural Language Inference Data.
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

Stable and Effective Trainable Greedy Decoding for Sequence to Sequence Learning.
Proceedings of the 6th International Conference on Learning Representations, 2018

Language Modeling Teaches You More than Translation Does: Lessons Learned Through Auxiliary Syntactic Task Analysis.
Proceedings of the Workshop: Analyzing and Interpreting Neural Networks for NLP, 2018

GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding.
Proceedings of the Workshop: Analyzing and Interpreting Neural Networks for NLP, 2018

Grammar Induction with Neural Language Models: An Unusual Replication.
Proceedings of the Workshop: Analyzing and Interpreting Neural Networks for NLP, 2018

Grammar Induction with Neural Language Models: An Unusual Replication.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

XNLI: Evaluating Cross-lingual Sentence Representations.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

A Stable and Effective Learning Strategy for Trainable Greedy Decoding.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

The Lifted Matrix-Space Model for Semantic Composition.
Proceedings of the 22nd Conference on Computational Natural Language Learning, 2018

Ruminating Reader: Reasoning with Gated Multi-hop Attention.
Proceedings of the Workshop on Machine Reading for Question Answering@ACL 2018, 2018

2017
The RepEval 2017 Shared Task: Multi-Genre Natural Language Inference with Sentence Representations.
Proceedings of the 2nd Workshop on Evaluating Vector Space Representations for NLP, 2017

Proceedings of the 2nd Workshop on Evaluating Vector Space Representations for NLP.
Proceedings of the 2nd Workshop on Evaluating Vector Space Representations for NLP, 2017

Sequential Attention: A Context-Aware Alignment Function for Machine Reading.
Proceedings of the 2nd Workshop on Representation Learning for NLP, 2017

2016
Generating Sentences from a Continuous Space.
Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning, 2016

A Fast Unified Model for Parsing and Sentence Understanding.
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

2015
Tree-Structured Composition in Neural Networks without Tree-Structured Architectures.
Proceedings of the NIPS Workshop on Cognitive Computation: Integrating Neural and Symbolic Approaches co-located with the 29th Annual Conference on Neural Information Processing Systems (NIPS 2015), 2015

A large annotated corpus for learning natural language inference.
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, 2015

Learning Distributed Word Representations for Natural Logic Reasoning.
Proceedings of the 2015 AAAI Spring Symposia, 2015

2014
Can recursive neural tensor networks learn logical reasoning?
Proceedings of the 2nd International Conference on Learning Representations, 2014

A Gold Standard Dependency Corpus for English.
Proceedings of the Ninth International Conference on Language Resources and Evaluation, 2014

2013
More Constructions, More Genres: Extending Stanford Dependencies.
Proceedings of the Second International Conference on Dependency Linguistics, 2013

2012
Automatic Animacy Classification.
Proceedings of the Human Language Technologies: Conference of the North American Chapter of the Association of Computational Linguistics, 2012

2011
Speech recognitionwith segmental conditional random fields: A summary of the JHU CLSP 2010 Summer Workshop.
Proceedings of the IEEE International Conference on Acoustics, 2011

2010
Modeling pronunciation variation with context-dependent articulatory feature decision trees.
Proceedings of the INTERSPEECH 2010, 2010


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