Alert button
Picture for Andrew McCallum

Andrew McCallum

Alert button

Optimal Transport-based Alignment of Learned Character Representations for String Similarity

Jul 23, 2019
Derek Tam, Nicholas Monath, Ari Kobren, Aaron Traylor, Rajarshi Das, Andrew McCallum

Figure 1 for Optimal Transport-based Alignment of Learned Character Representations for String Similarity
Figure 2 for Optimal Transport-based Alignment of Learned Character Representations for String Similarity
Figure 3 for Optimal Transport-based Alignment of Learned Character Representations for String Similarity
Figure 4 for Optimal Transport-based Alignment of Learned Character Representations for String Similarity
Viaarxiv icon

Supervised Hierarchical Clustering with Exponential Linkage

Jun 19, 2019
Nishant Yadav, Ari Kobren, Nicholas Monath, Andrew McCallum

Figure 1 for Supervised Hierarchical Clustering with Exponential Linkage
Viaarxiv icon

Energy and Policy Considerations for Deep Learning in NLP

Jun 05, 2019
Emma Strubell, Ananya Ganesh, Andrew McCallum

Figure 1 for Energy and Policy Considerations for Deep Learning in NLP
Figure 2 for Energy and Policy Considerations for Deep Learning in NLP
Figure 3 for Energy and Policy Considerations for Deep Learning in NLP
Figure 4 for Energy and Policy Considerations for Deep Learning in NLP
Viaarxiv icon

The Materials Science Procedural Text Corpus: Annotating Materials Synthesis Procedures with Shallow Semantic Structures

May 16, 2019
Sheshera Mysore, Zach Jensen, Edward Kim, Kevin Huang, Haw-Shiuan Chang, Emma Strubell, Jeffrey Flanigan, Andrew McCallum, Elsa Olivetti

Figure 1 for The Materials Science Procedural Text Corpus: Annotating Materials Synthesis Procedures with Shallow Semantic Structures
Figure 2 for The Materials Science Procedural Text Corpus: Annotating Materials Synthesis Procedures with Shallow Semantic Structures
Figure 3 for The Materials Science Procedural Text Corpus: Annotating Materials Synthesis Procedures with Shallow Semantic Structures
Figure 4 for The Materials Science Procedural Text Corpus: Annotating Materials Synthesis Procedures with Shallow Semantic Structures
Viaarxiv icon

Multi-step Retriever-Reader Interaction for Scalable Open-domain Question Answering

May 14, 2019
Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, Andrew McCallum

Figure 1 for Multi-step Retriever-Reader Interaction for Scalable Open-domain Question Answering
Figure 2 for Multi-step Retriever-Reader Interaction for Scalable Open-domain Question Answering
Figure 3 for Multi-step Retriever-Reader Interaction for Scalable Open-domain Question Answering
Figure 4 for Multi-step Retriever-Reader Interaction for Scalable Open-domain Question Answering
Viaarxiv icon

OpenKI: Integrating Open Information Extraction and Knowledge Bases with Relation Inference

Apr 12, 2019
Dongxu Zhang, Subhabrata Mukherjee, Colin Lockard, Xin Luna Dong, Andrew McCallum

Figure 1 for OpenKI: Integrating Open Information Extraction and Knowledge Bases with Relation Inference
Figure 2 for OpenKI: Integrating Open Information Extraction and Knowledge Bases with Relation Inference
Figure 3 for OpenKI: Integrating Open Information Extraction and Knowledge Bases with Relation Inference
Figure 4 for OpenKI: Integrating Open Information Extraction and Knowledge Bases with Relation Inference
Viaarxiv icon

Unsupervised Latent Tree Induction with Deep Inside-Outside Recursive Autoencoders

Apr 04, 2019
Andrew Drozdov, Pat Verga, Mohit Yadav, Mohit Iyyer, Andrew McCallum

Figure 1 for Unsupervised Latent Tree Induction with Deep Inside-Outside Recursive Autoencoders
Figure 2 for Unsupervised Latent Tree Induction with Deep Inside-Outside Recursive Autoencoders
Figure 3 for Unsupervised Latent Tree Induction with Deep Inside-Outside Recursive Autoencoders
Figure 4 for Unsupervised Latent Tree Induction with Deep Inside-Outside Recursive Autoencoders
Viaarxiv icon

Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks

Dec 31, 2018
Edward Kim, Zach Jensen, Alexander van Grootel, Kevin Huang, Matthew Staib, Sheshera Mysore, Haw-Shiuan Chang, Emma Strubell, Andrew McCallum, Stefanie Jegelka, Elsa Olivetti

Figure 1 for Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks
Figure 2 for Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks
Figure 3 for Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks
Figure 4 for Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks
Viaarxiv icon

Search-Guided, Lightly-supervised Training of Structured Prediction Energy Networks

Dec 22, 2018
Amirmohammad Rooshenas, Dongxu Zhang, Gopal Sharma, Andrew McCallum

Figure 1 for Search-Guided, Lightly-supervised Training of Structured Prediction Energy Networks
Figure 2 for Search-Guided, Lightly-supervised Training of Structured Prediction Energy Networks
Figure 3 for Search-Guided, Lightly-supervised Training of Structured Prediction Energy Networks
Figure 4 for Search-Guided, Lightly-supervised Training of Structured Prediction Energy Networks
Viaarxiv icon

Syntax Helps ELMo Understand Semantics: Is Syntax Still Relevant in a Deep Neural Architecture for SRL?

Nov 12, 2018
Emma Strubell, Andrew McCallum

Figure 1 for Syntax Helps ELMo Understand Semantics: Is Syntax Still Relevant in a Deep Neural Architecture for SRL?
Figure 2 for Syntax Helps ELMo Understand Semantics: Is Syntax Still Relevant in a Deep Neural Architecture for SRL?
Figure 3 for Syntax Helps ELMo Understand Semantics: Is Syntax Still Relevant in a Deep Neural Architecture for SRL?
Figure 4 for Syntax Helps ELMo Understand Semantics: Is Syntax Still Relevant in a Deep Neural Architecture for SRL?
Viaarxiv icon