Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox
Picture for Eduard Hovy

Eduard Hovy

Retrieve, Caption, Generate: Visual Grounding for Enhancing Commonsense in Text Generation Models


Sep 08, 2021
Steven Y. Feng, Kevin Lu, Zhuofu Tao, Malihe Alikhani, Teruko Mitamura, Eduard Hovy, Varun Gangal

Figure 1 for Retrieve, Caption, Generate: Visual Grounding for Enhancing Commonsense in Text Generation Models
Figure 2 for Retrieve, Caption, Generate: Visual Grounding for Enhancing Commonsense in Text Generation Models
Figure 3 for Retrieve, Caption, Generate: Visual Grounding for Enhancing Commonsense in Text Generation Models
Figure 4 for Retrieve, Caption, Generate: Visual Grounding for Enhancing Commonsense in Text Generation Models

  Access Paper or Ask Questions

SAPPHIRE: Approaches for Enhanced Concept-to-Text Generation


Aug 15, 2021
Steven Y. Feng, Jessica Huynh, Chaitanya Narisetty, Eduard Hovy, Varun Gangal

Figure 1 for SAPPHIRE: Approaches for Enhanced Concept-to-Text Generation
Figure 2 for SAPPHIRE: Approaches for Enhanced Concept-to-Text Generation
Figure 3 for SAPPHIRE: Approaches for Enhanced Concept-to-Text Generation
Figure 4 for SAPPHIRE: Approaches for Enhanced Concept-to-Text Generation
* INLG 2021. Code available at https://github.com/styfeng/SAPPHIRE 
  Access Paper or Ask Questions

Comparative Error Analysis in Neural and Finite-state Models for Unsupervised Character-level Transduction


Jun 24, 2021
Maria Ryskina, Eduard Hovy, Taylor Berg-Kirkpatrick, Matthew R. Gormley

Figure 1 for Comparative Error Analysis in Neural and Finite-state Models for Unsupervised Character-level Transduction
Figure 2 for Comparative Error Analysis in Neural and Finite-state Models for Unsupervised Character-level Transduction
Figure 3 for Comparative Error Analysis in Neural and Finite-state Models for Unsupervised Character-level Transduction
Figure 4 for Comparative Error Analysis in Neural and Finite-state Models for Unsupervised Character-level Transduction
* Accepted to SIGMORPHON 2021 
  Access Paper or Ask Questions

Improving Automated Evaluation of Open Domain Dialog via Diverse Reference Augmentation


Jun 05, 2021
Varun Gangal, Harsh Jhamtani, Eduard Hovy, Taylor Berg-Kirkpatrick

Figure 1 for Improving Automated Evaluation of Open Domain Dialog via Diverse Reference Augmentation
Figure 2 for Improving Automated Evaluation of Open Domain Dialog via Diverse Reference Augmentation
Figure 3 for Improving Automated Evaluation of Open Domain Dialog via Diverse Reference Augmentation
Figure 4 for Improving Automated Evaluation of Open Domain Dialog via Diverse Reference Augmentation
* Findings of ACL 2021 
  Access Paper or Ask Questions

More Identifiable yet Equally Performant Transformers for Text Classification


Jun 02, 2021
Rishabh Bhardwaj, Navonil Majumder, Soujanya Poria, Eduard Hovy

Figure 1 for More Identifiable yet Equally Performant Transformers for Text Classification
Figure 2 for More Identifiable yet Equally Performant Transformers for Text Classification
Figure 3 for More Identifiable yet Equally Performant Transformers for Text Classification
Figure 4 for More Identifiable yet Equally Performant Transformers for Text Classification
* ACL 2021 
 * ACL 2021 
  Access Paper or Ask Questions

A Survey of Data Augmentation Approaches for NLP


May 29, 2021
Steven Y. Feng, Varun Gangal, Jason Wei, Sarath Chandar, Soroush Vosoughi, Teruko Mitamura, Eduard Hovy

Figure 1 for A Survey of Data Augmentation Approaches for NLP
Figure 2 for A Survey of Data Augmentation Approaches for NLP
Figure 3 for A Survey of Data Augmentation Approaches for NLP
Figure 4 for A Survey of Data Augmentation Approaches for NLP
* Accepted to ACL 2021 Findings. GitHub repo with paper list at https://github.com/styfeng/DataAug4NLP 
  Access Paper or Ask Questions

Could you give me a hint? Generating inference graphs for defeasible reasoning


May 29, 2021
Aman Madaan, Dheeraj Rajagopal, Niket Tandon, Yiming Yang, Eduard Hovy

Figure 1 for Could you give me a hint? Generating inference graphs for defeasible reasoning
Figure 2 for Could you give me a hint? Generating inference graphs for defeasible reasoning
Figure 3 for Could you give me a hint? Generating inference graphs for defeasible reasoning
Figure 4 for Could you give me a hint? Generating inference graphs for defeasible reasoning
* Findings of the Association for Computational Linguistics: ACL 2021 
  Access Paper or Ask Questions

Classifying Argumentative Relations Using Logical Mechanisms and Argumentation Schemes


May 17, 2021
Yohan Jo, Seojin Bang, Chris Reed, Eduard Hovy

Figure 1 for Classifying Argumentative Relations Using Logical Mechanisms and Argumentation Schemes
Figure 2 for Classifying Argumentative Relations Using Logical Mechanisms and Argumentation Schemes
Figure 3 for Classifying Argumentative Relations Using Logical Mechanisms and Argumentation Schemes
Figure 4 for Classifying Argumentative Relations Using Logical Mechanisms and Argumentation Schemes
* To Appear in TACL 2021 
  Access Paper or Ask Questions

NAREOR: The Narrative Reordering Problem


Apr 14, 2021
Varun Gangal, Steven Y. Feng, Eduard Hovy, Teruko Mitamura

Figure 1 for NAREOR: The Narrative Reordering Problem
Figure 2 for NAREOR: The Narrative Reordering Problem
Figure 3 for NAREOR: The Narrative Reordering Problem
Figure 4 for NAREOR: The Narrative Reordering Problem

  Access Paper or Ask Questions

StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer


Apr 12, 2021
Yiwei Lyu, Paul Pu Liang, Hai Pham, Eduard Hovy, Barnabás Póczos, Ruslan Salakhutdinov, Louis-Philippe Morency

Figure 1 for StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer
Figure 2 for StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer
Figure 3 for StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer
Figure 4 for StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer
* NAACL 2021, code available at https://github.com/lvyiwei1/StylePTB/ 
  Access Paper or Ask Questions

CURIE: An Iterative Querying Approach for Reasoning About Situations


Apr 05, 2021
Dheeraj Rajagopal, Aman Madaan, Niket Tandon, Yiming Yang, Shrimai Prabhumoye, Abhilasha Ravichander, Peter Clark, Eduard Hovy

Figure 1 for CURIE: An Iterative Querying Approach for Reasoning About Situations
Figure 2 for CURIE: An Iterative Querying Approach for Reasoning About Situations
Figure 3 for CURIE: An Iterative Querying Approach for Reasoning About Situations
Figure 4 for CURIE: An Iterative Querying Approach for Reasoning About Situations
* This paper builds upon EIGEN (arXiv:2010.11764) and proposes a general framework for situational reasoning 
  Access Paper or Ask Questions

SelfExplain: A Self-Explaining Architecture for Neural Text Classifiers


Mar 23, 2021
Dheeraj Rajagopal, Vidhisha Balachandran, Eduard Hovy, Yulia Tsvetkov

Figure 1 for SelfExplain: A Self-Explaining Architecture for Neural Text Classifiers
Figure 2 for SelfExplain: A Self-Explaining Architecture for Neural Text Classifiers
Figure 3 for SelfExplain: A Self-Explaining Architecture for Neural Text Classifiers
Figure 4 for SelfExplain: A Self-Explaining Architecture for Neural Text Classifiers

  Access Paper or Ask Questions

NoiseQA: Challenge Set Evaluation for User-Centric Question Answering


Feb 16, 2021
Abhilasha Ravichander, Siddharth Dalmia, Maria Ryskina, Florian Metze, Eduard Hovy, Alan W Black

Figure 1 for NoiseQA: Challenge Set Evaluation for User-Centric Question Answering
Figure 2 for NoiseQA: Challenge Set Evaluation for User-Centric Question Answering
Figure 3 for NoiseQA: Challenge Set Evaluation for User-Centric Question Answering
Figure 4 for NoiseQA: Challenge Set Evaluation for User-Centric Question Answering
* EACL 2021 
  Access Paper or Ask Questions

Measuring and Improving Consistency in Pretrained Language Models


Feb 01, 2021
Yanai Elazar, Nora Kassner, Shauli Ravfogel, Abhilasha Ravichander, Eduard Hovy, Hinrich Schütze, Yoav Goldberg

Figure 1 for Measuring and Improving Consistency in Pretrained Language Models
Figure 2 for Measuring and Improving Consistency in Pretrained Language Models
Figure 3 for Measuring and Improving Consistency in Pretrained Language Models
Figure 4 for Measuring and Improving Consistency in Pretrained Language Models

  Access Paper or Ask Questions

Exploring Neural Entity Representations for Semantic Information


Nov 17, 2020
Andrew Runge, Eduard Hovy

Figure 1 for Exploring Neural Entity Representations for Semantic Information
Figure 2 for Exploring Neural Entity Representations for Semantic Information
Figure 3 for Exploring Neural Entity Representations for Semantic Information
Figure 4 for Exploring Neural Entity Representations for Semantic Information
* Proceedings of the Third BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP 2020, p. 204-216 
 * 9 pages, 1 figure 
  Access Paper or Ask Questions

Incorporating a Local Translation Mechanism into Non-autoregressive Translation


Nov 12, 2020
Xiang Kong, Zhisong Zhang, Eduard Hovy

Figure 1 for Incorporating a Local Translation Mechanism into Non-autoregressive Translation
Figure 2 for Incorporating a Local Translation Mechanism into Non-autoregressive Translation
Figure 3 for Incorporating a Local Translation Mechanism into Non-autoregressive Translation
Figure 4 for Incorporating a Local Translation Mechanism into Non-autoregressive Translation
* EMNLP 2020 
  Access Paper or Ask Questions

Event-Related Bias Removal for Real-time Disaster Events


Nov 02, 2020
Evangelia Spiliopoulou, Salvador Medina Maza, Eduard Hovy, Alexander Hauptmann

Figure 1 for Event-Related Bias Removal for Real-time Disaster Events
Figure 2 for Event-Related Bias Removal for Real-time Disaster Events
Figure 3 for Event-Related Bias Removal for Real-time Disaster Events
Figure 4 for Event-Related Bias Removal for Real-time Disaster Events
* To appear in EMNLP Findings 2020 
  Access Paper or Ask Questions

A Dataset for Tracking Entities in Open Domain Procedural Text


Oct 31, 2020
Niket Tandon, Keisuke Sakaguchi, Bhavana Dalvi Mishra, Dheeraj Rajagopal, Peter Clark, Michal Guerquin, Kyle Richardson, Eduard Hovy

Figure 1 for A Dataset for Tracking Entities in Open Domain Procedural Text
Figure 2 for A Dataset for Tracking Entities in Open Domain Procedural Text
Figure 3 for A Dataset for Tracking Entities in Open Domain Procedural Text
Figure 4 for A Dataset for Tracking Entities in Open Domain Procedural Text
* To appear in EMNLP 2020 
  Access Paper or Ask Questions

Pair the Dots: Jointly Examining Training History and Test Stimuli for Model Interpretability


Oct 31, 2020
Yuxian Meng, Chun Fan, Zijun Sun, Eduard Hovy, Fei Wu, Jiwei Li

Figure 1 for Pair the Dots: Jointly Examining Training History and Test Stimuli for Model Interpretability
Figure 2 for Pair the Dots: Jointly Examining Training History and Test Stimuli for Model Interpretability
Figure 3 for Pair the Dots: Jointly Examining Training History and Test Stimuli for Model Interpretability
Figure 4 for Pair the Dots: Jointly Examining Training History and Test Stimuli for Model Interpretability

  Access Paper or Ask Questions

EIGEN: Event Influence GENeration using Pre-trained Language Models


Oct 22, 2020
Aman Madaan, Dheeraj Rajagopal, Yiming Yang, Abhilasha Ravichander, Eduard Hovy, Shrimai Prabhumoye

Figure 1 for EIGEN: Event Influence GENeration using Pre-trained Language Models
Figure 2 for EIGEN: Event Influence GENeration using Pre-trained Language Models
Figure 3 for EIGEN: Event Influence GENeration using Pre-trained Language Models
Figure 4 for EIGEN: Event Influence GENeration using Pre-trained Language Models

  Access Paper or Ask Questions

Plan ahead: Self-Supervised Text Planning for Paragraph Completion Task


Oct 11, 2020
Dongyeop Kang, Eduard Hovy

Figure 1 for Plan ahead: Self-Supervised Text Planning for Paragraph Completion Task
Figure 2 for Plan ahead: Self-Supervised Text Planning for Paragraph Completion Task
Figure 3 for Plan ahead: Self-Supervised Text Planning for Paragraph Completion Task
Figure 4 for Plan ahead: Self-Supervised Text Planning for Paragraph Completion Task
* EMNLP 2020 
  Access Paper or Ask Questions

GenAug: Data Augmentation for Finetuning Text Generators


Oct 10, 2020
Steven Y. Feng, Varun Gangal, Dongyeop Kang, Teruko Mitamura, Eduard Hovy

Figure 1 for GenAug: Data Augmentation for Finetuning Text Generators
Figure 2 for GenAug: Data Augmentation for Finetuning Text Generators
Figure 3 for GenAug: Data Augmentation for Finetuning Text Generators
Figure 4 for GenAug: Data Augmentation for Finetuning Text Generators
* EMNLP 2020 Deep Learning Inside Out (DeeLIO) Workshop; Code available at https://github.com/styfeng/GenAug 
  Access Paper or Ask Questions

BERTering RAMS: What and How Much does BERT Already Know About Event Arguments? -- A Study on the RAMS Dataset


Oct 09, 2020
Varun Gangal, Eduard Hovy

Figure 1 for BERTering RAMS: What and How Much does BERT Already Know About Event Arguments? -- A Study on the RAMS Dataset
Figure 2 for BERTering RAMS: What and How Much does BERT Already Know About Event Arguments? -- A Study on the RAMS Dataset
Figure 3 for BERTering RAMS: What and How Much does BERT Already Know About Event Arguments? -- A Study on the RAMS Dataset
Figure 4 for BERTering RAMS: What and How Much does BERT Already Know About Event Arguments? -- A Study on the RAMS Dataset
* Accepted for the BlackBoxNLP 2020 Workshop @EMNLP 2020; Pre-camera-ready copy 
  Access Paper or Ask Questions

Detecting Attackable Sentences in Arguments


Oct 06, 2020
Yohan Jo, Seojin Bang, Emaad Manzoor, Eduard Hovy, Chris Reed

Figure 1 for Detecting Attackable Sentences in Arguments
Figure 2 for Detecting Attackable Sentences in Arguments
Figure 3 for Detecting Attackable Sentences in Arguments
Figure 4 for Detecting Attackable Sentences in Arguments
* EMNLP 2020 
  Access Paper or Ask Questions

Extracting Implicitly Asserted Propositions in Argumentation


Oct 06, 2020
Yohan Jo, Jacky Visser, Chris Reed, Eduard Hovy

Figure 1 for Extracting Implicitly Asserted Propositions in Argumentation
Figure 2 for Extracting Implicitly Asserted Propositions in Argumentation
Figure 3 for Extracting Implicitly Asserted Propositions in Argumentation
Figure 4 for Extracting Implicitly Asserted Propositions in Argumentation
* EMNLP 2020 
  Access Paper or Ask Questions

Explaining The Efficacy of Counterfactually-Augmented Data


Oct 06, 2020
Divyansh Kaushik, Amrith Setlur, Eduard Hovy, Zachary C. Lipton

Figure 1 for Explaining The Efficacy of Counterfactually-Augmented Data
Figure 2 for Explaining The Efficacy of Counterfactually-Augmented Data
Figure 3 for Explaining The Efficacy of Counterfactually-Augmented Data
Figure 4 for Explaining The Efficacy of Counterfactually-Augmented Data

  Access Paper or Ask Questions